Valuing Weather and Climate: Economic Assessment of Meteorological and Hydrological Services

Valuing Weather and Climate: Economic Assessment of Meteorological and Hydrological Services
Valuing Weather and Climate:
Economic Assessment of
Meteorological and
Hydrological Services
WMO-No. 1153
Valuing Weather and Climate:
Economic Assessment of
Meteorological and
Hydrological Services
WMO-No. 1153
2015
EDITORIAL NOTE
METEOTERM, the WMO terminology database, may be consulted at http://www.
wmo.int/pages/prog/lsp/meteoterm_wmo_en.html. Acronyms may also be found at
http://www.wmo.int/pages/themes/acronyms/index_en.html.
WMO-No. 1153
© World Meteorological Organization, 2015
The findings, interpretations, and conclusions expressed in this work do not necessarily
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ISBN 978-92-63-11153-1
Cover illustrations: Jürgen Mai (ESA), Stephan Bachenheimer (World Bank), Shutterstock
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CONTENTS
PREFACE��������������������������������������������������������������������������������������������������������������������������������������������� ix
ACKNOWLEDGEMENTS���������������������������������������������������������������������������������������������������������������xiii
EXECUTIVE SUMMARY������������������������������������������������������������������������������������������������������������������ xv
CHAPTER 1. INTRODUCTION�������������������������������������������������������������������������������������������������������� 1
1.1 Meteorological, hydrological and related services����������������������������������������������������������� 1
1.1.1
Meteorological services ����������������������������������������������������������������������������������������� 2
1.1.2 Hydrological services����������������������������������������������������������������������������������������������� 3
1.1.3 National service provision��������������������������������������������������������������������������������������� 3
1.1.4
Challenges facing National Meteorological and Hydrological
Services����������������������������������������������������������������������������������������������������������������������� 4
1.2 Economic valuation of met/hydro services������������������������������������������������������������������������� 6
1.3 Objectives of this publication ����������������������������������������������������������������������������������������������� 9
1.4Roadmap��������������������������������������������������������������������������������������������������������������������������������� 10
References ����������������������������������������������������������������������������������������������������������������������������������������� 12
CHAPTER 2. THE PRODUCTION, DELIVERY AND USE OF MET/HYDRO
SERVICES ������������������������������������������������������������������������������������������������������������������������������������������15
2.1Introduction��������������������������������������������������������������������������������������������������������������������������� 15
2.2 Nature and scope of met/hydro services ������������������������������������������������������������������������� 16
2.3 Service delivery ��������������������������������������������������������������������������������������������������������������������� 19
2.4 Users of met/hydro services�������������������������������������������������������������������������������������������������20
2.5 Generating value from services�������������������������������������������������������������������������������������������21
2.6Conclusions ���������������������������������������������������������������������������������������������������������������������������23
References�������������������������������������������������������������������������������������������������������������������������������������������23
CHAPTER 3. THE PURPOSES OF SOCIOECONOMIC BENEFIT
ASSESSMENTS OF MET/HYDRO SERVICES ������������������������������������������������������������������������������24
3.1Introduction���������������������������������������������������������������������������������������������������������������������������24
3.2 Evaluating met/hydro services �������������������������������������������������������������������������������������������24
3.3 Target audiences for socioeconomic benefit studies �����������������������������������������������������26
3.3.1 Governing decisionmakers�����������������������������������������������������������������������������������27
3.3.2 Public and sectoral users���������������������������������������������������������������������������������������28
3.3.3 National Meteorological and Hydrological Service staff���������������������������������29
3.4 Reasons to carry out a socioeconomic benefit study �����������������������������������������������������29
3.4.1 Validating the provision of basic met/hydro services��������������������������������������30
3.4.2 Validating past and current investments in specialized
met/hydro services�������������������������������������������������������������������������������������������������31
3.4.3 Justifying new investments in met/hydro services�������������������������������������������32
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VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
3.4.4 Determining the value of NMHSs to user goals�����������������������������������������������33
3.4.5 Prioritization or reallocation of resources�����������������������������������������������������������33
3.5Conclusions�����������������������������������������������������������������������������������������������������������������������������34
References �����������������������������������������������������������������������������������������������������������������������������������������34
CHAPTER 4. DESIGNING AND COMMISSIONING SOCIOECONOMIC
BENEFIT STUDIES����������������������������������������������������������������������������������������������������������������������������36
4.1Introduction���������������������������������������������������������������������������������������������������������������������������36
4.2 Stage one – Develop the concept note ����������������������������������������������������������������������������� 37
4.3 Stage two – Prepare the scope of work�����������������������������������������������������������������������������39
4.3.1 Socioeconomic benefit study step 1: Establish the baseline���������������������������42
4.3.2 Socioeconomic benefit study step 2: Identify change(s) in
National Meteorological and Hydrological Services��������������������������������������� 43
4.4 Stage three – Commission the study��������������������������������������������������������������������������������� 43
4.5 Stage four – Conduct the study�������������������������������������������������������������������������������������������44
4.6 Stage five – Communicate the study results���������������������������������������������������������������������44
4.7Conclusions�����������������������������������������������������������������������������������������������������������������������������45
References�������������������������������������������������������������������������������������������������������������������������������������������45
CHAPTER 5. ECONOMIC ESSENTIALS ��������������������������������������������������������������������������������������46
5.1Introduction���������������������������������������������������������������������������������������������������������������������������46
5.2 Met/hydro services inform decisions���������������������������������������������������������������������������������46
5.3 Adding up economic value: Benefits and costs���������������������������������������������������������������48
5.4 Scarcity and opportunity cost���������������������������������������������������������������������������������������������49
5.5 Met/hydro services as public goods�����������������������������������������������������������������������������������50
5.6 Adding up over time: Discounting and present values���������������������������������������������������51
5.7 Variability, uncertainty and risk�������������������������������������������������������������������������������������������53
5.8 Met/hydro services enter the market place – Supply and demand �����������������������������54
5.9Conclusions�����������������������������������������������������������������������������������������������������������������������������55
References�������������������������������������������������������������������������������������������������������������������������������������������55
CHAPTER 6. DEFINING AND MEASURING BENEFITS������������������������������������������������������������56
6.1Introduction���������������������������������������������������������������������������������������������������������������������������56
6.2 Understand the value chain�������������������������������������������������������������������������������������������������56
6.3 Socioeconomic benefit study step 3: Identify the full range of benefits���������������������59
6.4 Socioeconomic benefit study step 4:
Screen the benefits and select the analytical approach �������������������������������������������������62
6.5 Socioeconomic benefit study step 5:
Analyse the value of benefits – quantitative���������������������������������������������������������������������62
6.5.1 Non-market valuation techniques�����������������������������������������������������������������������63
6.5.2 Economic decision modelling �����������������������������������������������������������������������������68
6.5.3 Avoided cost/damage assessments, including avoided
mortality and morbidity impacts �����������������������������������������������������������������������71
6.5.4 Benefit transfer������������������������������������������������������������������������������������������������������� 74
CONTENTS
v
6.6
Socioeconomic benefit study step 6:
Analyse the value of benefits – qualitative �����������������������������������������������������������������������77
6.7Conclusions�����������������������������������������������������������������������������������������������������������������������������78
References�������������������������������������������������������������������������������������������������������������������������������������������78
CHAPTER 7. DEFINING AND MEASURING COSTS������������������������������������������������������������������81
7.1Introduction���������������������������������������������������������������������������������������������������������������������������81
7.2 Concepts for defining, measuring, attributing and aggregating costs�����������������������81
7.3 Socioeconomic benefit study step 3: Identify the full range of costs���������������������������82
7.3.1
National Meteorological and Hydrological Service and
commercial weather service costs�����������������������������������������������������������������������84
7.3.2 User costs�����������������������������������������������������������������������������������������������������������������85
7.4 Socioeconomic benefit study step 4:
Screen costs and select the analytical approach �������������������������������������������������������������86
7.5 Socioeconomic benefit study step 5: Analyse the value of costs –
quantitative�����������������������������������������������������������������������������������������������������������������������������87
7.5.1 Treatment of capital costs�������������������������������������������������������������������������������������88
7.5.2 Treatment of prices�������������������������������������������������������������������������������������������������88
7.5.3 Attributing joint costs �������������������������������������������������������������������������������������������90
7.5.4 Assigning prices to public goods and subsidized goods �������������������������������91
7.5.5 Opportunity costs of public funds ���������������������������������������������������������������������92
7.5.6 Substituting capital for labour (automation)����������������������������������������������������93
7.5.7Uncertainty�������������������������������������������������������������������������������������������������������������94
7.6 Socioeconomic benefit study step 6: Analyse the value of costs –
qualitative�������������������������������������������������������������������������������������������������������������������������������94
7.7Conclusions�����������������������������������������������������������������������������������������������������������������������������94
References�������������������������������������������������������������������������������������������������������������������������������������������95
CHAPTER 8. BENEFIT–COST ANALYSIS��������������������������������������������������������������������������������������96
8.1Introduction���������������������������������������������������������������������������������������������������������������������������96
8.2 Benefit–cost analysis concepts �������������������������������������������������������������������������������������������96
8.2.1 Benefit–cost analysis decision criteria – Net societal benefit �������������������������96
8.2.2 Selecting the discount rate�����������������������������������������������������������������������������������97
8.3 Socioeconomic benefit study step 7:
Summarize and compare all benefits and costs���������������������������������������������������������������99
8.3.1 Net present value and project decision criteria�������������������������������������������������99
8.3.2 Reporting qualitative benefit and cost information���������������������������������������103
8.3.3 Distributional issues���������������������������������������������������������������������������������������������103
8.4 Socioeconomic benefit study step 8:
List all omissions, biases and uncertainties ���������������������������������������������������������������������104
8.5 Socioeconomic benefit study step 9:
Conduct sensitivity analyses on key variable values �����������������������������������������������������105
8.6Conclusions���������������������������������������������������������������������������������������������������������������������������108
References ���������������������������������������������������������������������������������������������������������������������������������������108
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VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
CHAPTER 9. SOCIOECONOMIC BENEFIT STUDY STEP 10:
COMMUNICATING THE RESULTS OF SOCIOECONOMIC BENEFIT
STUDIES ������������������������������������������������������������������������������������������������������������������������������������������110
9.1Introduction ������������������������������������������������������������������������������������������������������������������������� 110
9.2 User interaction, satisfaction and value��������������������������������������������������������������������������� 110
9.3 Understanding and interpreting socioeconomic benefit study results ������������������� 111
9.3.1 Policy aspects ������������������������������������������������������������������������������������������������������� 111
9.3.2 Economic aspects������������������������������������������������������������������������������������������������� 112
9.4 Socioeconomic benefits study results translated into an audience
message��������������������������������������������������������������������������������������������������������������������������������� 114
9.5 Internal and external interpretation of the socioeconomic benefit study����������������� 115
9.5.1 Internal audience������������������������������������������������������������������������������������������������� 115
9.5.2 External audiences����������������������������������������������������������������������������������������������� 116
9.6 Audience diversification and varying distribution channels��������������������������������������� 118
9.7 Target audiences ����������������������������������������������������������������������������������������������������������������� 119
9.8 Analysing the overall success of a socioeconomic benefit study
communication strategy ���������������������������������������������������������������������������������������������������122
9.9Conclusions���������������������������������������������������������������������������������������������������������������������������122
References ���������������������������������������������������������������������������������������������������������������������������������������122
CHAPTER 10. LOOKING FORWARD������������������������������������������������������������������������������������������124
10.1 Guiding increased benefit delivery by National Meteorological and
Hydrological Services���������������������������������������������������������������������������������������������������������124
10.1.1 Supporting sustainable development through better-informed
services�������������������������������������������������������������������������������������������������������������������124
10.1.2 Decisionmaking needs good data �������������������������������������������������������������������125
10.1.3 Increasing value with better access to services�����������������������������������������������126
10.1.4 Increasing value with better utilization of services ���������������������������������������128
10.2 Enhancing the quality and utilization of socioeconomic benefit analysis�����������������129
10.2.1 Linking communities�������������������������������������������������������������������������������������������129
10.2.2 Monitoring and evaluation���������������������������������������������������������������������������������129
10.3 Goals for the future�������������������������������������������������������������������������������������������������������������130
References����������������������������������������������������������������������������������������������������������������������������������������� 132
APPENDIX A. GLOSSARY OF TECHNICAL TERMS����������������������������������������������������������������133
References�����������������������������������������������������������������������������������������������������������������������������������������146
APPENDIX B. METEOROLOGICAL, HYDROLOGICAL AND RELATED
SERVICES ����������������������������������������������������������������������������������������������������������������������������������������148
B.1Introduction�������������������������������������������������������������������������������������������������������������������������148
B.2 Meteorology, hydrology and oceanography�����������������������������������������������������������������150
B.3 Weather, climate and water����������������������������������������������������������������������������������������������� 151
B.4 Weather-, climate- and water-sensitive activities, sectors and countries�������������������152
B.5 Impacts of weather, climate and water���������������������������������������������������������������������������153
CONTENTS
vii
B.6 Origin of met/hydro services���������������������������������������������������������������������������������������������153
B.7 Nature and scope of met/hydro services �����������������������������������������������������������������������154
B.8 Economic characteristics of met/hydro services �����������������������������������������������������������155
B.9 Providers of meteorological and related services����������������������������������������������������������� 157
B.10 Users of met/hydro services�����������������������������������������������������������������������������������������������158
B.11 National Meteorological Services�������������������������������������������������������������������������������������158
B.12 National Hydrological Services�����������������������������������������������������������������������������������������159
B.13 International coordination of met/hydro services���������������������������������������������������������160
B.14 Level and quality of service �����������������������������������������������������������������������������������������������161
B.15 Service delivery �������������������������������������������������������������������������������������������������������������������162
B.16 Application of met/hydro services in decisionmaking �������������������������������������������������162
B.17 Funding, pricing and charging for services���������������������������������������������������������������������163
References�����������������������������������������������������������������������������������������������������������������������������������������164
APPENDIX C. A SHORT HISTORY OF STUDIES OF SOCIOECONOMIC
BENEFITS OF METEOROLOGICAL AND HYDROLOGICAL SERVICES������������������������������168
C.1Introduction�������������������������������������������������������������������������������������������������������������������������168
C.2 Original motivation for provision of meteorological services�������������������������������������168
C.3 Early work on the economics of meteorological information and
services����������������������������������������������������������������������������������������������������������������������������������170
C.4 Economic studies in support of World Weather Watch �����������������������������������������������170
C.5 The 1970s and early 1980s�������������������������������������������������������������������������������������������������171
C.6 The World Meteorological Organization conferences of 1987, 1990 and
1994���������������������������������������������������������������������������������������������������������������������������������������172
C.7 Climate information and services�������������������������������������������������������������������������������������173
C.8 World Meteorological Organization economic framework����������������������������������������� 174
C.9 Madrid Conference and Action Plan ������������������������������������������������������������������������������� 174
C.10 World Meteorological Organization Task Force, Forum and postMadrid activities ����������������������������������������������������������������������������������������������������������������� 175
C.11 World Bank studies of economic benefits����������������������������������������������������������������������� 176
C.12 Global Framework for Climate Services and Climate Services
Partnership activities�����������������������������������������������������������������������������������������������������������177
C.13 Recent studies�����������������������������������������������������������������������������������������������������������������������177
C.14 Valuation methodologies���������������������������������������������������������������������������������������������������178
References�����������������������������������������������������������������������������������������������������������������������������������������179
APPENDIX D. COMPLEMENTARY ROLES FOR OTHER SOCIAL SCIENCE
APPLICATIONS IN SOCIOECONOMIC BENEFIT STUDIES��������������������������������������������������184
D.1 Introduction: More than just economics�������������������������������������������������������������������������184
D.2 Identifying and understanding user problems, needs and perceptions�������������������186
D.3 Evaluation of met/hydro products or services���������������������������������������������������������������190
D.4 Finding expertise and building capacity to conduct social scientific
research and applications���������������������������������������������������������������������������������������������������194
References�����������������������������������������������������������������������������������������������������������������������������������������194
viii
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
APPENDIX E. CASE STUDIES������������������������������������������������������������������������������������������������������196
E.1 Summary of case study economic assessments�������������������������������������������������������������196
References����������������������������������������������������������������������������������������������������������������������������������������� 213
E.2 Case study 1: Evaluating the economic efficiency of National
Meteorological and Hydrological Services modernization in Europe
and Central Asia �����������������������������������������������������������������������������������������������������������������215
References�����������������������������������������������������������������������������������������������������������������������������������������221
Further reading �������������������������������������������������������������������������������������������������������������������������������221
E.3 Case study 2: Using benefit–cost analysis to evaluate the effectiveness
of a drought early warning and response system in Ethiopia�������������������������������������222
References�����������������������������������������������������������������������������������������������������������������������������������������228
E.4 Case study 3: Quantifying the success of the National Weather Service’s
life-saving Heat Watch/Warning System in Philadelphia���������������������������������������������230
References�����������������������������������������������������������������������������������������������������������������������������������������235
E.5 Case study 4: Applying benefit transfer to evaluate the benefits and
costs of improving met/hydro services to reduce disaster losses in
developing countries ���������������������������������������������������������������������������������������������������������236
References�����������������������������������������������������������������������������������������������������������������������������������������244
E.6 Case study 5: Using crop models and decision analysis to assess the
potential value of global circulation model-based seasonal rainfall
forecasts for crop management in Kenya�����������������������������������������������������������������������245
Reference�������������������������������������������������������������������������������������������������������������������������������������������250
E.7 Case study 6: Assessing the value of met/hydro information in
Switzerland for the aviation transport sector�����������������������������������������������������������������251
References�����������������������������������������������������������������������������������������������������������������������������������������256
E.8 Case study 7: Evaluating the avoided costs of the Finnish
Meteorological Institute’s met/hydro services���������������������������������������������������������������258
References�����������������������������������������������������������������������������������������������������������������������������������������265
E.9 Case study 8: Economic benefits of improved met/hydro services in
Mozambique �����������������������������������������������������������������������������������������������������������������������267
References�����������������������������������������������������������������������������������������������������������������������������������������279
E.10 Case study 9: Socioeconomic evaluation of improving met/hydro
services for Bhutan �������������������������������������������������������������������������������������������������������������280
References�����������������������������������������������������������������������������������������������������������������������������������������286
PREFACE
From 1970 to 2012, 8 835 disasters, 1.94 million deaths and US$ 2.4 trillion of economic
losses were reported globally as a result of weather-, climate- and water-related
disasters, collectively referred to as hydrometeorological disasters. In the last four
decades, the number of reported hydrometeorological disasters has increased almost
fivefold, from about 750 in the period 1971–1980 to about 3 500 during 2001–2010.1
Over the same period, cumulative economic losses have increased more than fivefold,
from US$ 156 billion to US$ 864 billion2 per decade.
Despite this increasing risk, which is due to a number of climatic and non-climatic
factors (including population growth in high-risk areas), improvements in early
warning systems and preparedness are making it possible to limit losses from
hydrometeorological disasters. This would not be possible without the informed use of
constantly improving meteorological, hydrological, oceanographic, social, behavioural
and related information. As forecasting and modelling capabilities improve, some
decisionmakers are going beyond risk mitigation to a more comprehensive risk
management approach that includes adapting to anticipated changes to avoid
damage altogether. Moreover, scientific, technological and social developments such
as the Internet and smartphones have generated an ongoing revolution in the demand
for and availability of weather, climate, water and related information services.
Hundreds of millions of people and organizations are gaining access to these services
and using them in decisionmaking with greatly enhanced public and private benefit.
Increased and diversified demand provides a great opportunity to improve and extend
hydrometeorological services. However, it also poses new challenges for service
providers in prioritizing investment in the underpinning infrastructure, advancement
of knowledge and generation of understanding, versus designing and financing
service delivery. Easier access to a growing volume of data and information requires
higher reliability, targeting, understandability, and decision-support services to ensure
information is used appropriately and with due regard to inherent limitations and
uncertainties. To optimally invest and meet rapidly evolving demands, more rigorous
and comprehensive methodologies for understanding user needs and evaluating the
benefits of the enabling infrastructure and of the provided hydrometeorological and
related services are needed.
National Meteorological and Hydrological Services (NMHSs), central governments and
development agencies need to understand the full value of the socioeconomic benefits
(SEBs) provided by hydrometeorological services, as well as the financial realities of
maintaining modern operations and service delivery, so that adequate financing can be
mobilized and invested strategically to ensure a significant impact of investment. This is
particularly true in developing countries where many NMHSs are not currently able to
fully provide basic services to help save lives and support economic development.
1
World Meteorological Organization, Centre for Research on the Epidemiology of Disasters and
Université Catholique de Louvan, 2014: Atlas of Mortality and Economic Losses from Weather, Climate
and Water Extremes (1970–2012) (WMO-No. 1123). Geneva, http://www.wmo.int/pages/prog/drr/
transfer/2014.06.12-WMO1123_Atlas_120614.pdf.
2
Values not adjusted for inflation.
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VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
Since the 1950s, the interest in the economic valuation of hydrometeorological services
has been growing in the hydrometeorological, climate and economics communities.
As part of a process of improving the understanding of SEBs of hydrometeorological
services, the World Meteorological Organization’s (WMO) high-level international
conference “Secure and Sustainable Living: Social and Economic Benefits of Weather,
Climate, and Water Services”, held in Madrid in 2007, agreed on a Statement and
Action Plan that sets out a comprehensive strategy for the enhancement, development
and application of improved methodologies for evaluating the benefits from the
operation of NMHSs. The present publication addresses the growing interest and need
identified during this conference and in the years since it took place. It is directed at the
hydrometeorological and socioeconomic research and service-provider communities,
as well as officials from government and international development agencies; but the
general public will also find an interest in understanding the role weather, climate and
water information plays in their daily life.
The World Bank Group, with a current hydrometeorological investment portfolio of
around US$ 500 million, estimates that globally improved weather, climate, and water
observation and forecasting could lead to up to US$ 30 billion per year in increases in
global productivity and up to US$ 2 billion per year in reduced asset losses.3 This scale
of improved productivity could be crucial to lifting out of poverty the millions around
the world whose livelihoods are at risk of climate shocks. The recognition of these
benefits and their contribution to sustainable development, poverty reduction and
shared prosperity is motivating the development community to invest more holistically
in modernizing hydrometeorological services4 and ensuring that service providers are
better connected with service users.
The review of all past and current SEB analysis performed for this publication indicates
that properly planned investments in hydrometeorological services provide significant
benefits relative to their costs. While the publication attempts to capture the currently
available wealth of experience and expertise across different contexts, it is not the end
point for developing global knowledge on SEB analysis of hydrometeorological studies.
Indeed, as we move to implement new global commitments on sustainable
development goals, climate change adaptation and disaster risk reduction, interest in
knowledge, expertise and implementation of SEB studies for hydrometeorological
services will continue to grow.
Further, the Global Framework for Climate Services (GFCS) – an initiative of the United
Nations adopted by the World Meteorological Congress in 2012 after the call of the
third World Climate Conference in 2009 – promotes better access and use of climate
information by users; encouragement of global, free and open exchange of climaterelevant data as an international public good; and multidisciplinary partnerships. The
implementation of GFCS facilitates the delivery of goods and benefits in key economic
3
Hallegatte, S., 2012: A Cost Effective Solution to Reduce Disaster Losses in Developing Countries: HydroMeteorological Services, Early Warning and Evacuation. World Bank policy research paper No. 6058.
Washington, D.C., World Bank.
4
Rogers, D.P. and V.V. Tsirkunov, 2013: Weather and Climate Resilience: Effective Preparedness through
National Meteorological and Hydrological Services. Directions in Development. Washington, D.C.,
World Bank.
xi
Preface
sectors such as agriculture and food security, health, energy, disaster risk management,
water resources management and urban environments. The present publication should
provide strong analytical support for implementation of GFCS, providing a broader
platform within which to use SEB studies to improve hydrometeorological services.
We hope this publication will be useful to make more evident and enhance the SEBs
that NMHSs of the world deliver daily to society and will help mobilize and optimize
financing to ensure NMHSs can fulfil their critical role in an even more effective way.
Jeremiah Lengoasa
James Close
David Yoskowitz
Deputy Secretary-General
of the World
Meteorological
Organization
Director,
Climate Change Policy and
Finance Group, World
Bank Group
Chief Economist,
National Oceanic and
Atmospheric
Administration, United
States Department of
Commerce
ACKNOWLEDGEMENTS
The publication was produced and edited by a team led by Glen Anderson, United
States Agency for International Development (USAID) Climate Change Resilient
Development Project and Engility Corporation*; Haleh Kootval, WMO*; and Daniel
Kull, Global Facility for Disaster Reduction and Recovery (GFDRR), World Bank Group*.
The author team, which includes the editors, was comprised of Janet Clements, Stratus
Consulting*; Gerald Fleming, Met Éireann (Ireland)*; Thomas Frei, Independent
Research Consultant, Zurich, Switzerland; Jeffrey Lazo, National Center for
Atmospheric Research*; David Letson, Department of Marine Ecosystems and Society,
University of Miami*; Brian Mills, Atmospheric Impacts and Adaptation, Environment
Canada*; Adriaan Perrels, Finnish Meteorological Institute (FMI)*; David Rogers,
Health and Climate Foundation and GFDRR, World Bank Group; Catherine Vaughan,
International Research Institute for Climate and Society, Earth Institute, Columbia
University*; and John Zillman, WMO and Australian Academy of Technological
Sciences and Engineering*. Schuyler Olsson, Engility Corporation and USAID Climate
Change Resilient Development Project, assisted in the preparation of Appendix A.
The editor and author team would like to thank the following for their guidance and
support throughout the development of the publication: Marianne Fay, Climate
Change Vice Presidency, World Bank Group; John Furlow, Global Climate Change
Office, USAID; Francis Ghesquiere, Disaster Risk Management Practice, World Bank
Group and GFDRR; and Tang Xu, WMO.
For the peer review of the publication, the team thanks Kwabena Asomanin Anaman,
Institute of Statistical, Social and Economic Research, University of Ghana (with
assistance from Felix Agyei-Sasu and Akosua Sarpomaa Dwira, University of Ghana);
Paul Davies, Met Office, United Kingdom of Great Britain and Northern Ireland;
Laurent Dubus, Research and Development, Électricité de France (EDF)*; Beth Ebert,
Centre for Australian Weather and Climate Research, Bureau of Meteorology; Stephane
Hallegatte, Climate Change Vice Presidency, World Bank Group*; Gordon McBean,
Department of Geography, Western University and International Council for Science;
Craig Meisner, Environment and Natural Resources Global Practice, World Bank Group;
Jiao Meiyan, China Meteorological Administration; Claudia Sadoff, Water Global
Practice, World Bank Group; Thomas Schuhmacher, Deutscher Wetterdienst; Kevin
Simmons, Corrigan Chair of Economics, Austin College; Douglas Smith, Department of
Economics, Carleton University; Bruce Stewart, WMO; Vladimir Tsirkunov, GFDRR,
World Bank Group; Rob Varley, Met Office, United Kingdom; and Peter Williams, High
Performance Computing Programme Office, Met Office, United Kingdom.
Special thanks to Jamie Carson, C.C. Global, Inc. and USAID Climate Change Resilient
Development Project, for her support over several months with technical editing and
for managing the revision process to address several hundred proposed edits and
comments provided by reviewers.
For all of the contributions and comments from the peer-review group, thank you to
Henrike Brecht, Urban, Rural and Social Development Global Practice, World Bank
xiv
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
Group; Ray Canterford, Commission for Instruments and Methods of Observation,
WMO; Jan Daňhelka, Czech Hydrometeorological Institute*; Devcharan Dubey, India
Meteorological Department, Meteorological Centre*; Juan Andres Elhordoy Gasparri,
Agriculture and Fisheries of Uruguay*; Moritz Flubacher, Cornelia Giger, Andrea Rossa
and Gabriela Seiz, International Affairs Division, Federal Office of Meteorology and
Climatology (MeteoSwiss), Switzerland; Don Gunasekera, Institute for Supply Chain
and Logistics, Victoria University; Lucy Hancock, GFDRR, World Bank Group; Chris
Hewitt, Met Office Climate Service, United Kingdom; William Hooke, American
Meteorological Society; Michel Jancloes, Health and Climate Foundation*; George
Kordzakhia, Department of Hydrometeorology (Georgia)*; Azarel Mariner, Secretariat
of the Pacific Regional Environment Programme*; Pierre-Philippe Mathieu, Earth
Observation Science and Applications Department, European Space Agency; LV
Minghui, China Meteorological Administration*; Samuel W. Muchemi, WMO*;
Nhlanhla Nhlonipho Nhlabasti, South African Weather Service*; Kevin O’Loughlin,
Trusted Magazine and Clear Weather Leaders; Carmen Rus, State Meteorological
Agency (Spain)*; Andrea Sealy, Caribbean Institute for Meteorology and Hydrology*;
Shaffiq Somani, Water Global Practice, World Bank Group; Asunción Lera St. Clair,
Center for International Climate and Environmental Research – Oslo*; and Joanna
Watkins, Governance Global Practice, World Bank Group.
* Participants at the 2013 meeting of the WMO “Forum on Social and Economic Applications and
Benefits of Weather, Climate and Water Services”, WMO, Geneva, Switzerland, 8–11 April 2013.
These participants led the groundtruthing session that developed the concept of this publication.
EXECUTIVE SUMMARY
For more than a century, nations have equipped themselves to provide weather,
climate and hydrological information, forecasts and, more recently, remotely sensed
data and early warnings to the public and private sectors. These services, collectively
referred to throughout this publication as met/hydro services, have increased the
safety and efficiency of land, sea and air transport, helped communities prepare for
and respond to extreme weather events, and facilitated improved decisionmaking in
weather-sensitive economic sectors. Increasingly, it has become easier for people and
businesses to access met/hydro information and products due to advances in the
Internet and telecommunications.
Yet, as NMHSs strive to maintain and improve the quality, diversity, and coverage of
their services, they face challenges similar to other public institutions in securing
adequate and sustained funding. To compete for and optimize the use of scarce public
investment resources, NMHSs may be required to demonstrate that the benefits of
their services are significantly larger than the costs to produce and deliver them.
Although there is not a single definitive study on the global benefits of met/hydro
services, economic studies have
Illustrative economic assessments
consistently generated benefit–cost
of met/hydro services
ratios (BCRs) of greater than one (see
– NMHS improvements to reduce disaster
box). This publication is intended to
losses in developing countries – BCRs range
help NMHSs and other providers of
from 4 to 1 to 36 to 1
met/hydro services develop a basic
– Current and improved weather forecasts in
understanding of economic valuation
the United States of America assessed for
methods to enable them to design
households – BCR of at least 4 to 1
and commission studies. It further
– Drought early warning system in Ethiopia to
reduce livelihood losses and dependence on
supports utilization of the results to
assistance – BCRs range from 3 to 1 to 6 to 1
improve service delivery through
– El Niño early warning system in a five-state
business optimization and
region of Mexico to improve decisionmaking
communication with decisionmakers,
in agriculture – BCRs range from 2 to 1 to 9 to 1
users and the public.
CREATING VALUE: LINKING PRODUCTION AND DELIVERY OF SERVICES TO
VALUED OUTCOMES
Met/hydro services do not generate economic and social value unless users benefit
from decisions as a result of the information provided, even if the services are of the
highest quality. In addition, met/hydro services of similar quality provided in two
countries can vary significantly in terms of their benefits depending on the relative
nature of weather- and climate-related risks, the number and types of users and their
capacity to take actions to avoid harm or increase economic output.
The generation of met/hydro services benefits can be depicted in a “value chain”
linking the production and delivery of services to user decisions and the outcomes and
values resulting from those decisions. The value chain presented in the figure below
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VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
COMMUNICATION PROCESSES
Weather
Climate
Water
SERVICE
PRODUCTION
Processing & data management
Weather/
climate/
water
Observations
Modelling
Forecasting
Service delivery
Research & development
Basic & specialized
services
NMHS & commercial
providers
User decisions
&
actions
Outcomes
VALUE
Benefits & costs
VALUEADDING PROCESSES
(and featured in Chapter 2) can be used to illustrate the production and delivery of the
entire suite of met/hydro services provided by NMHSs or to describe a single new or
existing service. How the value chain is specified depends on the met/hydro services to
be valued and the reasons for conducting the valuation study.
As is discussed in Chapter 3, the valuation study can be designed for the purpose of
validating the current provision of individual or all met/hydro services, justifying new
investments in those services, or demonstrating the value of met/hydro services in key
sectors such as agriculture, aviation or energy.
PLANNING THE STUDY
Chapter 4 provides a discussion of the process for planning, commissioning and
conducting SEB studies. On the assumption by the authors that few NMHSs would
conduct in-house economic studies, it is envisioned that a concept note will be
prepared to secure resources for the study in terms of financing, expertise and access
to the necessary information and data. The concept note will provide information on
reasons for conducting the study, the services and user communities to be assessed,
costs and time frame, valuation methods proposed and plans for disseminating the
results of the study. Chapter 4 also describes the elements of a detailed scope of work
required for procurement and to guide preparation of the study and dissemination of
the study’s results to decisionmakers and stakeholders.
CONDUCTING THE SOCIOECONOMIC BENEFIT STUDY
Socioeconomic benefit studies to support investment decisions will typically involve
analysis of benefits and costs and a comparison of benefits and costs using the net
benefits (benefits minus costs) or benefit–cost criteria. The diagram describes the
10 steps that are undertaken in conducting an SEB study.
xvii
Executive summary
Chapters 5 to 8 provide the reader with the essential economics material covering
steps 3 to 9 in the diagram. For readers not conversant with economics, Chapter 5
provides an introduction to definitions and concepts needed to understand the
discussions of benefits, costs and benefit–cost analysis (BCA) presented in Chapters 6,
7 and 8.
Chapter 6 provides an overview of the extensive variety of methods that have been
used to assess the benefits of met/hydro services. The methods can be tailored to
different users and benefit streams (avoided costs or damages, higher profits or
increased social welfare). Some methods, particularly where more precise results are
required, will involve extensive data collection, surveys of user preferences and
willingness to pay (WTP) for services, or economic modelling, while other methods
such as benchmarking and benefit transfer are reasonably inexpensive to apply. In
collaboration with their SEB study implementers, NMHSs will need to select the
benefits estimation method(s) most suitable to the services and types of users to be
assessed, while accounting for resource and time constraints.
SEB STUDY STEPS
SEB study step 1: Establish the baseline
SEB study step 2: Identify changes in NMHS service(s)
SEB study step 3: Identify full range of benefits and costs
SEB study step 4: Screen benefits and costs and select
analytical approach
Quantitative
Qualitative
SEB study step 5: Assess the value
of benefits and costs
in monetary terms, to the extent
feasible
SEB study step 6: Qualitatively
describe key benefits and costs
for which quantification is not
appropriate or feasible
SEB study step 7: Summarize and compare all benefits and costs
SEB study step 8: List all omissions, biases and uncertainties
SEB study step 9: Conduct sensitivity analyses
on key variable values
SEB study step 10: Formulate and communicate results
to decisionmakers and stakeholders
Involve stakeholders
Analyse benefits and costs
xviii
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
Given the experience of NMHSs in preparing budgets, the discussion of costs in
Chapter 7 will be more familiar. However, some adjustments are required in converting
budget information and expenditures, particularly for capital investments, into
economic costs that can be compared to benefits. In addition, SEB studies may also
require consideration of costs incurred by users to benefit from met/hydro services.
Chapter 8 describes the criteria and methods that are used to compare benefits and
costs and explains how these values are discounted and aggregated. Chapter 8 also
provides some guidance on how to present benefit–cost results to demonstrate
sensitivity to underlying assumptions and uncertainty.
Chapter 9 covers the important topic of communicating the results of SEB studies, the
range of audiences and the types of messages to be delivered via radio, television, the
print media, Internet, SMS text messaging and public meetings. Communication
efforts as well as assessment of benefits should be part of a continuous process of
education, outreach and review of the quality and uptake of met/hydro services.
Internal communication to inform prioritization and business planning is also
highlighted.
The publication also includes five appendices covering a glossary of met/hydro and
economic terms, historical background on the global development of met/hydro
services and progress in estimating benefits of these services, a survey of
non-economics social science methods for assessing the quality of met/hydro services,
and summaries of nine SEB studies.
As noted in the concluding chapter, there is still much work to be done to help NMHSs
and other providers to make the financial case to sustain and increase the quality and
coverage of met/hydro services. Chapter 10 also highlights the value that open-data
and open-access approaches can add. There are significant gaps in the application of
benefits estimation methods, regional coverage of studies (particularly in developing
countries), and studies for key economic sectors. The authors hope the publication
increases the understanding of the potential value of SEB studies and serves as a
catalyst for future studies.
CHAPTER 1. INTRODUCTION
METEOROLOGICAL, HYDROLOGICAL AND RELATED SERVICES
1.1
Meteorological, hydrological and related conditions affect everyone on the planet. The
variability of the atmosphere and of the underlying land and ocean, on timescales from
minutes and hours to decades and centuries, exerts a major influence on the general
public and national economies (see Figure 1.1).5 Extremes in temperature, precipitation
and wind and other natural hazards impact every country and every sector of society.
Rarely does a day go by without news of a weather-related disaster somewhere in the
world or new information on the expected impacts of human-induced climate change.
The informed use of meteorological, hydrological, oceanographic and related
information can deliver enormous benefits to society. Reliable weather, climate and
water information enables individuals, households, organizations, businesses and
governments to take decisions which reduce the impacts of natural hazards, enhance
the safety and convenience of daily life, increase business profitability, address the
challenges of public health and poverty alleviation, improve productivity, strengthen
national economies, protect the environment and provide a more secure basis for
future planning on hourly to century timescales.
1 century
Characteristic lifetime of event
1 decade
1 year
Climate prediction and projection
Climate
change
El Niño
Seasonal to interannual climate prediction
Monsoon
1 month
Mid-latitude
weather system
1 day
Tropical cyclone
Cold front
Thunderstorm
1 hour
Tornado
1 minute
Weather forecasting
10 m
100 m
1
10
100
1 000
10 000
100 000
Characteristic size of event (kilometres)
Figure 1.1. Time and space scales of weather and climate
Source: World Bank (2013a)
5
See Figure 2.2 for a more detailed version.
2
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
The second half of the twentieth century witnessed innovation and expansion in the
quantity, quality and availability of weather and climate information and the
development of a wide range of meteorological, hydrological, oceanographic and
other environmental services for individual social and economic sectors and for
communities at large. The provision of state-of-the-art forecast, warning and advisory
services for their national communities became a widely accepted responsibility of
governments in both developed and developing countries. Numerous studies
provided compelling evidence of the social, economic and environmental benefits of
the services and the importance of continuing investment in national and international
infrastructures and the scientific research on which they were based (WMO, 2014).
Internet, smartphone and other scientific, technological and social developments of
recent decades have continued to increase the demand for, and availability of, weather,
climate and related services. Billions of people are gaining access to these services and
using them in decisionmaking with greatly enhanced public and private benefit.
However, this is producing new challenges for the service providers in prioritizing their
investment in the underpinning infrastructure and in designing and funding the
services required. Easier access to the growing volume of data and information is
providing special challenges in ensuring that the quality of the data and information is
as high as possible and that they are used appropriately and with due regard to their
inherent limitations and uncertainties. Improvements in the quality and coverage of
these services, as well as the development of new services, has engendered additional
costs and demand for new, more rigorous and more comprehensive methodologies for
evaluating and demonstrating the benefits of the enabling infrastructure and of the
meteorological, hydrological and related services provided.
This publication outlines a number of methods for evaluating and demonstrating the
economic value of meteorological and hydrological services. First, however, it is
necessary to introduce some basic concepts in meteorological and hydrological service
provision, identify the challenges facing the major national organizations responsible
for these services, and recall the rich history of earlier work on economic valuation on
which this publication is built. The key meteorological, hydrological and economic
terms are briefly explained when first introduced and the sense in which they are used
in this publication is summarized in the glossary provided in Appendix A.
1.1.1
Meteorological services
Meteorological services consist of the provision of information and advice on the past,
present and future state of the atmosphere, including information on temperature,
rainfall, wind, cloudiness, air quality and other atmospheric variables, as well as the
occurrence and impacts of significant weather and climate phenomena such as storms,
flooding, droughts, heatwaves and cold waves. Meteorological services are usually
regarded as falling into the two broad classes of “weather services” and “climate
services” based on the characteristic timescales of weather (minutes to weeks) and
climate (months to centuries), respectively, albeit with substantial overlap between the
two, as well as with hydrological and oceanographic services.
Chapter 1. Introduction
3
Meteorological service provision is an inherently international activity requiring global
coordination, worldwide observation networks and efficient international data
exchange. Over the past 150 years, the global meteorological community has built up
the scientific understanding and technical infrastructure needed to support the
provision of comprehensive weather and climate services to both national and
international users in every country (Daniel, 1973). The global meteorological service
system is based on a strong tradition of voluntary cooperation through WMO, with
every WMO Member country contributing what it can to the international effort and
every country able to draw, according to its needs, on the global system to support the
provision of essential services to its national community (WMO, 1990a). The role of
WMO in international coordination of service provision is summarized in Appendix B
(section B.13).
1.1.2
Hydrological services
Hydrological services consist of the provision of information and advice on the past,
present and future state of rivers, lakes and other inland waters including streamflow,
river and lake levels and water quality. These services focus mainly on the surface
component of the hydrological cycle, through which the rainfall over a catchment is
partitioned between storage, runoff and evaporation back to the atmosphere, which
provides some of the moisture supply for producing clouds and further rain. They also
include information on subsurface (underground) water resources.
The provision of hydrological services has historically been more closely linked with
national and local arrangements for navigation, river management and water supply.
Although there is a long tradition of cooperation within river basins in Europe and
some other parts of the world, hydrological service provision lacks the strong tradition
of voluntary global cooperation, which was a primary factor that shaped the
development of meteorological services worldwide. Since 1975, WMO has served as
the United Nations specialized agency for operational hydrology, and hence for
hydrological service provision (WMO, 2003). Responsibility for scientific hydrology has
in recent decades resided with the International Hydrological Programme of the
United Nations Educational, Scientific and Cultural Organization (UNESCO).
1.1.3
National service provision
Virtually all meteorological, hydrological and related services and the benefits they
provide depend on the existence of an integrated observation, data processing,
information production and service delivery system for the region or country
concerned. Most countries have a long-established system based on the operation of
a primarily government-funded National Meteorological Service (NMS) (WMO, 1999;
Zillman, 1999). In those countries where the NMS also carries hydrological
responsibilities, it is often referred to as a National Hydrometeorological Service,
albeit with the same abbreviation, NMS (WMO, 2000). Many countries, however,
operate a separate National Hydrological Service (NHS), usually in a natural resource
or water-supply ministry (WMO, 2001). The abbreviation NMHS is used in this
4
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
Box 1.1: Important acronyms/abbreviations used in this publication
NMSNational Meteorological or Hydrometeorological Service
NHS
National Hydrological Service
NMHSNational Meteorological and Hydrological Service
publication to refer to an NMS or NHS. The abbreviation NMHSs, in the plural, is used
by WMO as shorthand for NMSs and NHSs (WMO, 2000) (Box 1.1). The director of an
NMS usually, but not necessarily, serves as the permanent representative of their
country with WMO.
In addition to their NMHSs, most countries have a range of public and private service
providers who draw to varying degrees on the basic national meteorological and
hydrological observation and data-processing infrastructure and information to
provide a range of basic (public) and special (user-specific) meteorological and
hydrological services (WMO, 1990b). The essential arrangements for the production,
delivery and application of met/hydro services are introduced in Chapter 2 and
elaborated in greater detail in Appendix B.
Increasingly since the 1980s, one of the major issues of national service provision has
related to the relative roles of the public and private sectors, especially in the
commercialization of meteorological services. This issue was examined in depth in the
context of the United States in the publication Fair Weather: Effective Partnerships in
Weather and Climate Services (National Research Council, 2003), which triggered a
decade of ongoing consultations amongst the public, private and academic sectors
and the adoption of the concept of a national weather, water and climate enterprise.
1.1.4
Challenges facing National Meteorological and Hydrological
Services
The rapidly growing demand for met/hydro services around the world presents major
scientific, operational and public policy challenges for NMHSs that maintain and
operate most of the more than US$ 10 billion in global infrastructure on which the
quality and value of these services ultimately depends (Zillman, 2003). This increasing
demand is diverse in nature and suggests the need for major investments in:
–
Comprehensive, high-quality and robust observational networks;
–
Efficient data collection and management, and rapid information exchange;
–
State-of-the-art information technology and computing facilities;
–
Sophisticated data-analysis schemes and powerful simulation and forecasting
models;
–
Improved understanding of meteorological and hydrological phenomena
through ongoing scientific research;
Chapter 1. Introduction
–
Effective tailoring of services to user needs;
–
Efficient public and private service delivery arrangements;
–
Effective communication of the science, including its limitations and
uncertainties, and its applicability;
–
Improved methodologies and algorithms for use of meteorological, hydrological
and related information in decisionmaking.
In addition to these needs, NMHSs also face broader challenges associated with social
and technological changes that affect the ways in which people and activities are
vulnerable to weather, climate and water influences and how they use meteorological
and hydrological information to reduce risks and vulnerabilities and seize
opportunities. So the challenge facing NMHSs is much more than that of mustering
resources and achieving stability of funding for their infrastructure – their leadership
must also foresee and plan for a wide range of social and technological changes and
their implications for service provision and realization of the benefits available from
effective use of the services. The NMHSs in many countries face major challenges in
ensuring their capacity to meet the ever-growing demand for their services, while
maintaining the integrity of the science that is the basis for these services, as well as
providing authoritative information and advice for decisionmaking by their national
communities.
It has long been understood that investments in NMHSs provide countries with a
greater return of more than an order of magnitude in economic benefits in addition to
their vitally important, but less quantifiable contribution to human safety and wellbeing. This realization, which goes back to the 1960s, has been reinforced over the
years by the wide range of studies summarized briefly in section 1.2. But the
expenditure, both globally and for individual countries, has reached a scale that
requires NMHSs to demonstrate the value of the public investment necessary to
support the level of met/hydro services expected by their governments and national
communities.
The challenges facing NMHSs have to some extent been exacerbated by the diversity
of funding and operational models that have arisen due to pressure on public funds,
commercialization, competition and the challenges of international data exchange
(WMO, 1999). While the experience of the past decade suggests that it is possible to
maintain the overall stability of the international met/hydro service system with a
variety of national funding and operational models (WMO, 2013), many NMHSs have
found that they are in urgent need of:
–
Clearer demonstration of the importance of the underpinning observational and
data-processing infrastructure and supporting research needed to provide
essential public information, forecast and warning services to their national
communities;
5
6
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
–
More rigorous and widely understood demonstration of the SEBs, both public
and private, of the services they provide;
–
A more systematic basis for prioritizing the use of available funding for
infrastructure and service development and improvement;
–
Stronger economic evidence for the substantial additional investment in climate
services infrastructure necessary to support national responsibilities under the
Global Climate Observing System (GCOS), GFCS and the United Nations
Framework Convention on Climate Change.
1.2
ECONOMIC VALUATION OF MET/HYDRO SERVICES
There has been substantial interest since the 1950s in both the meteorological/
hydrological and economics communities in economic valuation of meteorological and
hydrological services (Bijvoet and Bleeker, 1951; Gibbs, 1964; WMO, 1975, 1994a,
2009). This has been driven, in particular, by the promise of the enormous potential
benefits from investment in the space-based observing and digital-computing
technologies of the WMO World Weather Watch (WWW) instituted in 1963 (WMO,
1966; Thompson and Ashford, 1968).
The development and application of economic valuation methodologies accelerated in
the 1980s and early 1990s in response to the increased pressure on the budgets of
NMHSs and the end of the period of rapid growth in investment in international
meteorological infrastructure that had fuelled the establishment of WWW and the
Global Atmospheric Research Programme (GARP). The World Meteorological
Organization sponsored three major international conferences focused on
demonstrating and enhancing the benefits of meteorological and hydrological services
– in the United Kingdom in 1987 (Price-Budgen, 1990), and in Geneva in 1990 and
1994 (WMO, 1990b, 1994b). The two Geneva conferences focused particularly on ways
of bringing the systems and services of NMHSs of the developing countries up to or
nearer the standards of those of developed countries (WMO, 1996).
The 1990s saw increasingly sophisticated national economic valuation studies (for
example, Chapman, 1992; Anaman et al., 1995; Anaman et al., 1998) and the
publication of a comprehensive book on the economic value of weather and climate
forecasts (Katz and Murphy, 1997).
During the second half of the 1990s, the increased focus, in WMO circles, on providing
a more secure legal, economic and policy framework for international meteorological
cooperation generated renewed efforts to establish a systematic and economically
rigorous approach for assessing the economic benefits of NMSs (Freebairn and
Zillman, 2002) and an overall economic framework for meteorological service
provision (WMO, 2002; Gunasekera, 2004). This placed particular emphasis on the
characteristics of public good of most meteorological services (Samuelson, 1954;
Chapter 1. Introduction
7
Heilbroner and Thurow, 1994; Harris, 1995; Stiglitz et al., 2000) and led to renewed
efforts to more clearly define the role of NMHSs in the provision of public and private
met/hydro services.
Economic valuation studies were conducted over the following decade in many
countries and through a number of WMO mechanisms including a WMO “Forum
[initially task force] on Social and Economic Applications and Benefits of Weather,
Climate and Water Services”. This led to the convening of a high-level international
conference in Madrid in March 2007 on “Secure and Sustainable Living: Social and
Economic Benefits of Weather, Climate and Water Services”. The Madrid Conference
Statement and Action Plan (WMO, 2007, 2009) set out a comprehensive five-year
strategy for enhancement of the applications and benefits of met/hydro services
around the world, including a specific call, through its action 11, for the development
and application of improved methodologies for evaluating the benefits from operation
of NMHSs.
The immediate follow-up to the Madrid Conference included the preparation of the
publication Primer on Economics for National Meteorological and Hydrological Services (Lazo
et al., 2009). Subsequent work on the role of the social sciences in enhancing the value
of meteorological and related services and a range of studies associated with
implementation of the new GFCS (Hewitt et al., 2012) and the Climate Services
Partnership (CSP) (for example, Clements et al., 2013; von Flotow and Ludolph, 2013)
has led to increased understanding of the many economic factors influencing the value
of met/hydro services, including the diverse national policy frameworks within which
NMHSs operate. Appendix C provides a short history of met/hydro economic valuation
studies during the past 60 years and Appendix E provides summaries of 10 case studies.
The notion that the benefits of met/hydro services significantly exceed the costs to
produce and deliver these services is not based on a single authoritative global study.
For the purposes of this publication, more than 140 studies of the value of met/hydro
services were reviewed (see Clements et al., 2013). Table 1.1 provides a representative
sample of studies for which both benefits and costs were assessed. The studies cover
assessments for “whole of services”, and also a range of specific met/hydro services in
developed and developing countries for individuals, households, and a variety of
economic sectors. In Table 1.1, BCRs range from 2 to1, to 36 to 1, and in one study, in
which the value of lives was quantified, a BCR of 2 000 to 1 was estimated.6
6
There are numerous factors that influence the magnitude of benefits. Lower levels of benefits may
be observed if there are significant lags in adoption of new services because of the time required to
trust the product. Also, users may have limited capacity, especially in agriculture in developing
countries, to take advantage of improved forecasts to avoid losses or increase profits. In addition, if
there are significant resource and time constraints imposed on the SEB study, analysts may not
consider all user communities or all types of benefits. The value of statistical lives, illness and
morbidity are rarely quantified and can be a significant source of benefits. The level of benefits will
also depend on the starting point or baseline for calculating changes. For example, a new met/
hydro service will typically generate considerably more benefits than one that is improved in
reliability. Ranges are often reported in SEB studies because assumptions must be made about the
way that user communities respond to new or improved services. Analysts will often estimate
benefits for alternative scenarios or assumptions to help decisionmakers and other audiences
understand the sensitivity of results to alternative specifications.
8
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
Table 1.1. Illustrative economic assessments of met/hydro services
SEB study
Geographic
location
Sectors
Benefits methods/
measures
BCR
Contingent valuation study
of the public weather
service in the Sydney
metropolitan area (Anaman
et al., 1998)
Sydney,
Australia
Households
WTP survey of
households
4:1
Economic value of current
and improved weather
forecasts in the United
States household sector
(Lazo and Chestnut, 2002)
United States
Households
WTP survey of
households
4:1 +
Benefits of Ethiopia’s
Livelihoods, Early
Assessment and Protection
(LEAP) drought early
warning and response
system (Law, 2012)
Ethiopia
Households
Quantification of
avoided livelihood
losses and decreased
assistance costs
Success of the United
States National Weather
Service (NWS) Heat
Watch/Warning System
in Philadelphia (Ebi et al.,
2004)
Philadelphia,
Pennsylvania
Households/ Regression analysis
elderly
to determine lives
saved; application
of the United States
Environmental
Protection Agency’s
(EPA) value of a
statistical life (VSL)
estimate
2 000:1 +
The benefits to Mexican
agriculture of an El Niño/
Southern Oscillation
(ENSO) early warning
system (Adams et al., 2003)
Five-state
region in
Mexico
Agriculture
Change in social
welfare based on
increased crop
production with
use of improved
information
2:1 to 9:1
The value of hurricane
forecasts to oil and gas
producers in the Gulf of
Mexico (Considine et al.,
2004)
Gulf of
Mexico
Oil drilling
Value of avoided
evacuation costs and
reduced foregone
drilling time
2:1 to 3:1
Economic efficiency of
NMHS modernization in
Europe and Central Asia
(World Bank, 2008)
Eleven
European
and Central
Asian
countries
Weatherdependent
sectors
Sector-specific and
benchmarking
approaches to
evaluate avoided
losses
2:1 to 14:1
3:1 to 6:1
9
Chapter 1. Introduction
Table 1.1. Illustrative economic assessments of met/hydro services (continued)
SEB study
Geographic
location
Sectors
Benefits methods/
measures
BCR
Benefits and costs of
improving met/hydro
services in developing
countries (Hallegatte, 2012)
Developing
countries
National
level and
weathersensitive
sectors
Benefits-transfer
approach to quantify
avoided asset losses,
lives saved, and
total value added
in weather-sensitive
sectors
4:1 to 36:1
Avoided costs of the
FMI met/hydro services
across economic sectors
(Leviäkangas and Hautala,
2009)
Finland
Key
economic
sectors
Quantification of
avoided costs and
productivity gains;
also used impact
models and expert
elicitation
5:1 to 10:1
Social economic benefits of
enhanced weather services
in Nepal – part of the
Finnish–Nepalese project
(Perrels, 2011)
Nepal
Agriculture,
transport
and
hydropower
Statistical inference
and expert
judgement
10:1
Economic and social
benefits of meteorology
and climatology (Frei,
2010)
Switzerland
Transport,
energy,
aviation,
agriculture,
households
Benefit transfer,
expert elicitation,
decision modelling
5:1 to 10:1
Socioeconomic evaluation
of improved met/hydro
services in Bhutan (PilliSihvola et al., 2014)
Bhutan
National
level
Benefit transfer,
expert elicitation,
cardinal rating
method
3:1
The ratio of benefits to costs in these studies supports the statement by M. Jarraud,
Secretary-General of WMO in 2007: “Traditionally, the overall benefits accrued from
investment made in the meteorological and hydrological infrastructures were
estimated to be, in several countries, in [the] order of 10 to 1” (World Bank, 2013b).
The key conclusion is that met/hydro services provide significant benefits relative to
their costs and SEB studies can play an important role in helping NMHSs make the case
to sustain or increase public investments in these services.
1.3
OBJECTIVES OF THIS PUBLICATION
As a further and more comprehensive response to Action 11 of the Madrid Action Plan,
and following increasing World Bank interest in the benefits available from increased
investment in NMHSs (see, for example, Rogers and Tsirkunov, 2013; World Bank,
2013b, 2014), WMO and the World Bank, with support from USAID for the CSP
10
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
through its Climate Change Resilient Development project, joined forces for the
preparation of this publication. The main objectives of the publication are to:
–
Assist NMHSs in evaluating, demonstrating and enhancing the benefits of the
services they provide;
–
Build increased understanding between meteorologists and hydrologists on the
one hand, and economists and other social scientists on the other;
–
Increase awareness of SEBs of met/hydro services within the current and potential
user communities;
–
Provide a rigorous basis and practical guidance for evaluating the economic
benefits of individual services and components of the service-provision
infrastructure;
–
Assist in communicating the results of SEB studies to users and potential users of
the services, to governments and other funding organizations, and to public and
private decisionmakers at all levels of society.
The publication is addressed to all those in the met/hydro service-provider and user
communities with an interest in evaluating the benefits and costs of the services
provided and, especially, to the meteorologist/hydrologist and economics/social
science staff or advisors of NMHSs charged with designing, guiding and conducting
valuations.
Chapter 1. Introduction
Chapter 2. Met/hydro services
Chapter 3. Purpose of SEB studies
Chapter 4. Designing SEB studies
Chapter 5. Economic essentials
Chapter 6. Benefits
Chapter 7. Costs
Chapter 8. BCA
Chapter 9. Communications
Chapter 10. Looking forward
Figure 1.2. Chapter roadmap
flow diagram
7
1.4
ROADMAP
The flow diagram7 (Figure 1.2) describes the
sequencing of topics in the publication.
Chapters 2, 3 and 4 are designed to help the
reader structure economic valuation and
benefit–cost studies. Chapter 2 provides a brief
introduction to the production and delivery of
met/hydro services and the mechanisms
through which they generate economic value
for their user communities. Most of the material
will be familiar to the service-provider
community, but may provide useful
background for those readers who have not
previously been involved with the provision
and use of met/hydro services. Chapter 3
explains the purpose of conducting SEB studies
for met/hydro services and identifies the
The chapter roadmap appears at the start of each of the 10 chapters to help guide readers through
the SEB assessment/study process. See footnote 2 for more information on SEBs.
Chapter 1. Introduction
11
various audiences interested in the results of such studies.8 Chapter 4 describes the
steps involved in framing and commissioning an assessment, including the
engagement of key stakeholders, detailed scoping of the study and other practical
issues involved in getting the study underway and communicating the study’s results.
Chapters 5, 6, 7 and 8 provide detailed discussion of economic terms, the types of
benefits and costs, and methods for measuring them, and the process for conducting
BCAs. Chapter 5 provides a summary of the economic essentials relevant to valuation
studies and BCAs. It is aimed at providing the meteorological and hydrological serviceprovider community with the basic understanding of economic terms needed to guide
the commissioning, conduct and use of economic valuation studies. Chapter 6 defines
and characterizes the benefits achievable from the use of met/hydro services, describes
the various methodologies already used and potentially available for their valuation,
and provides case study examples to illustrate both the strengths and limitations of the
various approaches. Chapter 7 explains concepts and methodologies used to define
and measure costs incurred at different stages in the service production and delivery
chain and by users of these services. Chapter 8 provides a simple workbook approach
to the conduct of BCAs for met/hydro services.
Chapter 9 deals with the important issues involved in communicating the results of an
SEB study to governments and other service providers, funder and user institutions and
the general public. It is aimed at ensuring the effective use of the study analyses in
public policy formation for the funding and operation of NMHSs.
Chapter 10 provides the summary conclusions of the group of meteorologists,
hydrologists, economists and other social scientists who prepared this publication. The
conclusions focus on the current state of knowledge and suggested priorities for future
work on improved approaches for assessing the benefits and costs of meteorological,
hydrological and related services.
There are five appendices (including Appendices A, B and C already introduced), as
follows:
–
Appendix A – Glossary of technical terms;
–
Appendix B – Meteorological, hydrological and related services;
–
Appendix C – A short history of studies of socioeconomic benefits of
meteorological and hydrological services;
8
Note that the term SEB assessment/study is used throughout the publication to refer to economic
assessments, most of which involve estimation of benefits and costs, and range from quickturnaround assessments to extensive studies. The emphasis on benefits relates to the view that the
primary reason for undertaking economic assessments of met/hydro services is related to
demonstrating their benefits vis-à-vis other types of public investment.
12
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
–
Appendix D – Complementary roles for other 9 social science applications in
socioeconomic benefit studies;
–
Appendix E – Case studies (a summary of a representative set of economic
valuation case studies which are used to illustrate the various methodologies
outlined earlier in the publication).
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are covered extensively in Chapters 6, 7, and 8.
Chapter 1. Introduction
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National Meteorological and Hydrological Services. Directions in Development. Washington,
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52:360–365.
CHAPTER 2. THE PRODUCTION, DELIVERY AND
USE OF MET/HYDRO SERVICES
2.1
Chapter 1. Introduction
Chapter 2. Met/hydro services
Chapter 3. Purpose of SEB studies
Chapter 4. Designing SEB studies
Chapter 5. Economic essentials
Chapter 6. Benefits
Chapter 7. Costs
Chapter 8. BCA
Chapter 9. Communications
INTRODUCTION
The current organizational structure, functions
and services of NMHSs are related to a guiding
mandate, vision or mission and attendant goals
and objectives (see Box 2.1 for examples).
Apparent in the NMHS mission statements are
the following principal motivations: safety of
citizens and households, protection of property,
and support for economic growth and
efficiency. These objectives guide the
production and delivery components of NMHSs
and establish the priorities and broad
parameters of the communities they are
obliged and intend to serve.
Virtually all met/hydro services and the benefits
they provide depend on the existence of an
integrated system of observation, data processing and management, modelling,
forecasting, research and development, and service production and delivery for the
country or region concerned. An idealized and simplified version of this system is
present in Figure 2.1.
Chapter 10. Looking forward
This chapter provides a brief introduction to the production, delivery and use of met/
hydro services. The scope and nature of met/hydro services are described and service
delivery mechanisms are explained by elaborating upon elements of the diagram in
Figure 2.1. Additional context and detail are provided in Appendix B. The
conceptualization is then broadened into a general value chain to address the
connections between the production and delivery of met/hydro services and the various
user communities and to highlight important features of the value generation process.
Processing & data management
Weather
Climate
Water
Observations
Modelling
Forecasting
Service delivery
Research & development
Figure 2.1. Components of the service production and delivery system of NMHSs
16
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
Box 2.1: Illustrative NMHS mission and vision statements
United Kingdom Met Office (2013)
The Met Office endeavours to meet its aim through provision of weather and climate
services that help the United Kingdom Government, devolved administrations, other public
and international bodies, the public and a wide range of commercial customers achieve
goals. The Met Office’s “Top Level Objectives” underpin this:
– Enabling protection – Protecting lives, infrastructure and the natural world;
– Improving well-being − Improving quality of life and well-being, now and in the future;
– Increasing prosperity − Enabling United Kingdom economic growth and international
competitiveness.
Indian Meteorological Department (2013)
– To take meteorological observations and to provide current and forecast meteorological
information for optimum operation of weather-sensitive activities such as agriculture,
irrigation, shipping, aviation and oil explorations;
– To warn against severe weather phenomena such as tropical cyclones, nor’westers,
duststorms, heavy rains and snow, cold and heatwaves, and the like, which cause
destruction of life and property.
Kenya Meteorological Service (2013)
– Our vision: To become a leading, world-class operational forecasting centre and scientific
institution that provides optimum contribution to improved quality of life;
– Our mission: To facilitate accessible meteorological information and services and infusion
of scientific knowledge to spur socioeconomic growth and development.
MetService (Meteorological Service of New Zealand Ltd.) (2013)
MetService provides comprehensive weather information services, 24 hours per day,
365 days a year. Our national weather forecasts are vital to the public and we are constantly
enhancing and improving their delivery. We provide groundbreaking products and services
that give a competitive edge to local and international businesses in the energy, media,
transport, resources, industry, infrastructure and retail sectors.
2.2
NATURE AND SCOPE OF MET/HYDRO SERVICES
In the broadest sense, meteorological services consist of the provision of information
and advice on the past, present and future state of the atmosphere, including
information on temperature, rainfall, wind, cloudiness and other atmospheric variables
and their influence on weather- and climate-sensitive activities and communities. The
physical phenomena responsible for such conditions are manifest at particular spatial
and temporal scales, as depicted in Figure 2.2 and also earlier in Figure 1.1, and this has
important implications in terms of observability, predictability and service design. For
example, with respect to tornadoes or other phenomena that form and evolve at very
fine spatial (tens to hundreds of metres) and temporal (minutes) scales, it is only
possible with present knowledge to issue a location- and time-specific warning with
about 20 minutes of advanced notice. Contrast this with a large tropical cyclone with a
diameter of hundreds of kilometres that forms and matures over a period lasting from a
17
Chapter 2. The production, delivery and use of met/hydro services
few to several days prior to affecting land, thus permitting long lead times for warnings
and attendant preparations. Beyond a couple of weeks, even large tropical storms
cannot be confidently resolved with high temporal or spatial precision. However, as
the frequency of storms and other hazardous events often correlates with indicators of
larger scale atmospheric and oceanic circulation patterns or conditions, they can be
statistically linked to predictions at long-range weather, seasonal and climatic scales
(for example, annual basin forecasts of hurricane occurrence; large basin flood events;
increased frequency/severity of storms under climate-change scenarios). Predictions or
forecasts concerning tropical storms and tornadoes are representative of a particularly
important subset of the information on future conditions (“forecasts” or “predictions”)
that consists of “warnings” or “early warnings” of hazardous or dangerous
meteorological conditions and extreme weather and climate phenomena. This
category also includes flooding, droughts, high winds, extreme heat and cold that
pose an immediate or highly consequential threat to life, property or livelihoods
(Zillman, 2014).
Hydrological and meteorological services overlap significantly largely because the
atmospheric component is a critical part of the hydrological cycle – and thus both
services are concerned by any hazards associated with too much or too little water.
Flood warnings, therefore, are regarded as both meteorological and hydrological
services. Hydrological services involve the provision of information and advice on the
past, present and future state of rivers, lakes and other inland waters, including
streamflow; river, lake and reservoir levels; water quality and so on. As with
meteorological services, Figure 2.2 is also useful when considering the important
Local scale
Climate change crojection
Decadal climate prediction
10 km
Seasonal to interannual
climate prediction
Nowcasting
Current weather
Mesoscale
Recent weather
100 km
Synoptic
scale
Recent climate
1 000 km
Continental/
regional
scale
“Normal” climate
10 000 km
Long-range weather forecasting
Global Scale
FUTURE CLIMATE
Medium-range weather forecasting
WEATHER
Short-range weather forecasting
PAST CLIMATE
1 km
Last Last
decade year
Last Last
Yesterday
month week
Now
Tomorrow
Next
week
Next
month
Next
year
Next
Next
Next
decade century millennium
Figure 2.2. Characteristic spatial scales of weather phenomena
(left-hand scale) and the approximate temporal terminology for weather and
climate description and prediction (bottom scale)
18
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
time–space characteristics of hydrologic hazards and accompanying implications for
services (for example, the potential precision of a prediction). For example, the lead
time for a flood event warning at the outlet of a large (that is, 100 000 square
kilometres or more) river basin is much greater (days) than that for a comparatively
small watershed (that is, less than 100 square kilometres) – the latter are often referred
to as “flash flood” events, with only minutes to hours of advanced warning potential.
In all cases, the accuracy of the flood event is very much tied to the skill of those
responsible for the precipitation forecast and predictions of other important
antecedent factors (for example, saturation level of soils, snowpack, and the like).
Many national agencies also provide marine weather and climate services, covering
hazards such as high waves, currents, storm surge/coastal inundation, and sea ice.
While the accuracy of warnings for such hazards often depends on the skill of those
responsible for forecasting meteorological conditions, oceanic observations and
predictions (for example, temperature profiles and sea ice state) are fundamental
inputs to long-range weather, seasonal and climate-scale forecasts.
Almost every meteorological and hydrological variable is of importance to some
section of society, and hence part of a meteorological or hydrological service, whether
in the form of long-term statistics or analyses (for example, for dam, bridge or building
design), information on current conditions (for example, for air traffic management,
runway selection and ground crew stoppages) or forecast conditions on timescales
from minutes to months, years or decades (for example, for crop harvesting, electricity
load planning or drought preparedness).
Most countries place the highest priority on the provision of warning services enabling
communities to prepare for, and minimize the impacts of, extreme hydrometeorological
phenomena such as tornadoes, storms, hurricanes, heatwaves, wildfires, floods and
droughts. The warnings can take the form of general cautionary advice or detailed,
location-specific, model-based forecasts of hazard evolution, expected impacts or
consequences and precautions for particular vulnerable segments of society.
Virtually all weather and climate forecasts and warnings may be presented in words,
numbers or graphical form; may be expressed in categorical or probabilistic terms; and
are updated frequently – all according to the standard practices of the service agency,
which generally reflect the needs and preferences of user communities. In many cases
practices are coordinated and standardized through international organizations, for
example WMO and the International Civil Aviation Organization for aeronautical
needs and services (see http://www.wmo.int/pages/prog/amp/aemp/aeronauticallinks_en.html).
The information can be developed and delivered by national forecast centres or through
local meteorological and hydrological offices using guidance from the national centres.
Some products may be derived directly from the output of numerical weather prediction,
while many others go through post-processing and varying degrees of interpretation,
adjustment and synthesis by forecasters and other practitioners. Forecasts and warnings
can be examined and considered qualitatively by individual decisionmakers or they can
pass directly into automated decision algorithms of various kinds.
Chapter 2. The production, delivery and use of met/hydro services
19
Box 2.2: Example of the United Kingdom Met Office tailored services
The United Kingdom Met Office offers a range of special services tailored to specific road,
rail, aviation, and marine transportation interests. Their road service applications include
forecasts and training for route planning, optimization and maintenance (see http://www.
metoffice.gov.uk/roads).
Working with Devon City Council and transportation consultants, the Met Office was able
to streamline maintenance routes into groups with similar road weather hazards through an
analysis of climatology, thus reducing the number of routes from 48 to 38 and saving £ 20 000
per route in terms of reduced mileage, fuel, fleet and labour costs (Met Office, 2011).
Since the 1980s, Members of the WMO community have found it useful to distinguish
between two broad categories of services:
–
Basic services: Those services provided at public expense to discharge a
government’s sovereign responsibility for protection of life and property, for the
general safety and well-being of the national community and for provision for the
essential information needs of future generations;
–
Special services: Those services beyond the basic services aimed at meeting the
needs of specific users and user groups and that may include provision of
specialized data and publications, their interpretation, distribution and
dissemination.
Many services, particularly special services, often go well beyond the simple
dissemination of information to include consultative advice or scientific investigation
into particular meteorological and hydrological phenomena and events or their
impacts.
As apparent in Figure 2.2, information services extend across all timescales. While the
emphasis and examples referenced in this section have related primarily to short- to
medium-term forecasts and warnings, services also include retrospective products
based on recent or long-term historical observations as well as future long-term
predictions and projections.
2.3
SERVICE DELIVERY
The ultimate benefit from the use of met/hydro services depends at least as much on
the effectiveness of the service delivery process as it does on the inherent scientific
quality of the forecast or other information provided.
The 2011 World Meteorological Congress approved a detailed WMO Strategy for Service
Delivery aimed at guiding the various participants in both the national and international
meteorological and hydrological service provision system on ways of improving the
overall quality of their services and the benefits from their application (WMO, 2014). The
six “strategic elements” which provide the overall framework for the strategy are:
20
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
–
Evaluate user needs and decisions;
–
Link service development and delivery to user needs;
–
Evaluate and monitor service performance and outcomes;
–
Sustain improved service delivery;
–
Develop skills needed to sustain service delivery;
–
Share best practice and knowledge.
An implementation plan for the Strategy for Service Delivery was published in 2014
(WMO, 2014). The strategy represents an important initiative in support of the Madrid
Action Plan (WMO, 2009), the WMO Strategic Plan (WMO, 2011) and the GFCS
Implementation Plan (WMO, 2012) and can be expected to reinforce the focus on
service improvement in all countries.
2.4
USERS OF MET/HYDRO SERVICES
The users of met/hydro services (especially meteorological services) include virtually
every person on the planet (Zillman, 2014). The overall user community is often broken
down into the general public, consisting of individuals, households and a wide range
of government and non-government organizations, on the one hand, and specific user
sectors and user communities on the other (Table 2.1).
Each of these major user sectors has specific requirements for historical, current and
forecast meteorological and/or hydrological information and advice, and most of them
have well-established consultation and coordination mechanisms for formulating user
requirements and meeting user needs. That said, the individual actors, enterprises and
institutions within these broad user sectors, and most definitely the general public,
vary in terms of their desire and capacity to obtain, understand and utilize information
– typically it is the larger organizations, businesses and agencies that are best able to
leverage the value of information. Industry, professional, non-government associations
Table 2.1. Sector utilization of met/hydro services
Economic sectors
–Services
–Manufacturing
–Energy
– Insurance and finance
–Tourism
–Agriculture
–Transportation
–Construction
–Mining
Public safety
Natural resources
–Defence
–Emergency
management
–Health
–Transportation
safety
– Water supply
–Natural resources
management
(forests, coasts,
terrestrial and marine
ecosystems)
21
Chapter 2. The production, delivery and use of met/hydro services
and other advocates (such as WMO) often play the role of demonstrating the utility of
incorporating met/hydro information into decisions among the underserviced
communities.
While practice differs from country to country, the term “users” is usually taken to
embrace the entire user community, albeit often with emphasis on the general public
and other consumers of the “basic service”. The terms “client” and “customer” have
been mostly reserved for the users of specialized products and services, especially
those provided on a commercial basis (Zillman, 1999).
GENERATING VALUE FROM SERVICES
2.5
Many actors and interactions are involved in the process that ultimately leads to
generating value – those who conceive, create, develop, disseminate, translate,
exchange, promote, receive, interpret, utilize and benefit from one or more products
or services. The production and service-delivery elements described in Figure 2.1
capture important components of this process. However, it is also necessary to
appreciate the roles of communication, perception and interpretation, decisionmaking
behaviour, and actions taken by users – these, in turn, lead to outcomes and ultimately
value. Figure 2.3 extends the service production and delivery process by incorporating
these aspects into a comprehensive yet simple value chain that will be elaborated and
referred to throughout the remainder of the publication.
The met/hydro service production system, including the operation of capital-intensive
monitoring and modelling infrastructure and the production of information targeting
broad public audiences, is typically managed within the domain of governmentsupported NMHSs. Outputs from this system are distributed through two streams, one
delivering basic services through traditional or social mass media, emergency service
organizations and public sector agencies; the other providing specialized services
through private sector providers or commercial arms of NMHSs. Even when the focus
is strictly on assessing an aspect of a public service, it is important to include and
COMMUNICATION PROCESSES
Weather
Climate
Water
SERVICE
PRODUCTION
Processing & data management
Weather/
climate/
water
Observations
Modelling
Forecasting
Research & development
Service delivery
Basic & specialized
services
NMHS & commercial
providers
User decisions
&
actions
Outcomes
VALUE
Benefits & costs
VALUEADDING PROCESSES
Figure 2.3. Simplified schematic of the met/hydro services value chain
22
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
consider the role of private sector players in the production and delivery of knowledge,
as that may be an important vehicle for the creation of value.
Potential value is added at each link of the chain moving from left to right as services
are received by users and incorporated into or considered in decisions. Decisions
consist of three general types – strategic, operational and tactical (Davison et al., 2012)
– and conveniently align more or less onto the spatial–temporal scales and categories
of products and services (see Figure 2.2). Strategic decisions are typically infrequent
and long-term commitments are often related to large investments and major
infrastructure designs, which may be informed by interannual and climate-change
scale prediction or projection information as well as analyses of long historical records
(for example, streamflow statistics to justify the sizing and design of a hydroelectric
power installation). Operational decisions are those required for the routine,
continuous daily management of an organization or activity and are normally informed
with forecast information in the order of minutes to one day, such as that used to
allocate winter maintenance equipment, personnel and treatment technologies (for
example, road ploughing and/or applications of de- or anti-icing chemicals and
abrasives) to clear roadways during a particular winter storm. Tactical decisions lie
between those at operational and strategic levels, are often repetitive but less frequent
than operational decisions, and are usually informed with meteorological and
hydrological information at daily to seasonal scales. Crop plant selection and advanced
natural gas contract purchases are examples of tactical-level decisions. While the above
examples and classification of decisions stems from organization management, the
concept is portable to the general public where strategic decisions might relate to the
choice of a place to live or work; operational decisions could include selection of
appropriate clothing and accessories (for example, whether to be equipped with an
umbrella) on a given day; and tactical decisions might involve booking a vacation or
changing automobile tyres from summer to winter models.
Value-adding processes involve tailoring services to more specialized applications and
decisions (that is, making the information more relevant and trustworthy) or
expanding the reach of an information product to ever-greater audiences (more
people, decisionmakers, clients). The efficacy of the information is highly dependent
on communication processes that influence the ability of users to perceive, interpret
and apply knowledge as intended by the service or information provider(s). Such
processes operate throughout the production, delivery and use of met/hydro
information and are significantly affected by psychological, social, cultural, political,
economic, institutional and other non-weather factors. As a simple example, given
warning of a pending storm, one is far more likely to cancel or defer a non-essential
weekend trip rather than a commute to work, especially if the avoided work trip leads
to a lost day of wages. Such non-weather factors are essential to understanding
deviations from the behaviours expected (for example, staying off the roadways to
reduce risk) by those issuing warnings and providing services.
The results of decisions taken or not taken, with or without the benefit of met/hydro
services, are outcomes – the critical pieces that link met/hydro services to value.
Beneficial outcomes may include losses avoided (typically reported as injuries,
fatalities, displaced populations, property damage, environmental impact and various
Chapter 2. The production, delivery and use of met/hydro services
23
measures of costs, income and productivity) or additional profits realized due to
improved decisions for weather events. Outcomes less commonly acknowledged and
analysed, but no less important, include aspects of time (for example, delay),
inconvenience and feelings or emotions (pleasure, stress, dissatisfaction, sadness,
sense of place/community, and the like). When assessing the value of a service, one is
really attempting to qualify and quantify the aggregate effects of changes in outcomes
thought to result from the introduction, improvement or withdrawal of the service.
2.6
CONCLUSIONS
Demonstrating the value of met/hydro services can be an important factor in
supporting decisions to maintain or increase funding for these services. However, this
is not a simple task for economics or other social sciences. In part this is because the
relationships and actors within the value-creation process are dynamic and reflective
– the value-creation process is iterative and interactive, as important feedbacks
continuously connect outcomes back to the producers of information through formal
and informal systems of verification and valuation.
REFERENCES
Davison, M., A. Gurtuna, C. Masse and B. Mills, 2012: Factors affecting the value of
environmental predictions to the energy sector. Environmental Systems Research, 1:4.
Indian Meteorological Department, 2013: IMD’s mandate, http://www.imd.gov.in/doc/
mandate.htm.
Kenya Meteorological Service, 2013, http://www.meteo.go.ke/.
Met Office, 2011: Case study: Devon City Council. Exeter, Met Office, http://www.metoffice.gov.uk/
media/pdf/i/2/Route_Optimisation_case_study.pdf.
Met Office, 2013: Met Office framework document 2013. Exeter, Met Office, http://www.
metoffice.gov.uk/media/pdf/k/b/MO_framework_document.pdf.
MetService, 2013: Annual Report 2013: It’s a Small World. Wellington, Meteorological Service of
New Zealand Ltd.,http://about.metservice.com/assets/ar-2013-2/MetService-AR-2013.pdf.
World Meteorological Organization, 2009: Secure and Sustainable Living. The Findings of the
International Conference on Secure and Sustainable Living. Social and Economic Benefits of
Weather, Climate and Water Services (WMO-No. 1034). Geneva.
———, 2011: WMO Strategic Plan 2012-2015 (WMO-No. 1069). Geneva.
———, 2012: Draft Implementation Plan of the Global Framework for Climate Services (GFCS).
Report dated 18 September 2012, tabled at the Extraordinary Session of the World
Meteorological Organization Congress, 29–31 October. Geneva.
———, 2014: The WMO Strategy for Service Delivery and Its Implementation Plan (WMO-No. 1129).
Geneva.
Zillman, J.W., 1999: The National Meteorological Service. WMO Bulletin, 48:129–159.
———, J.W., 2014: Weather and climate information delivery within national and international
frameworks. In: Weather Matters for Energy (A. Troccoli, L. Dubus and S.E. Haupt, eds.). New
York, Springer.
CHAPTER 3. THE PURPOSES OF SOCIOECONOMIC BENEFIT
ASSESSMENTS OF MET/HYDRO SERVICES
Chapter 1. Introduction
Chapter 2. Met/hydro services
Chapter 3. Purpose of SEB studies
Chapter 4. Designing SEB studies
Chapter 5. Economic essentials
Chapter 6. Benefits
Chapter 7. Costs
Chapter 8. BCA
Chapter 9. Communications
Chapter 10. Looking forward
3.2
3.1
INTRODUCTION
Many NMHSs are seeking to improve and
expand their services to meet new and increasing
national needs. Others facing level or shrinking
budgets need to ensure the best possible use of
available funds to maintain their basic
infrastructure and essential services to the
highest possible standard. In all of these cases,
NMHSs will be increasingly expected to
document the quality of met/hydro services, the
level of uptake by users, and the value of these
services. This chapter provides an overview of the
types of analysis that NMHSs might commission10
to make the funding case, and describes several
ways that SEB studies can be used to support
arguments for sustained or increased funding.
EVALUATING MET/HYDRO SERVICES
A comprehensive evaluation of met/hydro services would cover verification of service
quality, characteristics of service uptake by user communities and the economic value
of services to user communities. Most NMHSs are continually evaluating the quality of
their forecasts and other services (Mason, 2013). These evaluations might involve
ex-ante or ex-post analysis (see section 6.2) of forecasts with actual weather data to
generate routine verification scores and/or customer satisfaction surveys to assess
perceptions of service reliability and access. Together, these analyses can be used to
support service improvements and demonstrate reliability to funding authorities and
user communities.
In addition to their utility in assessing service quality, customer satisfaction surveys are
a tool used by NMHSs to understand who is accessing information, how that
information is being used, and the experience of users in matching that information to
their specific needs. In addition to their use for evaluating current products and
services, surveys and focus group interviews can also be used to explore potential
demand for new services.
There are numerous non-economic social science methods that can be employed to
understand the uptake of met/hydro services. Non-economic methods can be used to
reveal diverse information on the value of the service, including, for instance, the
ability of users to access, understand and apply particular met/hydro services to their
10
At the time of writing, most NMHSs do not have an on-staff economist. Even as met/hydro staff
review this guide to SEB studies, the authors do not expect that NMHSs will be able to produce
such studies without external support.
CHAPTER 3. THE PURPOSES OF SOCIOECONOMIC BENEFIT ASSESSMENTS OF
MET/HYDRO SERVICES
25
particular needs. Non-economic social science evaluation studies can also describe the
capacity of users to incorporate met/hydro information into particular decision
contexts, which are not quantifiable in strictly monetary terms. This will also help
characterize the ease with which met/hydro information flows from an NMHS to
intermediaries and on to the end users in question. Appendix D provides a more
detailed description of the many applicable non-economic social science methods that
can contribute to the evaluation of met/hydro services.
These assessments can be very useful as NMHSs work to understand their customers’
needs, improve individual products and/or better tailor services to specific user groups.
Non-economic methods also serve as important complements to economic methods,
providing the context and background to help understand how economic studies
should be designed in order to best reflect the value of a service and better understand
the determinants of the pace and extent of uptake for current and future services.
While non-economic methods are very useful in illuminating the context in which
services are provided and used, in many cases NMHSs will also need to determine and
communicate the value of their met/hydro services in economic terms. Economic
valuations can be very helpful as NMHSs make decisions about how to allocate
resources – for example, allowing limited resources to be directed at specific needs to
enable the organization to fulfil its central mission or role. It can be challenging for
NMHS management to decide where best to invest their (usually scarce) financial and
personnel resources (Rajasekaram et al., 2010). Too often, previous patterns of
investment are maintained without their effectiveness being explored in any rigorous
manner.
An SEB study can point the way to a more informed and evidence-based
decisionmaking process in that it can identify elements of the organization that will
produce the best return on resource investment. This can be a difficult process; any
change in budget allocation that differs significantly from historical patterns will
almost certainly present challenges within an organization. Nonetheless, decisions
based on the outcomes of SEB studies are more likely to be beneficial for the
organization in helping it to retain relevance than decisions made without reference to
such studies; such decisions are also more defensible than those made without a similar
level of analysis.
Economic studies are powerful tools in communicating with funders to help them
understand the likely return on current and/or future investments in met/hydro
services. In all cases, an NMHS that can plausibly demonstrate that it provides good
“value for money” (whether societal or economic in character) is in a better position to
argue for the retention of, or an increase in, its existing resources (see Box 3.1). The
studies listed in Table 1.1 in Chapter 1 provide a range of examples for which benefits
exceed costs by a substantial margin, whether the study focuses on the analysis of
whole of services or individual services for all or selected user communities.
It should be considered that many other government agencies will be engaged in
similar exercises to demonstrate the value of the services that they provide; an NMHS
that cannot point to an SEB study to support its case for funding may find itself at a
26
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
Box 3.1: Target audiences for socioeconomic benefit studies
When considering why an SEB study should be commissioned, careful thought needs to be
given to the audience to which the finalized assessment report will be targeted, and how
that report will be communicated to that audience. While this topic is covered in depth in
Chapter 9, those developing the study should, early on in the process, develop a clear idea
as to the formats in which the results will be presented to the audience, for example, text
narratives, tables, graphics, and the like. Different presentation formats will work best with
different audiences. It would be unwise, for example, to present tables of detailed results to
meetings of key users, whereas those in funding agencies or finance ministries may
specifically require such details to aid them in their decisionmaking. The form of
presentation should always be tailored to the specific audience if the message is to be
communicated to maximum effect, and this has implications that reach right back into the
specification and design of an SEB study.
serious disadvantage when the finance ministry and/or relevant donor comes to make
its key decisions. It will not normally be sufficient to demonstrate that a positive
economic benefit will derive from resource investment in an NMHS, as other agencies
will have similar support to their applications; it is important to document the
economic benefit in a way that can be supported by the study outcomes.
While these and other goals for SEB studies are dealt with in more detail in the
following section, it is important that NMHSs come to view the valuation of met/hydro
services not as a one-off project, but as a part of ongoing service development and
delivery. Regardless of whether economic or non-economic methods are used, it is
clearly beneficial for NMHSs to perform assessments on a routine basis to help them
characterize the value of their service developments over time, similarly to the way that
regular forecast verification helps to illuminate the extent to which forecast skills have
evolved. A schedule of periodic assessment procedures, which could include economic
studies, non-economic social science assessments, or a mixture of both, should be
developed by each NMHS.
3.3
TARGET AUDIENCES FOR SOCIOECONOMIC BENEFIT STUDIES
As those working in NMHSs will know, when a forecast is issued to a specific user, it is
usually tailored to the needs of that user. The more closely the forecast is tailored to
user needs, the more likely it is to assist users in their decisions and generate value as
users benefit from the decision. In an analogous manner, an SEB study should be
conceived and carried out with careful consideration given to the needs it will fulfil.
Every SEB study should start with a question to be answered or a purpose to be met.
The nature of that purpose will inform the type of study to be undertaken, its scale and
scope, and the communication strategy that will be employed to ensure maximum
exploitation of the study results. The purpose, of course, will be informed by relevant
stakeholders and the target audience for the study, which may include government
decisionmakers, public and sectoral users and staff, as detailed below. Figure 3.1 lists
and characterizes the main types of NMHS operating models and describes the
CHAPTER 3. THE PURPOSES OF SOCIOECONOMIC BENEFIT ASSESSMENTS OF
MET/HYDRO SERVICES
27
institutional context defining how they are financed and managed. This can help
NMHSs that employ varying operating models understand relationships between the
met/hydro service and an audience, funding agency, user, and the like.
3.3.1
Governing decisionmakers
Every NMHS exists within an institutional framework or structure, the details of which
fundamentally inform the identification of an SEB study’s target audience and
communication strategy. Rogers and Tsirkunov (2013) reviewed the global landscape
of NMHSs and concluded that five broad operating models are currently employed,
summarized in Figure 3.1.
In practice, the majority of NMHSs are structured following one of the three least
autonomous models, that is, departmental units, contract agencies and public bodies.
Directly
controlled
Indirectly controlled
Departmental
unit
Contract
agency
Public body
State-owned
enterprise
Provatized
company
Type of
task
Public service
provision
Public service
provision
Public service
provision
Public service
provision
Public service
provision
Own legal
personality
No
No
Partially or
fully separate
Legal basis
Public
law
Public
law
Finances
State
budget
Control
mechanism
Direct
political
Ministerial
responsibility
Yes
Yes
Public
law
Private
law
Private
law
State budget;
own revenues
possible
State budget
and own
revenues
Own
revenues
Own
revenues
Framework
document
Statutes,
law
Market
Intervention
Regulation
Yes
Partial
Type of
task
No
Yes
Greater autonomy
Figure 3.1. Five NMHS operating models in current use
Source: Rogers and Tsirkunov (2013)
28
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
For NMHSs that are fully part of the civil service of the country in question (as a part of
the government department or as an agency reporting directly to a department or
minister) the key decisionmakers may be in the parent department and/or in the
finance or treasury ministry. Decisions may be at the administrative level or at the
political level or, as is most usual, some mixture of the two. If, on the other hand, an
NMHS is constituted as an agency with its own board of directors (for example, a
state-owned enterprise or privatized company), then this board represents a key
decisionmaking layer to which the SEB study must be communicated.
If an NMHS has some commercial freedom and can raise money for investment from
private sources (for example, banks), the effective communication of the study
outcomes will be essential in assembling the business case and preparing proposals for
potential investors/lenders. Even within government, many investment funding
decisions are now taken on the basis of competitive business cases. Frequently, it will
not be sufficient to demonstrate a positive return on investment in an NMHS; the
return may need to be demonstrably higher than other potential investments seeking
funding from the same source of public funds.
3.3.2
Public and sectoral users
Almost all NMHSs will have, as a basic public task, the provision of forecast and
warning services to the general public. These may be communicated directly to the
public by an NMHS through its own staff or through partner organizations such as
emergency management agencies and the media. In virtually all cases, there will also
be online channels of communication, ranging from the traditional websites to social
media. There may be differences in the relative importance of each of these media
channels as well as in the transmission of weather information, but in general the
weather message is tailored to each specific means of dissemination. In an analogous
manner, it will be important to carefully tailor the communication of SEB study data for
each of these specific media, exploiting their individual strengths and avoiding their
individual weaknesses. Additional strategies to reach the media and external audiences
will be examined in more detail in Chapter 9.
Sectoral users, including agencies, organizations and private companies, can be both
contributors to and consumers of SEB studies. Government agencies reliant on met/
hydro services may contribute data and information and even help advocate on behalf
of NMHSs by promoting their SEBs, while they and other agencies may also be
competing for the same public funding. In both cases, the agencies form a key
audience for SEB studies. Agencies and companies that pay for met/hydro services will
most likely be interested in SEB analysis to inform their relationship with NMHSs, for
example to gauge the fairness of the fees they are paying. International donors and
financiers will of course be interested in understanding and determining the expected
socioeconomic returns of their investments, and may require an SEB analysis as a
condition of funding.
CHAPTER 3. THE PURPOSES OF SOCIOECONOMIC BENEFIT ASSESSMENTS OF
MET/HYDRO SERVICES
3.3.3
29
National Meteorological and Hydrological Service staff
It will be highly desirable that all members of an NMHS staff are engaged in the SEB
study, understand the process of analyses and play a role in implementing the resulting
decisions to ensure that these analyses are fully and effectively utilized. Depending on
the scope of the study, some staff will most likely be highly engaged in the process, or
will at least contribute key information. All relevant staff should be aware from the
beginning of the reasons that management has for pursuing such analysis, and be
informed of the process and results at regular intervals. Studies should not only be
communicated to staff as a static audience; opportunities must be provided for
questioning, feedback and deeper engagement if so desired.
A compelling reason why the staff of an NMHS will have a deep interest in the results of
an SEB study is that the results should help to confirm to them a sense of the
significance of the work that they perform, and thus support and promote morale in
the organization. Everyone wants to feel that they do useful work and tangible
evidence of the value of an NMHS and its products will, in most cases, raise the
confidence levels of the individuals working within the organization and contribute
positively to both individual and corporate self-esteem.
3.4
REASONS TO CARRY OUT A SOCIOECONOMIC BENEFIT STUDY
There are many possible purposes or needs that may inform the decision to conduct an
SEB study with a focus on met/hydro services. The impetus may come from outside the
NMHS – perhaps from the parent government ministry or the treasury. It may come
from a board of directors or a council of users if such formal structures exist.
Alternatively, the initiative may come from the management of the NMHS, either to
provide them with quality evidence on which to base management decisions or
evidence to assist them in advocating for improved resources from the public purse.
While each NMHS will have its own unique circumstances and challenges, this section
attempts to describe and summarize some of the more common needs that underlie
the requirement to conduct an SEB study and suggest some of the characteristics of
studies that might address those diverse needs, together with appropriate examples.
These needs include, but are not limited to, validating the provision of existing or
proposed new services, determining the contribution of met/hydro services to user
goals in strategic sectors or among members of the general public, and assessing the
allocation of NMHS resources to specific services.11
11
The final purpose – assessing the allocation of NMHS resources – only entails analysis of costs. As
SEB studies are designed to evaluate benefits, it would not provide a motivation for such SEB
studies. However, SEB studies often focus on both benefits and costs. By determining how to use
resources more cost-effectively, which will reduce total costs, this can increase net benefits (the
difference between benefits and costs). Furthermore, the determination of lower-cost strategies to
provide services can complement SEB analysis results and make a more compelling case to provide
financial support for NMHSs.
30
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
The specific purpose or need will inform the type of valuation that should take place, in
that it should deliver the precise metrics that support the particular need. The manner
in which SEB study results are to be employed and communicated will also need to be
considered at this early stage; the study results will not exist in isolation but will
typically feed into a wider process of decisionmaking. In addressing this point, the
concept of framing the study will need to be taken into account. In the
communications literature, “framing” (see, for example, Scheufele, 1999; Entman,
2004) refers to the creation of a common understanding of the purposes of the
intended study plus the mode of presentation.
3.4.1
Validating the provision of basic met/hydro services
While politicians and other opinion formers sometimes argue against public sector
spending on the grounds that a well-resourced government is a contradiction to a
healthy economy, it is government spending that creates the conditions for businesses
and communities to prosper. Governments fund transportation and energy
infrastructure, ensure fair business practices, educate and train a large fraction of the
workforce and contribute significantly to keeping it healthy. They also provide the
resources to cope with crises created by natural and man-made hazards. National
Meteorological and Hydrological Services contribute significantly to the latter and
provide routine services that facilitate efficiencies in for-profit weather-sensitive
industries and for the economy as a whole.
In the latter context, NMHSs are viewed by some governments as entities that can
provide a return on capital or can support some fraction of their own infrastructure
costs, thereby subsidizing any public sector investment. While this approach may be
politically attractive, it undermines the essentially public-good role of NMHSs and, if
accompanied by inadequate financing, contributes to a decrease in a country’s ability
to cope with climate- and weather-related fluctuations. Documenting the value of
basic met/hydro services helps to justify basic investment in NMHSs.
The primary audience for those SEB studies that aim to validate the existence of the
publicly funded NMHS is normally the owner of the NMHS, usually the responsible
Box 3.2: Validating whole-of-service investments
The Finnish Meteorological Institute was one of the first NMHSs in Europe to conduct an
economic valuation of its met/hydro services. The study was designed to demonstrate the
value of all services, but focused only on major sectors and user groups: transportation,
construction and facilities management, logistics, energy, and agricultural production. The
authors used existing data, impact models, and interviews to determine the current level of
use of met/hydro services, how individuals and organizations change their decisions in
response to this information, and how decisionmakers and other users benefit from it.
Estimated annual benefits for the sectors studied were US$ 359 million–US$ 390 million,
about five times the annual costs of providing all FMI met/hydro services (US$ 68 million–
US$ 82 million). Case study 7 in Appendix E provides additional detail on the FMI study.
Source: Leviäkangas and Hautala (2009)
CHAPTER 3. THE PURPOSES OF SOCIOECONOMIC BENEFIT ASSESSMENTS OF
MET/HYDRO SERVICES
31
Box 3.3: Validating current investments in specialized met/hydro services
In 2014, MeteoSwiss analysed the benefits of the terminal aerodrome forecasts (TAFs) it
provides to Switzerland’s domestic airlines. Specifically, interviews were conducted with
airline representatives and a normative, economic decision model was applied to quantify
the economic value of TAFs in terms of avoided fuel and flight-deviation costs. Results of the
study indicate that the annual economic benefits of TAFs are between US$ 14 million and
US$ 22 million at Switzerland’s two main airports. The study helped to validate past
investments in TAFs, and also allowed MeteoSwiss to assess options for improving TAFs to
increase economic benefits. Case study 6 in Appendix E provides additional detail on the
MeteoSwiss TAF benefit study.
Source: Frei et al. (2014)
ministry or the treasury. However, it should be stressed that these whole-of-service
studies can be difficult to scope out, can be very time-consuming and typically require
considerable resources to conduct (a more in-depth discussion of such studies can be
found in Chapter 6). More limited studies, focusing on a particular sector, geographical
region or major client, are recommended as a starting point for organizations
developing an SEB study for the first time.
3.4.2
Validating past and current investments in specialized
met/hydro services
Many NMHSs are called on, from time to time, to justify their continuing operation and
especially the substantial investment of public funds to support their basic infrastructure
and their entire suite of services. And most NMHSs frequently find themselves needing
to validate investments in specific programmes and/or services provided to a particular
sector. The NMHS may be interested in determining if a particular service that has been
provided in the past should be maintained or discontinued. There may be interest in
understanding which sectors benefit from specific types of services. In comparison to
the whole-of-service study described in the section above, this type of SEB study
typically will have a more narrowly focused scope of work and may be more
manageable in scale and less costly and time-consuming to conduct.
For instance, SEB studies that focus on specific user sectors (for example, agriculture or
transport) can illustrate the value of met/hydro services to specific actors (Frei et al.,
2014). The valuation of the benefits associated with early warning systems also fall into
this category. In Hong Kong, China, for instance, it has been shown that early storm
warnings ensure that people have the time to return safely to their homes using an
adaptive public transport system that is responsive to the warnings. Timely warnings,
effective communication and response ensure the safety of Hong Kong citizens and
permit the economy to rebound quickly from such natural hazards (Rogers and
Tsirkunov, 2011).
While these studies focus on the economic benefits associated with specific activities,
they can also be a means to explain the value of NMHSs to their respective governments
and to improve the availability of financial resources to invest in this sector.
32
3.4.3
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
Justifying new investments in met/hydro services
In general, a well-established NMHS can reasonably expect that its annual budget
allocation will bear some close relationship to the allocation levels in recent years,
being adjusted up or down in line with the prevailing economic health of the country
(amongst other considerations). Seeking an additional allocation of funds for new
activities or investments is, however, a more challenging scenario and will typically
require a robust illustration of the benefits to be realized by the new allocations
sought.
The economic assessments employed in this case are necessarily pragmatic, with the
aim of determining the likely SEBs of enhanced services provided through the new
activities or new facilities of the NMHS. One of the difficulties in this case is that
potential users of these new services are likely to be unaware of the new opportunities
and benefits that might ensue. Therefore, there is a risk that the beneficiaries will
undervalue the potential benefits of modernization or improvement, or require
significant time to adjust their decisions to the new or improved information.
To mitigate this, economic assessments aim to estimate the potential aggregate
benefits that would accrue to national business activities from an improved quality
(accuracy, timeliness and reliability) of met/hydro information and services. The
approach used in these studies focuses on estimating potential countrywide losses
from high-impact met/hydro hazards, while assuming that the potential benefits of
modernization will be realized over several years. There are a number of complex
aspects to this approach, notably the absence of systematic recordings of damage/
losses (both in physical and value terms) incurred by the economy, sectors of society
and the population as a whole as a result of met/hydro hazards. As a result, it is also
necessary to apply additional approaches (World Bank, 2008).
Box 3.4: Justifying new investments in met/hydro services
The World Bank, working with a number of NMHSs in Europe and Central Asia, has
conducted 11 studies to evaluate the benefits associated with existing weather and met/
hydro services, as well as the benefits that large-scale NMHS modernization might achieve.
The studies employed two assessment methods:
– A sector-specific method to estimate the economic benefits of met/hydro services in
weather-dependent sectors using available in-country data and expert surveys;
– A benchmarking method to assess the losses caused by prior weather events involving
the estimation of reduction in losses from weather events that could be achieved with
improved services.
Results of the World Bank studies indicate that improving met/hydro services and
information would result in significant economic benefits. For example, results for
Kyrgyzstan indicate that the benefits (avoided damages) of investments to improve met/
hydro services are 2.4 to 3.2 times the costs of these investments. Case study 1 in Appendix E
provides additional detail on the sector-specific and benchmarking studies that the World
Bank has conducted in countries in Europe and Central Asia.
Source: World Bank (2008)
CHAPTER 3. THE PURPOSES OF SOCIOECONOMIC BENEFIT ASSESSMENTS OF
MET/HYDRO SERVICES
33
Box 3.5: Informing strategic policy decisions
User-tailored climate services can generate significant SEBs in the agricultural sector; for
example, by early warning systems which trigger preventive measures to avoid or reduce
crop losses. This potential was explored by the Peruvian National Service for Meteorology
and Hydrology (SENAMHI) and MeteoSwiss in a pilot case study estimating WTP for specific
early warning systems in the Peruvian region Cusco. The study applied the statedpreference method (see sections 6.5.1, 6.5.3, 6.5.4 and 7.6), an econometric approach
based on face-to-face interviews with more than 60 individual farmers. The results indicate
SEBs for coffee and maize cultivation over a period of 10 years of about of US$ 10 million for
the Cusco region and well over US$ 100 million for Peru as a whole. Considering only coffee
farmers, the estimated WTP corresponds to up to 1% of Peru’s coffee export value. The study
shows clear evidence for the need and utility of tailor-made climate services for the
agricultural sector, hence underscoring the essential role NMHSs can play, for instance in
ensuring food security or improving farmers’ incomes. It thus demonstrates the importance
of climate services as a basic element for national climate change adaptation strategies in
climate-sensitive sectors.
Source: MeteoSwiss and SENAMHI (2014)
This approach also draws attention to the fact that, in many cases, measurable social
and economic benefits will accrue only after substantial investment to transform
ill-equipped and nearly obsolete NMHSs. Over 100 NMHSs in developing countries are
considered to be in need of substantial investment to bring their services to a level at
which they can provide timely, reliable and accurate forecasts of high-impact weather
to the public and to national economic sectors (Rogers and Tsirkunov, 2013).
3.4.4
Determining the value of NMHSs to user goals
While an NMHS will normally be focused primarily on its routine forecast and warning
operations, it has the capacity to inform and contribute to larger strategic goals that
may be national or even international in scale. Examples of national goals might be
those linked to the safety and security of citizens (civil protection), to food and
nutrition (agricultural development and food security), to public health (air quality) or
to climate adaptation. International goals might include those policies that are aimed
at opening up public data sets for use by third parties, for example, the European
Union’s Directive on Infrastructure for Spatial Information in the European Community
(INSPIRE) relating to the reuse of public sector information in the European Union (de
Vries et al., 2011), and similar initiatives in Australia (Office of the Australian
Information Commissioner, 2011). This special category of SEB studies can help to
determine how an NMHS, operating at the national level, can contribute to the
realization of these larger strategic sectoral goals.
3.4.5
Prioritization or reallocation of resources
Decisions regarding how to allocate resources are normally internal to an NMHS. A
decision may be required as to where investment should be focused to improve the
34
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
overall quality and range of services provided to the public and specialized users. For
example, choices may need to be made between investments in ground-based or
space-based observation systems, or perhaps between investments in observation
systems or forecast systems. Choices may need to be made between allocating monies
to tangible assets (equipment, computers), or to capacity-building activities, including
training and other activities.
A particular example of this type of choice faced by many NMHSs includes whether
resources devoted to weather modification (for example, hail suppression) might not
be better allocated to improved forecast and warning services. An analysis of costeffectiveness can be useful in determining whether the current or improved quality
and level of met/hydro services is achieved at lowest cost.12
The context of this category of need or purpose is usually a national one, whereby a
public audit office or similar institution carries out a study of a publicly-funded
institution to ascertain whether or not public monies have been used in an optimal
manner. However, an NMHS could, on its own initiative, embark on a study of this type
to illustrate to the public that it is using tax revenues prudently. This type of study may
also be required to support cost estimates provided to a regulator, for example in the
aviation industry, where the costs of support services are determined by regulation
and passed on to the users – in this case the airlines and, ultimately, the travelling
passengers.
3.5
CONCLUSIONS
The articulation of the purposes of SEB studies provides the impetus for developing
studies to answer one or more questions about the value of met/hydro services and
renewing or expanding political, financial and public support for NMHSs. This initial
realization of the importance of the benefits of met/hydro services represents the
beginning of a process of SEB study approval, resource mobilization, study design and
implementation and communication of results that is the focus of the next six chapters.
REFERENCES
de Vries, M., L. Kapff, M. Negreiro Achiaga, P. Wauters, D. Osimo, P. Foley, K. Szkuta, J. O’Connor
and D. Whitehouse, 2011: Pricing of Public Sector Information Study (POPSIS) – Models of Supply
and Charging for Public Sector Information (ABC) – Final Report. Commissioned by the European
Commission Information Society and Media Directorate-General, http://ec.europa.eu/
digital-agenda/en/news/pricing-public-sector-information-study-popsis-modelssupplyand-charging-public-sector.
12
Cost-effectiveness analysis considers alternative ways of achieving the same level of service – the
option that can provide the desired level of services at lowest cost is considered to be
cost-effective.
CHAPTER 3. THE PURPOSES OF SOCIOECONOMIC BENEFIT ASSESSMENTS OF
MET/HYDRO SERVICES
35
Entman, R.M., 2004: Projections of Power: Framing News, Public Opinion, and U.S. Foreign Policy.
Chicago, University of Chicago Press.
Frei, T., S. von Grünigen and S. Willemse, 2014: Economic benefit of meteorology in the Swiss
road transportation sector. Meteorological Applications, 21:294–300.
Leviäkangas, P. and R. Hautala, 2009: Benefits and value of meteorological information services
– The case of the Finnish Meteorological Institute. Meteorological Applications, 16:369–379.
Mason, S.J., 2013: Guidance on verification of operational seasonal climate forecasts. Report
prepared under the auspices of WMO, Commission for Climatology XIV, Expert Team on
CLIPS Operations, Verification, and Application Service, http://www.seevccc.rs/SEECOF/
SEECOF-10/SEECOF-LRF-TRAINING/November%2013th%202013/CCl%20verification%20
recommendations.pdf.
MeteoSwiss and SENAMHI, 2014: Socio-economic benefits of enhanced climate services: A pilot
case study for the coffee and maize cultivation in Peru. Office of the Australian Information
Commissioner, 2011: Issues paper 2 – Understanding the value of public sector information
in Australia, http://www.oaic.gov.au/information-policy/information-policy-engagingwith-you/previous-information-policy-consultations/information-policy-issues-paper-2november-2011/issues-paper-2.
Rajasekaram, V., G.A. McBean and S.P. Simonovic, 2010: A systems dynamic modelling
approach to assessing elements of a weather forecasting system. Atmosphere–Ocean,
48(1):1–9.
Rogers, D. and V. Tsirkunov, 2011: Costs and benefits of early warning systems. Global
assessment report on disaster risk reduction. United Nations Office for Disaster Risk
Reduction and World Bank, http://www.preventionweb.net/english/hyogo/gar/2011/en/
bgdocs/Rogers_&_Tsirkunov_2011.pdf.
Rogers, D. and V. Tsirkunov, 2013: Weather and Climate Resilience: Effective Preparedness through
National Meteorological and Hydrological Services. Directions in Development. Washington,
D.C., World Bank, http://dx.doi.org/10.1596/978-1-4648-0026-9.
Scheufele, D., 1999: Framing as a theory of media effects. Journal of Communication,
49(2):103–122.
World Bank, 2008: Weather and Climate Services in Europe and Central Asia: A Regional Review.
World Bank working paper No. 151. Washington, D.C.
CHAPTER 4. DESIGNING AND COMMISSIONING
SOCIOECONOMIC BENEFIT STUDIES
4.1
Chapter 1. Introduction
Chapter 2. Met/hydro services
Chapter 3. Purpose of SEB studies
Chapter 4. Designing SEB studies
Chapter 5. Economic essentials
Chapter 6. Benefits
Chapter 7. Costs
Chapter 8. BCA
INTRODUCTION
As noted in Chapter 3, there are several
motivations for studying the costs and benefits
of NMHSs. Studies might be designed to
support one or more of these motivations. The
purpose of this chapter is to help met/hydro
service providers undertake the groundwork
necessary to conduct and commission an SEB
study covering the analysis of benefits, costs
(cost-effectiveness analysis), or BCA, and
communicate study results to decisionmakers
and stakeholders.
Chapter 9. Communications
While NMHSs may have the capability to
conduct non-economic studies on the
importance of their services (for example, user
Chapter 10. Looking forward
surveys to assess quality and uptake) or apply
simplified methods such as the benchmarking approach developed by the World Bank
(see section 6.5.3 for a detailed description) to provide order-of-magnitude benefit
estimates, it is assumed that few NMHSs will prepare in-house SEB studies. Thus, this
chapter is organized according to a five-stage process to help NMHSs design and
commission SEB studies. The stages and main outputs for SEB studies are described in
Figure 4.1.
OUTPUTS
STAGES
Develop concept note
Prepare scope of work
• Implementation plan
• Consultant TOR
•Communication
strategy
• Concept note
• Decision on
socio­economic
benefit study
Commission the study
• Tender documents
• Selection memo
• Contract documents
STAGES
OUTPUTS
Conduct
the study
• Review draft(s)
• Final report
Communicate study
results
•Communication
products
Figure 4.1. Process of designing and commissioning socioeconomic benefit studies
Chapter 4. Designing and commissioning socioeconomic benefit studies
4.2
37
STAGE ONE – DEVELOP THE CONCEPT NOTE
The first stage concerns the preparation of a concept note that will enable high-level
government or NMHS management to take a decision to provide financial support for
the SEB study, agree to consider the results of the study in terms of resource allocation
and understand other potential uses of study results. The concept note should also
anticipate the types of questions that decisionmakers will ask related to the study’s
purpose(s), intended audiences, content, financial and staff resource requirements,
and management of the preparation, review and communication of the results of the
SEB study.
The purposes of SEB studies were enumerated and discussed in Chapter 3. In most
cases, their primary purpose is related to financial and staff support for NMHSs, the
operation of their infrastructure or the specific met/hydro services they provide. For
decisions related to budgets, the study will help
decisionmakers determine if public expenditure on
Box 4.1: Contents of
NMHSs is highly valued vis-à-vis other investments
the concept note
that government can make by applying BCA. Less
Description of the study
frequently, studies may focus only on an
– Purpose of the study
assessment of the costs of alternatives for
– Met/hydro services to be
producing and delivering a specific type or level of
assessed
met/hydro services using cost-effectiveness
– Sectors to be assessed
analysis. In addition to funding and allocation
– Benefit–cost methods
decisions, SEB study results can be used to educate
Budget and financing
the public about the value of services or increase
– Costs of the study
awareness and uptake of services by user
– (Potential) sources of
communities.
financing
The concept note should include a description of
the study, provide information on budget and
financing, the timeframe to design, commission
and conduct the study, and describe roles and
responsibilities that will be likely divided between
Roles and responsibilities for:
the NMHS, consultants, and other stakeholders. In
– Management oversight
Box 4.1, an illustrative description of the contents
– Procurement (if necessary)
of the concept note is provided. Even if a concept
– Preparation of the study
note is not required to make a decision on whether
– Dissemination of results
to conduct an SEB study, the contents described in
the box will be useful in preparing a briefing for
decisionmakers, external funding agencies, or NMHS senior management, and will
provide the framework and a summary of the content to be included in the study’s
scope of work in stage two.
Timeframe
– Design and procurement
– Study preparation and
dissemination of results
In most cases, an NMHS will provide management oversight for the study, but if the
study is required to be viewed as truly independent, oversight might be provided by a
steering committee comprised of multiple agencies and representatives from user
communities. Audiences for SEB studies depend in part on the purpose of the study
and the desire of an NMHS to exploit results with the public and user communities.
38
VALUING WEATHER AND CLIMATE:
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Table 4.1 provides a list of primary audiences for SEB studies undertaken for each of the
purposes described in Chapter 3. The concept note should also provide an outline of
the review process and plans for sharing results with the various audiences described
in Table 4.1. This element of the concept note should describe how and at what stages
in the process stakeholders are to be engaged.
The study may be conducted by a single individual, single organization or a
consortium. Potential organizations involved in conducting the study might include
the NMHS, other agencies, non-governmental organizations or universities, or a
private firm. If, for example, the prime purpose is understood by the key stakeholders
as providing evidence for the urgency of a supplementary investment programme
aimed at reinstating and refurbishing observation and localized weather service
capacity (where these have been allowed to deteriorate), a report from a widely
respected – possibly international (and hence more neutral) – expert organization is a
good option (see, for example, World Bank, 2008). Alternatively, if the NMHS aims to
provide input for a well-founded state or ministerial budget allocation, the
recommended course would be to engage national independent experts with
background guidance from a broadly based advisory group and have them deliver a
report (for example, Met Office, 2007). For the purpose of prioritization of public
spending, the coordination of SEB studies across comparable actors from other sectors
can often be useful, especially in case of joint benefits, such as those related to traffic
safety or to public health.
The concept note should also provide an outline of the review process and plans for
sharing results with the various audiences described in Table 4.1. This element of the
concept note should describe how and at what stages in the process stakeholders are
to be engaged (Box 4.2).
Table 4.1. Primary audiences for socioeconomic benefit studies
Purposes
Validating the
provision of
basic met/
hydro services
Validating the
provision of
specialized met/
hydro services
Supporting
investments in
new met/
hydro services
Determining
the value of
NMHS services
to user goals
Governing decisionmakers
(ministry, treasury, boards
of directors, and the like)




NMHS leadership










Audiences
Sectoral ministries and
partner agencies
External funding agencies
User communities


Chapter 4. Designing and commissioning socioeconomic benefit studies
39
Box 4.2: Stakeholder engagement in socioeconomic benefit studies
Stakeholders play a key role in the engagement process of an SEB study. Met/hydro
stakeholders include government and non-governmental organization staff, users of met/
hydro services, and the public. Before a study begins, stakeholders should be consulted to
help those managing the study to set goals. For some NMHSs, this may require beginning
with market research to determine user groups.
Alternatively, involvement of stakeholders can be implemented at the later stages of the study
– during review of the scope of work, review of study results, and communication of the SEB
study to various audiences. Stakeholder engagement must be driven by well-researched and
strategic information, as well as communicated with a clear message that provides examples
of the enhanced quality of services and improved accountability of decisionmaking as a result
of the SEB study. Stakeholders may be engaged by NMHSs through formal written
commenting rounds, information provision, semi-structured interviews, workshops and
advisory groups. Interactions can be technical, overarching or results-based. Depending on the country that the SEB study covers, varying consultation mechanisms may
be chosen. The form of consultation may be guided by legislation on transparency,
accountability and divisions between provision and reviewing of public services; this
highlights the importance of due diligence. Stakeholder involvement in the SEB study is
valuable because it communicates performance and thus provides accountable, transparent
and independent updates about services.
Three other points regarding the content and presentation of the concept note may
assist in informing decisionmakers. First, it may be useful to combine other types of
analysis with SEB analysis. For example, NMHSs may propose to conduct an analysis of
the technical quality of NMHS services and products and provide results to
decisionmakers on customer satisfaction.
Second, it may be useful to view the SEB study as one analytical element of an ongoing
process of assessment, given that NMHSs will likely need to justify resource allocations
on a sustained basis. The concept note might discuss the strategy of the NMHS for
updating the study on a regular basis.
Third, given the novelty of the commissioning of SEB studies by NMHSs, particularly in
developing countries, it might be useful to provide decisionmakers with evidence from
SEB studies in other countries that show that similar assessments yield significant benefits
and that the proposed methods are based on international good practices. An inventory
of case-studies is provided by WMO on its website (http://www.wmo.int/pages/prog/
amp/pwsp/SocioEconomicCaseStudiesInventory.htm) and Appendix E of this publication
describes a selection of SEB case studies. In addition, input from user groups, including
those with economic activities in multiple countries, can be very valuable or even
indispensable in improving the scope and accuracy of estimated benefits and cost.
4.3
STAGE TWO – PREPARE THE SCOPE OF WORK
Once a favourable decision on the SEB study has been taken, a detailed scope of work
should be prepared that includes the following components: (a) motivation/context for
the study (from the concept note); (b) roles and responsibilities for management
40
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
oversight, study preparation and review, and communicating the results; (c) plan for
conducting the study; (d) budget and timeline; (e) communication strategy. As few
NMHSs have capabilities to conduct an in-house SEB study, the detailed scope of work will
be required as one of the documents to guide responses to a competitive procurement.
The first two components will help bidders for this work to understand policy questions
to be informed by the SEB study and how the study will be coordinated, including the
commitment of staff resources that the NMHS will provide and the proposed processes
for engaging stakeholders and distributing the draft report for review.
The plan for conducting the SEB study is the key component of the detailed scope and
will help to determine funding requirements and the timeline for completing the
study. Figure 4.2 below provides a basic flow chart that summarizes the preparation of
the study as a sequence of 10 steps (referred to as SEB study step 1, and so on) and
Table 4.2 briefly describes each step and directs the reader to more detailed
discussions of each step.
SEB STUDY STEPS
SEB study step 1: Establish the baseline
SEB study step 2: Identify changes in NMHS service(s)
SEB study step 3: Identify full range of benefits and costs
SEB study step 4: Screen benefits and costs and select
analytical approach
Quantitative
Qualitative
SEB study step 5: Assess the value
of benefits and costs
in monetary terms, to the
extent feasible
SEB study step 6: Qualitatively
describe key benefits and costs
for which quantification is not
appropriate or feasible
SEB study step 7: Summarize and compare all benefits and costs
SEB study step 8: List all omissions, biases and uncertainties
SEB study step 9: Conduct sensitivity analyses
on key variable values
SEB study step 10: Formulate and communicate results
to decisionmakers and stakeholders
Figure 4.2. Steps in conducting a socioeconomic benefit analysis
Involve stakeholders
Analyse benefits and costs
Chapter 4. Designing and commissioning socioeconomic benefit studies
41
Table 4.2. Summary of socioeconomic benefit study steps
Step 1: Establish the baseline –
The baseline for the study is the current situation and provides a point of reference
for changes in the met/hydro services to be evaluated (section 4.3.1)
Step 2: Identify changes in NMHS service(s) –
These changes can involve the introduction of new services or products, expanded
geographic coverage of existing services, improvements in services, and the like
(section 4.3.2)
Step 3: Identify the full range of benefits and costs –
This step focuses on reviewing the baseline and service changes to enumerate
benefits to user communities and costs incurred under both scenarios; it is useful
to characterize the various user groups in terms of number, types, and locations
of different users in case the analysis will only focus on a sample of users or user
communities (sections 6.3 and 7.3)
Step 4: Screen the benefits and costs and select the analytical approach –
This step is critical in sizing the study and selecting estimation methods. Costs and
time constraints may limit the types of benefits or costs that can be analysed as
well as the estimation methods. At this step, data needs and availability would also
be determined as required for the estimation methods selected for the SEB study
(sections 6.4 and 7.4)
Steps 5 Analyse benefits and costs –
and 6: Benefits and costs are analysed in quantitative and qualitative terms to facilitate
determination of net benefits (benefits minus costs) (sections 6.5, 6.6, 7.5, and 7.6)
Step 7: Summarize and compare all benefits and costs –
This step involves the comparison of benefits and costs using economic criteria to
determine if the change in services results in benefits that are greater than costs
(section 8.3)
Step 8: List all omissions, biases and uncertainties –
This is important in helping NMHSs and funding authorities understand the
limitations due to data limitations, funding constraints, and uncertainties inherent in
assumptions and future values (section 8.4)
Step 9: Conduct sensitivity analysis on key variable values – This analysis follows directly
from step 8 and involves methods for presenting benefit and cost results for a range
of assumptions on uncertain variables (section 8.5)
Step 10: Formulate and communicate results to decisionmakers and stakeholders – Once
the study is completed, the results will be reviewed and formulated into results
to be shared with various audiences. The communication strategy will guide the
development of messages and mechanisms for delivering results to audiences
(sections 9.4–9.7)
The plan for conducting the SEB study can vary in detail. If there are regulations that
mandate specific types of estimation methods, this information should be
communicated in the solicitation for proposals. In some cases, the NMHS may want to
provide bidders with some flexibility to propose detailed approaches for conducting
SEB study steps 3, 4, 5 and 6.
42
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
The budget for the study can be difficult to determine until the plan for conducting the
study has been developed. If bidders have discretion to propose estimation methods,
the range of proposed project costs could vary significantly across proposals. The cost
of the SEB study depends on several factors. Simple and focused studies may require
only several person–months input, whereas wide-scoped, in-depth studies covering
multiple economic sectors may demand various person–years of input, plus significant
coordination costs and staff time in the NMHS. In some cases, the study will have to be
tailored to available resources, particularly if data are lacking or of poor quality. This
may preclude a comprehensive SEB study covering all users and benefit streams and
necessitate the use of certain types of valuation methodologies such as “benefit
transfer”, involving the use of intermediate or final results from one or more other
comparable studies (see section 6.5.4). As a general rule it will be easier to justify
comprehensive SEB studies and larger budgets when they are designed to inform
decisions on large investments in met/hydro services or demonstrate the whole-ofservice value of an NMHS.
The timeline for conducting the study should account for the time to collect data, carry
out surveys, conduct the study and draft and finalize the report. In addition, the
timeline should be adjusted to ensure adequate time for stakeholder consultations and
mandated provisions for public review of the draft SEB study. If the SEB study is
coordinated with other analyses and will be presented to decisionmakers as a package,
the timeline for the SEB study should be aligned to the timelines for these other
analyses.
4.3.1
Socioeconomic benefit study step 1: Establish the baseline
The assessment of benefits and costs focuses either on the current suite of services
(whole of service or specific services) or a change from one suite of met/hydro services
to an alternative configuration of services. The current or status-quo situation is viewed
as the base case or baseline. To establish the baseline, the study team characterizes the
services that are currently offered and the outcomes observed for the current situation.
The baseline represents the level and quality of service against which changes are
measured from the proposed NMHS programme. It is important to define the scale
and timing of the impacts of the baseline, articulate what problems the proposed
programme is intended to resolve and be explicit about assumptions.
When considering the different levels of information quality, the NMHS should also
recognize the importance of data and forecast quality and developing and maintaining
a good verification system. While standard verification measurements (for example,
500-millibar skill scores) do not translate directly to economic value, if the NMHS
cannot or does not measure the quality of its forecasts in standard meteorological
terms it will be a much less convincing process to develop economic measures of the
value of that information.
In general, when evaluating the output of an NMHS, the value of specific products or
programmes and changes in the quality of available forecasts and services is of
greatest interest. Economists consider this to be determining the value at the “margin”
Chapter 4. Designing and commissioning socioeconomic benefit studies
43
or valuing a “marginal” change in the services or products being provided. This would
usually involve a relatively small change when compared to the total set of products
and services provided by an NMHS.
Valuing the NMHS in total (that is, whole of services) is a conceptually different
problem than valuing changes in met/hydro services, and doing so would be difficult
in situations where it is unreasonable to assume that the alternative to the baseline
would be no services or products from the NMHS. The total value of an NMHS would
be the difference between current information and either persistence or climatology
(whichever it is assumed that the end users would rely on if the NMHS were not
providing any services). In some cases, the baseline information without the NMHS
may be the information provided by another NMHS (for example, from a
neighbouring country).
4.3.2
Socioeconomic benefit study step 2: Identify change(s) in
National Meteorological and Hydrological Services
To determine what is being valued, consider the primary options and what reasonable
or potential alternatives should be included in the analysis. Options often of interest to
NMHSs include changes or improvements in:
–
Observation systems;
–
Data assimilation;
–
Forecasting models;
–
Computer facilities and capacity;
–
Forecast dissemination.
Extending the traditional realm of many NMHSs may involve improvements or
implementation of new or better uses and responses to information, including
improved:
–
Forecast communication;
–
Development of decision support tools;
–
Emergency response activities for severe weather.
4.4
STAGE THREE – COMMISSION THE STUDY
In most cases, NMHSs will contract with outside organizations to prepare the SEB
study. Even if an NMHS has in-house economic expertise, it may still be better to
44
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
contract with an independent organization to emphasize the impartial nature or
enhance the credibility of the study. The NMHS can identify potential contractors via
open tendering procedures or through targeting of a limited number of pre-qualified
organizations. National and often international guidelines will indicate the tendering
procedures to be followed by the NMHS. For medium- and large-sized studies, open
tendering will often be required. For smaller studies, tendering on invitation could be
considered so as to reduce administrative burden.
In addition to the detailed scope, the tendering documentation should describe
eligibility requirements, requirements for project staffing, experience in conducting
similar studies, guidance on the preparation of the cost proposal, criteria that will be
used to evaluate technical and cost components of proposals, and instructions for
submitting proposals. The NMHS is expected to follow rules for reviewing proposals,
selecting the successful bidder and informing all bidders of their decision. If possible,
the NMHS should engage a selection committee that includes at least one member
with economic expertise.
4.5
STAGE FOUR – CONDUCT THE STUDY
The implementation of the study should align with the detailed scope and timeline. It
is encouraged that NMHSs meet frequently with the project team beginning with
project inception. In addition to the importance of these meetings to monitor progress
and address problems that may arise, these meetings will also present an opportunity
for the NMHS to become better versed in understanding economic concepts and the
methods used by the contractor, as the NMHS will later be responsible for
communicating results to decisionmakers and other audiences.
Even as the review process develops alongside the actual assessment and several
interim checks are usually built in, the overall process should allow for a formal review
phase of the entire output of the SEB study prior to the draft being made final. The
entire output should be evaluated against the requirements of the contractual
agreement with respect to contents (methods, results and interpretation of results)
and presentation (that is, clarity and tailoring of the message to the relevant
audiences).
4.6
STAGE FIVE – COMMUNICATE THE STUDY RESULTS
After the final study results and reporting are approved, the NMHS will engage in
internal and external communication of the SEB study results. This phase of the study is
described in greater detail in Chapter 9, but a couple of points are provided in this
section. First, as noted earlier, the NMHS should begin thinking about communicating
SEB study results at the stage of preparing the detailed scope to ensure that staff
responsible for communicating results will begin to identify audiences and messages
Chapter 4. Designing and commissioning socioeconomic benefit studies
45
Box 4.3: Communication – A crucial role in the socioeconomic
benefit study process
As noted in Box 3.1, a communication strategy is an essential element in the design of an SEB
study. Even though the communication element of the exercise will be primarily focused
towards the end of the process (communicating the results of the assessment to key
stakeholders), the communication needs should inform all aspects of the design of the
study. A strong story encompassing clear results will not necessarily flow from an SEB
assessment automatically – it needs to be planned for through the design and
commissioning stage. Chapter 9 provides more detail about how to approach
communication planning and strategy throughout the SEB study.
early in the process and have the opportunity to interface with the project team to
understand study methods and expected results.
Second, while communication is the final step in the SEB study design, there may be
considerable effort undertaken prior to the study’s completion. It may be useful to
conduct focus group interviews or other stakeholder consultations to test alternative
ways to communicate economic messages to different audiences. The NMHS may want
to meet with media outlets and user communities to brief them on the study while it is
underway. In addition, some preliminary communication materials may be released to
make audiences more aware of NMHS services and products and NMHS efforts
underway to assess service quality, options for strengthening or expanding services
and financing these investments.
4.7
CONCLUSIONS
This chapter has described the basic five-stage process to be undertaken in designing,
commissioning, implementing and communicating the results of an SEB study, with
only a brief introduction to the methods and analysis that are actually used to conduct
the study. The next four chapters provide additional details that will enable NMHSs to
gain an understanding of economic terms, benefit and cost assessment concepts and
methodologies, and options for comparing benefits and costs needed to prepare the
concept paper and scope of work, and work effectively with economic consultants in
supervising the study, managing reviews, and communicating the study results.
REFERENCES
Met Office, 2007: The public weather service’s contribution to the UK economy, http://www.
metoffice.gov.uk/media/pdf/h/o/PWSCG_benefits_report.pdf.
World Bank, 2008: Weather and Climate Services in Europe and Central Asia: A Regional Review.
World Bank working paper No. 151. Washington, D.C.
CHAPTER 5. ECONOMIC ESSENTIALS
Chapter 1. Introduction
5.1
INTRODUCTION
Of the five stages described in Chapter 4 to
design an SEB study, the preparation of the
Chapter 3. Purpose of SEB studies
detailed scope of work is likely to be the most
challenging for non-economists unfamiliar with
Chapter 4. Designing SEB studies
methods of measuring and comparing benefits
and costs. The next four chapters are designed
Chapter 5. Economic essentials
to help NMHSs and other service providers gain
Chapter 6. Benefits
a basic understanding of the economic
methods used to enable them to commission
Chapter 7. Costs
SEB studies and communicate the results to
Chapter 8. BCA
decisionmakers and other audiences. This
chapter introduces the reader to essential
Chapter 9. Communications
economic concepts that are discussed in greater
detail in Chapter 6 (benefits), Chapter 7 (costs)
and Chapter 8 (BCA). Appendix A includes
Chapter 10. Looking forward
definitions of economic terms used in the
publication. Basic economics textbooks (for
example, free, online options: Kling, 2002; Amos, 2014) cover most of the economic
concepts (see also the intermediate text: McAfee, 2009) that are used. The reader may
also find it useful to consult a public finance textbook (Johansson, 1991; Cornes and
Sandler, 1996; Conservation Strategy Fund, 2014) for more detailed discussion of topics
such as public goods and BCA.
Chapter 2. Met/hydro services
5.2
MET/HYDRO SERVICES INFORM DECISIONS
Met/hydro services generate net economic benefits through an integrated process
described in Chapter 2 as a value chain. The costs of producing met/hydro services are
associated with observations, modelling, forecasting and service. Once basic met/
hydro services are produced, they may undergo repackaging and tailoring into more
specialized products by the NMHSs or other service providers before they are
consumed by user communities. Figures 5.1 and 5.2 ( previously presented as
Figures 2.1 and 2.3) summarize, respectively, the production and delivery of services
and the full value chain that covers basic production and tailoring of services, plus the
uptake by users in making decisions and taking actions to produce outcomes that can
be valued in the study. To understand the economic benefits of met/hydro services,
one may consider how those services help to make better decisions. Aviators know
better when to cancel flights; farmers may avoid crop losses; and emergency officials
might be able to avert flood damages. Not all costs can be averted, of course, but some
can; and in other cases, met/hydro services create opportunities to benefit from
situations. A high snowpack estimate, for example, is often welcome news for
downstream water resource managers.
47
Chapter 5. Economic essentials
Processing & data management
Weather
Climate
Water
Observations
Modelling
Forecasting
Service delivery
Research & development
Figure 5.1. Components of the service production and delivery system of NMHSs
In the value chain, costs are incurred to produce, tailor and disseminate met/hydro
services to users (first two purple boxes in Figure 5.2). However, there are also costs
involved when users make decisions and take actions based on those decisions. While
each link in the value chain can add to the value of met/hydro services, it is more
practical to determine the benefits of services once users have responded to the
information provided by NMHSs and other providers.
Economists speak of the economic benefits of met/hydro services as an example of a
“value of information”. Given the pace of innovation in information technology,
questions concerning the value of information are of great interest to economists.
Precisely what makes met/hydro services valuable is a complex issue because
information services are technically sophisticated and because of the sheer number
and variety of decision applications. As mobile Internet devices become more
prevalent, the number and economic value of potential met/hydro service decision
applications increases. One peculiarity of information as an economic service is that
one cannot know its value with certainty until after it is produced. While accuracy is
COMMUNICATION PROCESSES
Weather
Climate
Water
SERVICE
PRODUCTION
Processing & data management
Weather/
climate/
water
Observations
Modelling
Forecasting
Research & development
Service delivery
Basic & specialized
services
NMHS & commercial
providers
User decisions
&
actions
Outcomes
VALUE
Benefits & costs
VALUEADDING PROCESSES
Figure 5.2. Simplified schematic of the met/hydro services value chain
48
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
desirable for observations and predictions in the geosciences, accuracy alone does not
guarantee that information will be useful.
It is difficult to know the value of a specific piece of information unless considering its
use in a specific decision context. What a flood warning might be worth, for example,
is hard to say unless it is known when it will occur, how many people might be
affected, and if and how they could protect themselves. In this situation, not even a
very good warning can be expected to enable all damages to be avoided. The benefits
of the warning will thus be less than the expected total loss in the absence of the
warning. More generally, the economic benefit of met/hydro services is based on the
expected outcome from an improved, service-assisted decision compared to the
expected outcome of the decision without the service (see also section 5.3).
The benefits that met/hydro services create – depending on the related decision
circumstances (for example, crops grown, resource conditions and technology) – have
become important public policy concerns. Basic met/hydro services are mainly
provided by the public sector. Estimating the economic benefit of met/hydro services
can help show if their improved provision and dissemination would offer greater value
to society than other investments, such as improvements in public health services.
5.3
ADDING UP ECONOMIC VALUE: BENEFITS AND COSTS
In economics, a cost is anything that lessens the well-being of the entire society, or
societal welfare; if resources are used to produce a particular good or service, they are
no longer available for other purposes. Most readers will be familiar with the concept
of cost as the value of the inputs needed to produce any good or service, measured in
some units or numeraire, generally money. Note that the resources sacrificed to
produce met/hydro services may or may not be directly associated with a cash flow.
For example, the use of a computer may not require any additional expenditure but
would count as a cost if it displaces other possible uses for the computer. Since multiple
met/hydro services tend to be developed and provided jointly, finding the incremental
cost of an individual met/hydro service can be challenging. In addition to provision
costs, any use of a decisionmaker’s time or other resources is also considered a cost
associated with the met/hydro service enterprise.
In contrast to a cost, a benefit is anything that increases societal welfare or represents a
gain from taking an action (Tietenberg and Lewis, 2014). The benefits of met/hydro
services result from users taking decisions at least in part based on the weather, water
and climate information that is provided. Farmers may earn higher incomes by
tailoring their planting or harvesting decisions to a seasonal forecast. A power
company may be able to better plan and reduce fuel costs for the winter heating or
summer cooling season based on such forecasts.
For both costs and benefits, economists distinguish between the total and incremental
values. In economics, incremental cost (benefit) is the change in the total cost (benefit)
when the quantity produced changes by one unit. It is the cost (benefit) of producing
Chapter 5. Economic essentials
49
one more unit of a good. Essentially, total and incremental values address different
questions. Total costs and benefits will be the focus of the SEB study when evaluating
the full suite of services of the NMHS, while incremental costs and benefits will be the
focus when assessing individual or a subset of NMHS met/hydro services or in
assessing improvements in services.
Perspective is crucial to understanding costs and benefits. Avoided flood damages that
represent a service benefit to an urban dweller, for example, may be seen as a lost
opportunity, or cost, by a builder. Since the builder is still able to pursue other projects,
his cost may be less than the benefit to the urban dweller. There are few actions that are
taken in response to met/hydro services, or more generally the provision of any type of
public service or policy, where there are not winners and losers. Some additional
discussion of the types of decision rules that are used in this case is provided in Chapter 8.
The benefits of met/hydro services, minus their costs – which economists refer to as net
benefits – represent the societal value or worth of met/hydro services. Whether and
how much public funds should be devoted to met/hydro services are important public
policy questions. Economics contributes to policy discussions an ability to quantify
changes in society’s well-being stemming from changes in the condition or availability
of met/hydro services. Improving our knowledge of economic net benefits of met/
hydro services can inform decisionmaking in at least two ways: first, it can identify or at
least approximate what the best economic choices may be; second, it can reveal the
economic importance of previous choices.
Often, met/hydro services must be processed or translated so that they more directly
address the needs of a particular decision application (for example, farming) or region.
The met/hydro services must then be interpreted by decisionmakers, who must decide
how to respond to the information. If the information, over time, results in higher
incomes or lower production costs the improvement would represent an economic
benefit. Any deficiency at one of the links in the met/hydro service value chain can
reduce benefits. For example, when users in developing countries take actions, even
though they know what decision they should make, their opportunities may be limited
and thus the benefits of a forecast may be reduced. For example, if farmers cannot
purchase more drought-resistant seeds or shift to crops that require less water, they
may not benefit from an accurate forecast. This means that other factors besides the
met/hydro service will be important in determining their benefits.13
5.4
SCARCITY AND OPPORTUNITY COST
What are the reasons for an NMHS to know the economic costs and benefits of met/
hydro services? Estimating economic values is difficult and, at times, contentious. Yet
13
Attribution of benefits to met/hydro services can be a complex problem when other types of
information are required by users to make decisions. For example, in the case of farmers’ efforts to
respond to drought, they may also require production and market information as well as access to
seed and other farm inputs to take advantage of the forecast and the understanding of the
drought’s severity.
50
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
NMHSs are frequently asked if they are making the best use of time and resources.
Economic costs and benefits demand the attention of those managing the met/hydro
process because the availability of resources such as land, labour and capital are scarce
relative to the demands placed on them. No society has the necessary productive
resources to fulfil all human wants and needs. Trade-offs exist and a sense of priorities
is essential. Because met/hydro services are costly to produce but can inform the use of
scarce resources, the decision to offer met/hydro services is partly an economic one.
Economics can inform policymakers about the costs and benefits of alternative and, in
some cases, competing uses of economic resources.
If met/hydro services such as flood and extreme weather forecasts were available for
everyone in any quantity, no economic problem would exist. But infrastructure such as
automatic weather stations and Doppler radar are scarce, and expenditures on this
infrastructure implies that some other resource demand will go unmet.
In public policy, NMHSs must frequently make choices. Because of this, NMHSs should
consider which resource uses are most highly valued. The key notion here is what
economists refer to as opportunity cost, the idea that the resource-use choices NMHSs
make will restrict or preclude other opportunities. In identifying trade-offs, economics
gives NMHSs a needed reminder that normally resource demand outweighs resource
availability.
5.5
MET/HYDRO SERVICES AS PUBLIC GOODS
Basic met/hydro services are different from most goods and services; they can be
provided at the same cost of production to a thousand or a million users. Unlike most
goods and services, one person’s consumption/use of the met/hydro services does not
reduce the availability of the services to others. This is important from the perspective
of justifying met/hydro service provision because benefits increase with the number of
users, whereas costs of production remain constant.
Many met/hydro services fall into an important category that economists refer to as
public goods. The key attribute of public goods that distinguishes them from private
goods is a property referred to as “non-rivalry” by economists. Non-rivalry means that
once a basic met/hydro service is provided for one person, it is available for all to use.14
One surprising implication of non-rivalry is that the optimal price to charge for a public
good, such as many met/hydro services, is zero. The intuition behind this puzzle is that,
once a basic met/hydro service, for one and all, has been provided, society benefits if
more people use it, and charging a price would only deter use of the public good.15
14
Even though the cost to provide the good to additional users is zero, users will still incur costs to
access the information on television, radio, or a cell phone.
15
In practice, some degree of rivalry may exist in the use of some met/hydro services, and in those
cases the service is referred to as a congested public good. The met/hydro service can be shared,
but only on a first come, first served basis. One example would be an extreme weather warning
that can only be accessed via a slow Internet connection (United Nations Industrial Development
Organization, 2008).
Chapter 5. Economic essentials
51
Another attribute ascribed to public goods is “non-excludability”, suggesting that once
the public good is provided, it should be available to all. For many public goods, it may
be technically possible to exclude users. For example, companies can exclude
households from accessing satellite television and users can be charged for information
that can only be accessed on the Internet. Unless there is public funding available to
finance the production or provision of met/hydro services or other public goods, it may
be necessary to require payment for the service in order to finance the costs of the
public good. Clearly, satellite television will not be provided by private companies
unless they can cover their costs, and some NMHSs will charge for specialized products
to cover the incremental costs of their production if there is no funding support from
the government for such specialized services.
Met/hydro services become less costly on a per user basis when the service can be
offered to a greater number of users. Since providing met/hydro services costs largely
the same, in total, regardless of how many persons use them, less populous nations
tend to pay much higher costs per user to provide the services. Similarly, a more
populous nation will often be able to provide more numerous and varied met/hydro
services since the provision costs can be allocated across a larger number of users. The
decline of unit costs for each met/hydro service with the expansion of the number of
the services offered is termed by economists as an economy of scale. An NMHS that
already provides daily temperature forecasts may find it can also provide hourly
temperature forecasts at little additional cost. The exception is the case of
geographically larger countries that pay most per user, since the cost of operation is
strongly linked to the area over which networks must be maintained. In those cases,
diseconomies rather than economies of scale are observed. When met/hydro service
provision costs decline as the variety of services rises, economists say that service
provision is characterized by “economies of scope”.
5.6
ADDING UP OVER TIME: DISCOUNTING AND PRESENT VALUES
The economic costs and benefits of met/hydro services must be aggregated over
individuals, sectors and regions to arrive at national totals. In addition, benefits and
costs will vary in magnitude over time, and an analysis that only considers their
magnitude in the current year will present an inaccurate estimate of the value of met/
hydro services. On the cost side of the ledger, the development of a new service or
expansion of an observational network will entail significant upfront investment
outlays; design and calibration of a new decision support system will involve high costs
initially, with lower costs in later years, while costs may increase over time because of
inflation. The benefits of a new met/hydro service will tend to increase over time as a
result of the learning curve or lagged adoption. For example, it may take time for users
to trust the new service enough to make economic decisions or determine how to best
respond to it. The other problem with using current-year benefits relates to the
probabilistic nature of benefits, especially those related to user responses to services
that help them understand and respond to extreme events such as droughts. In the
year of the analysis, if weather is uneventful a drought early warning system will be less
valuable than if it had been a drought year. Similarly, if benefits are expressed as
52
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
reduced damages to tropical storms and floods due to an improved forecast, current
year benefits, whether there is a flood or not, will either overestimate or underestimate
typical benefits observed over several years.
When calculating total benefits and costs over time, two interrelated factors – inflation
and the “time value of money” need to be accounted for in comparing these economic
magnitudes from one year to the next. When inflation is included in recording or
projecting values over time, it is said that the values are in “nominal” terms. Many
financial analyses are conducted in nominal terms. For economic analyses, though, it
may be more appropriate to use “real” (that is, inflation-adjusted) monetary units
(hereafter, United States dollars (US$) are used in examples). The use of real, inflationadjusted costs and benefits can result in significantly different calculations in countries
experiencing serious inflation. In real United States dollars, a dollar today has the same
purchasing power as a dollar 10 years from now, regardless of the rate of inflation.
In addition to inflation, SEB studies must account for the fact that most people prefer a
dollar today to a dollar available in the future. Most also prefer to use that dollar to
consume today or to invest to yield more than a dollar in the future. This preference for
near-term consumption over deferred consumption is called the “social rate of time
preference” or the “time value of money”. This social rate of time preference is the real
(that is, inflation-free), net-of-tax and risk-free rate of interest that would need to be
paid to a person to entice consideration of the delayed receipt of a real dollar. The rate
used for converting future values to current value is referred to as the “discount rate”
and it is expressed as a per cent per year (for example, 3% per year). It is similar to an
interest rate. The greater the preference for immediate benefits (time preference) or
the greater expected rate of return on other investments today (known as the
“opportunity cost of capital”), the greater the discount rate. For instance, a value of
US$ 100 to be realized in five years (t = 5) discounted at a 3% rate of interest (r = 0.03)
would be considered as being worth US$ 86.26 in present value (PV) (t = 0):16
PV (time 0) =
Future value (time t )
(1 + r )t
=
$ 100
(1 + 0.03)5
= $ 86.26
Alternatively, the same US$ 100 to be realized in five years (t = 5) discounted at a 10% rate
of interest (r = 0.10) would be considered as being worth only US$ 62.09 in PV (t = 0):
PV (time 0) =
$100
(1 + 0.10)5
= $62.09
The discount rate can be expressed in either nominal or real terms. A real discount rate
is the nominal discount rate minus the inflation rate. Here, the key is to use a real
16
In the examples, the dollar symbol ($) is used simply to indicate a monetary measure. The analyst
should use the unit of currency relevant to his/her decisionmaking process.
Chapter 5. Economic essentials
53
discount rate when analysing dollars in real terms and a nominal discount rate when
analysing values in nominal terms.17
The net present value (NPV) of a met/hydro service is simply the sum of its benefits
minus its costs, all expressed in PV terms. Alternatively, NPV of benefits and costs may
be summarized as a ratio (that is, the BCR) or as an implied return on investment funds
(that is, the internal rate of return). These measures use the exact same benefit and cost
measures as in the NPV approach but summarize them a little differently.
5.7
VARIABILITY, UNCERTAINTY AND RISK
Far more is known about the benefits and costs of met/hydro services in the current
year than is known in the future. The nature of imprecise future values is due to two
factors: variability – the natural variations in an estimation resulting from its properties
or the forces acting on it – and uncertainty about the estimated value that arises from
lack of knowledge about what will happen, what decisions will be taken, and how
significant will be the magnitude or timing of changes in key variables that are critical
in determining the estimated value.
Parameters such as temperature and precipitation will vary in magnitude over different
timescales; these parameters might be characterized by constructing probability
distributions based on historical data and using expected values in the SEB analysis.
For example, historical data may be used to determine the frequency and magnitude
of droughts, floods, frost, or extreme heat events and apply this information in
estimating future benefit streams. For example, if the benefits of a drought early
warning system in years where droughts occur can be estimated and assumptions can
be made on the probability of a drought (assuming away the problems of droughts
varying in magnitude for the purposes of illustration), expected benefits can be
estimated for future years by multiplying benefits by the probability of a drought.
Uncertainty relates to the lack of knowledge about the true value of a key variable or
parameter both in the present and future. For example, in SEB studies, it is difficult to
determine beforehand how individuals or business will respond to weather and
climate forecasts in any given year. Similarly, the damages of a particular class of
tropical storm are difficult to determine because many factors come into play, such as
the time of day that the storm first makes landfall, local meteorological conditions and
tidal information, as well as characteristics of the geographical area (rural, urban,
megacity, residential, industrial, agricultural, and the like). There are many sources of
uncertainty that may need to be accounted for in SEB studies, such as market forces
and inflation, innovation and technological change, political unrest, climate change
and sea-level rise.
For most of these sources of uncertainty, probabilities cannot be assigned to different
outcomes and the uncertainty is carried over into benefit and cost estimates in SEB
17
Additional discussion on determining the appropriate discount rate to use in SEB studies is
provided in section 8.2.2.
54
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
studies. However, “risk” is a form of uncertainty where, while the actual outcome of an
action is not known, probabilities can be assigned to each of the possible outcomes. In
the case of the more common types of uncertainties, sensitivity analysis can be
conducted for benefit and cost estimates to determine how significantly SEB study
results are sensitive to different values of uncertain parameters.18 The challenge in
conducting sensitivity analysis is in selecting the range of parameter values that will be
acceptable to decisionmakers and other audiences. Different methods for selecting
parameter values include: (a) establishing deviations (for example, + 15%) from an
historical value; (b) selecting values from simulation models; (c) relying on stakeholder
or expert judgment (the Delphi process) to select parameter values.
5.8
MET/HYDRO SERVICES ENTER THE MARKET PLACE –
SUPPLY AND DEMAND
Met/hydro services are produced and consumed in the market place. Costs are
incurred by NMHSs as buyers of labour, energy and equipment. In turn, a diverse
customer base of aviation, agricultural and other interests uses met/hydro services. To
estimate the costs and benefits of met/hydro services, we turn to the market place,
where most buying and selling occurs. The net benefit of met/hydro services is simply
what they are worth to their clients, based on their demand, minus the cost to NMHSs
of supplying the services. Demand is simply how much of a good or service consumers
wish to buy at various prices. Similarly, supply is simply how much producers offer at
various prices.
We usually think of the economy in terms of market economic values such as spending,
sales, output, income, employment and tax revenues generated. However, the
economic values observed in markets may well be conditioned by others not directly
transacted in markets. Met/hydro services, for instance, are seldom allocated using
market prices, although they may indirectly generate a great deal of market-based
economic activity in transportation, agriculture and tourism. Both market and
non-market values are important in determining which alternative uses of economic
resources will yield the greatest net gain to society. Who receives that gain is also
important. Economists separate market values and non-market values into two
categories, according to the group receiving the value, consumers or producers.
Economic methods are available for evaluating changes in the quality or availability of
natural resources, whether or not the uses of resources are commonly transacted in
markets. If the resource uses are traded as goods or services in markets, wellestablished empirical techniques (for example, multiple regression or computer
simulation models) exist for measuring changes in individuals’ well-being or welfare
(Chapter 6). Economists use directly observed information from market transactions to
evaluate consumer and producer surpluses as approximations of the satisfaction that
society derives from the good or service. Consumer surplus is the excess of what
18
For modelling risk, methods such as Monte Carlo simulations may be employed in economic
valuation. Additional discussion of Monte Carlo methods is provided in Chapter 8.
Chapter 5. Economic essentials
55
consumers are willing to pay over market price. Producer surplus is the excess of market
price over and above production costs.
How much better off would we be if a new met/hydro service improved the
productivity of agriculture or improved decisions in other economic sectors?
Chapters 6–8 will examine this essential question in more detail. Economics provides
methods and tools to help evaluate questions about the use of services by comparing
economic surplus — the sum of consumer surplus and producer surplus — with and
without the service. Economics can help determine if met/hydro services are highly
valued, in comparison with alternative investments, and worthy of designation as
priorities.
5.9
CONCLUSIONS
Met/hydro services are costly to provide, but create SEBs when user communities make
decisions and take actions based on the information they generate. While the
budgetary costs of met/hydro services may be apparent enough, the economic
benefits produced and how NMHSs should compare those benefits with budgetary
costs are not as widely appreciated. Public officials with limited budgets and
competing needs need to know the economic contribution that met/hydro services
make. To show the economic principles underlying the concepts of economic costs
and benefits for met/hydro services, this chapter has provided a basic overview of
economic terminology, covering supply, demand, scarcity, opportunity cost, public
goods and discounting, as well as terms such as risk and uncertainty that are
important factors that can influence the magnitude and confidence in estimates of
benefits and costs.
REFERENCES
Amos, O., 2014: A pedestrian’s guide to the economy, http://www.amosweb.com/cgi-bin/
awb_nav.pl?s=pdg.
Conservation Strategy Fund, 2014: Introduction to cost-benefit analysis. Video, https://www.
youtube.com/watch?v=7tdKkeNClPE&list=PLBfu1mD9hk64sgOIH_nUEsndUzACDe4Y&app=desktop.
Cornes, R. and T. Sandler, 1996: The Theory of Externalities, Public Goods, and Club Goods. Second
edition. Cambridge, Cambridge University Press.
Johansson, P-O., 1991: An Introduction to Modern Welfare Economics. Cambridge, Cambridge
University Press.
Kling, A., 2002: The Best of Economics, http://arnoldkling.com/econ/contents.html.
McAfee, R.P., 2009: Introduction to Economic Analysis, http://www.mcafee.cc/Introecon/IEA.pdf.
Tietenberg, T.H. and L. Lewis, 2014: Environmental and Natural Resource Economics. Tenth edition.
Boston, Pearson Addison Wesley.
United Nations Industrial Development Organization, 2008: Public Goods for Economic
Development. UNIDO sales No. E.08.II.B36 ISBN 978-92-1-106444-5. Vienna.
CHAPTER 6. DEFINING AND MEASURING BENEFITS
Chapter 1. Introduction
Chapter 2. Met/hydro services
Chapter 3. Purpose of SEB studies
Chapter 4. Designing SEB studies
Chapter 5. Economic essentials
Chapter 6. Benefits
Chapter 7. Costs
Chapter 8. BCA
Chapter 9. Communications
Chapter 10. Looking forward
6.1
INTRODUCTION
The earlier chapters have provided the
groundwork needed to frame an SEB study in
terms of questions to be answered, the
specification of met/hydro services and user
communities to be assessed. Building on that
groundwork and the introduction of key
economic concepts in Chapter 5, Chapter 6
provides guidance on the processes and
methods that can be used to assess the benefits
of met/hydro services. Specifically, the
following sections outline a general process for
conducting benefit analysis, based on the
following steps:
–
Understand the value chain;
–
Identify the full suite of economic, social and environmental benefits associated
with met/hydro services and programmes;
–
Quantify and monetize the value of benefits identified;
–
Qualitatively describe and analyse benefits that cannot be feasibly monetized;
–
Deal with uncertainty surrounding benefit estimates.
Within this framework, specific methods and models are described that can be used to
estimate the benefits of met/hydro services. An overview of general issues and
limitations that must be considered when assessing benefits is also provided. The aim
of this chapter is to provide a baseline understanding of key economic principles and
methods rather than a prescriptive approach for valuing specific benefits.
To value the benefits of met/hydro services, the analyst must understand and
characterize the potential users of the service and its impact on their decisions. This
concept is discussed in Chapter 2 through the introduction of the met/hydro services
value chain and is briefly addressed here within the context of benefit analysis.
6.2
UNDERSTAND THE VALUE CHAIN
Ultimately, the value of met/hydro services is determined based on how (and whether)
potential users receive and interpret met/hydro information, and how that information
impacts or changes their decisions and actions. The outcomes associated with these
decisions/actions are then compared to the outcomes that would have occurred in the
Chapter 6. Defining and measuring benefits
Box 6.1: Value added by
met/hydro services in
agriculture
While each link in the met/
hydro services value chain can
add value, it is often difficult
to measure the added value at
intermediate points in the
delivery of services. For
example, in agriculture,
farmers may base decisions on
observation data, but it is
likely that the observation
data will provide inputs into
the development of forecasts
or other products and that
these will be used by farmers
in making cultivation
decisions.
57
absence of the service. Thus, when assessing benefits,
it is essential that the analyst understand the relevant
components of the value chain within the context of
the service being evaluated.
As described in Appendix D, different social science
methods such as customer surveys can be employed
to assess how users have made, or will make,
decisions when presented with new met/hydro
information and services. However, in many cases it
will be necessary to make assumptions about users’
responses. This often requires expertise or
understanding with respect to specific users (for
example, households, agriculture, water resource
management and energy sector users) and
appropriate authorities should be consulted to elicit
their views on how users might respond to met/
hydro information.
When evaluating benefits at an aggregate level (for example, for a sector or
nationwide), it will also be important to evaluate or make assumptions about the rate
of adoption of specific services (that is, the percentage of targeted people/businesses
that use the service), as this will affect the magnitude of benefits realized. Economists
speak of anticipated met/hydro service adoption as an example of demand forecasting.
Demand forecasting involves both informal methods, such as expert judgment, and
quantitative methods, such as the analysis of historical usage data or survey data.
Demand forecasting may be used in pricing decisions, in assessing future capacity
needs, or in deciding whether to offer new or improved met/hydro services. In some
cases adoption may be close to 100% (for example, the use of weather forecasts by
households). For many sector-specific services, however, the rate of adoption may be
much lower, particularly in developing countries where communication of services
may be challenging or users have fewer options to act on improved or new met/hydro
services. Factors that may impact the behaviour of potential users and the rate of
adoption of the met/hydro service being valued include:
Box 6.2: Framing the benefit analysis
Considerations in framing the analysis and identifying benefits of met/hydro services might
include:
– Understand the climate services value chain;
– Identify potential users and how climate service information impacts their decisions
(typically requires working with users);
– Apply a triple bottom line (TBL) approach to identify the full suite of financial, social and
environmental benefits;
– Consider whether the climate service will result in non-marginal changes or downstream
impacts;
– Identify all benefits regardless of to whom, when or where they accrue.
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VALUING WEATHER AND CLIMATE:
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–
How well the service is communicated to the user;
–
Characteristics of the service (for example, accuracy or lead time);
–
Decisionmaker characteristics (for example, risk aversion, or prior knowledge of
information);
–
Decisionmaker environment (for example, government programmes and policies
that might affect adoption of services, community norms);
–
Availability of resources and management options for changing behaviour in
response to information.
Although it may be difficult to incorporate many of these factors into the benefits
assessment, it is important to recognize how they might impact the outcome of the
analysis (for example, identifying whether these factors lead to an overestimation or
underestimation of value). Performing sensitivity analyses surrounding these assumptions
(see section 8.5) can also help to quantify the potential impact of these different factors.
For example, many studies of the benefits of met/hydro services assume that the service
includes a perfect forecast. However, the benefits of the service may vary considerably
based on the conditions that actually occur and how they differ from the perfect forecast
scenario. To assess the range of potential benefits associated with a given service, it is
advisable to evaluate two or more scenarios under which forecast accuracy varies.
In addition, as discussed in Chapter 3, studies of the benefits of met/hydro services can
include ex-ante or ex-post assessments. In ex-ante assessments, the value of climate
services is forecast in advance of their provision. In practice, people must make choices
and reveal values ex ante before they know which state of the world will actually
prevail. Ex-post studies cannot capture what people may be willing to pay to avoid risk
but, to their advantage, are based on actual data regarding the historical or current use
and value of existing met/hydro services. To estimate service value ex post requires
assumptions regarding what would happen without met/hydro services.
Ex-ante studies typically assume that baseline decisions taken by users are based on
perfect knowledge of historical climate data or on the forecast available at the time.
The value of these baseline decisions is then compared to the value of simulated, and
presumably more beneficial decisions than would be taken in the baseline case.
Simulations are typically based on historical (that is, retrospective) conditions,
especially if an improvement in met/hydro services is to be evaluated. For ex-ante
studies of new services, an analysis of decisionmaking behaviour, including attitudes
towards risk, might be undertaken to specify simulation assumptions about behaviour.
These analyses might include discussions with experts or surveys and/or focus group
interviews with potential users.
In relationship to this chain, ex-ante studies are extremely important for providing
insight into the potential value of climate services prior to their implementation.
However, the necessary assumptions associated with these studies introduce some
uncertainty into the analysis. For example, in studies related to agriculture, crop
Chapter 6. Defining and measuring benefits
59
simulation models are used to represent how crop output might change in response to
decisions made with and without the met/hydro service being evaluated. These
models are assumed to match on-the-ground conditions, but do not account for many
aspects of human behaviour. In reality, even if a farmer does adopt a specific
management strategy, it may take several years before he or she begins to see returns.
The farmer may also choose to implement a different strategy, or may not have the
resources to change farming techniques at all. He or she may also decide to pursue
other means of income for the season. These types of behavioural effects are not
included in most models and studies.
Resolving this issue completely would require extensive ex-post studies conducted after
forecasts have been widely communicated and adopted for a sufficient period to allow
for learning and widespread adoption (Meza et al., 2008). However, ex-post studies are
often very expensive and time-consuming to conduct. Studies that combine qualitative
social science methods for understanding the determinants of the use of forecasts and
value with modelling approaches that can realistically incorporate this information can
help to reduce the uncertainty associated with ex-ante studies (Meza et al., 2008).
6.3
SOCIOECONOMIC BENEFIT STUDY STEP 3:
IDENTIFY THE FULL RANGE OF BENEFITS
The point of departure for this discussion is provided by SEB study steps 1 and 2 (see
Figure 4.2) concerning establishment of the baseline scenario and identification of the
change in services to be valued. Step 3 focuses on determining the types of benefits
associated with the met/hydro service(s) to be evaluated. As described below, it is
recommended to apply a TBL approach to identify the full suite of financial, social and
environmental benefits, including those that can easily be quantified and monetized
and those that are more amenable to qualitative evaluation.
As detailed above, to identify potential benefits, NMHS staff should consider how the
climate service will be used and how the use of the service will change outcomes
associated with a specific decision or action (vis-à-vis the value chain). For example,
agricultural users of met/hydro services might alter crop management decisions in
response to new met/hydro information, which would result in increased profits or
reduced losses in the event of extreme weather phenomena such as droughts.
Households and businesses may make more informed decisions about preparing for an
extreme event if early warning systems were improved, resulting in additional lives saved
and less property damage. Users of met/hydro services in the energy sector may be able
to optimize hydropower operations based on improved streamflow information. This
would result in increased revenues and, potentially, a more reliable supply of energy.
Triple bottom line benefits
To determine the total economic value of met/hydro services, it is important that all
benefits be identified, regardless of to whom they accrue or where they might be
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realized. This includes the financial benefits (for example, increased revenues) of a
given service or programme, as well as any environmental and social benefits that may
result (for example, lives saved, improved recreational experiences, minimization of the
release of toxic substances, and the like). The inclusion of environmental and social
values in the economic analysis process is often referred to as TBL accounting.
Table 6.1. Examples of the triple bottom line benefits of met/hydro services
–
–
–
–
Avoidance of loss of life and/or injuries/illnesses from natural disasters
Safety and security of the travelling public
Improved information and data to the scientific community
Contribution to the day-to-day safety, comfort, enjoyment and general
convenience of citizens, including:
–Recreation
– Travel and commuting
– Preparation for severe weather
– Home improvement decisions
– Other direct and indirect forms of societal benefits
– Event management
–Avoided climate-related illnesses (for example, heat-related illnesses,
vector-borne diseases that are worsened by climate such as malaria)
–
–
–
–
–
–
Long-term monitoring of basic indicators of the state of the environment
Minimization of release of toxic substances and other pollutants
Management of local environmental quality
Support for addressing major global environmental issues
Water savings
Reduced runoff from fertilizer application, resulting in improved water
quality
–
–
–
–
–
–
–
–
–
–
–
–
Avoidance of crop losses from frost, hail or drought
Increased farm production and sales
More efficient scheduling of the use of agricultural machinery
Reduced transportation fuel consumption through route planning
Improved scheduling of flight arrivals and departures
Minimization of airline costs from aircraft diversions
Minimization of search and rescue costs
Minimization of drought-relief costs
Efficient scheduling of ship loading facilities
Avoidance of unnecessary shutdown of offshore oil and gas operations
Avoidance of weather damage to personal property
More efficient planning of energy production and delivery
Social
Environmental
Economic
Source: Lazo et al. (2009)
61
Chapter 6. Defining and measuring benefits
The TBL approach accounts for the fact that the benefits of services extend well beyond
the traditional financial bottom line that portrays only cash flows (that is, revenues and
expenditures), or other benefits that are more easily monetized. As providers of met/
hydro services, NMHSs and commercial weather services also need to consider their
stewardship and other responsibilities and to thus account for how they may generate
values that contribute towards the social and environmental bottom lines. Section 6.5
discusses methods employed by economists to monetize social and environmental
benefits (which often include “non-market” benefits) associated with met/hydro services.
In the current context, the TBL approach provides an organizing framework within
which the broad array of benefits associated with climate services can be portrayed
and communicated. This TBL approach should include those outcomes that can be
quantified and monetized (including both market and non-market benefits described
below), as well as outcomes that are less amenable to reliable valuation and instead
require qualitative discussion.
Table 6.1 provides several examples of different types of social, environmental and
economic benefits often associated with met/hydro services. Many of these benefits
can be analysed at the individual or household level (for example, improved crop
yields experienced by an individual farmer), as well as at the sector (for example,
avoidance of unnecessary shutdown of offshore oil and gas operations), or national
levels (for example, impacts across multiple sectors of the economy). Figure 6.1
provides an illustration of a comprehensive review of the potential range of benefits
from an actual study (Lazo et al., 2009).
Marine resource
mgt. benefits
Private sector
benefits (e.g.,
highways)
New
supercomputer
Improved
environmental
modelling
International
benefits
Improved
operational
forecasts
(NWS benefits)
DOE benefits
(wind)
Air force
benefits
Agriculture
benefits
Marine
transportation
benefits
Household
benefits
Total
benefits
Retail
benefits
Aviation
benefits
Energy benefits
(temps., wind)
Army
benefits
Figure 6.1. Benefits of improved weather modelling
Note: NWS = United States National Weather Service; DOE = United States Department of Energy.
Sources: Lazo et al. (2009); Lazo et al. (2010)
62
6.4
VALUING WEATHER AND CLIMATE:
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SOCIOECONOMIC BENEFIT STUDY STEP 4:
SCREEN THE BENEFITS AND SELECT THE ANALYTICAL APPROACH
Once the financial, social and environmental benefits have been identified, the next
step is to screen the benefits to determine their relative importance (for example, in
terms of magnitude) and assess which are most likely to be amenable to quantitative
assessment and those that will be difficult to assess, except in qualitative terms. Once
this screening has been completed, methods for assessing benefits can be selected.
Additional discussion of methods is provided in sections 6.5 onwards.
As shown in Table 6.1, outcomes associated with met/hydro services may include
increased crop yields (yield per hectare), lives saved, reduced illnesses due to climaterelated disease, energy savings (and associated reduction in carbon emissions and
other greenhouse gases, water savings and increased recreational visitor days, among
others. The quantification of the value of these outcomes can involve extensive
modelling efforts and often requires expertise in relevant fields. It is therefore often
very important to work closely with experts in health, agriculture, water-resource
management, energy and other sectors to complete this stage of the analysis. The
principal role of the economist at this stage is to ensure that the information provided
is useful for the subsequent economic valuation models that may be used later in the
benefit analysis. The analyst should give special care to ensuring that the outcomes
evaluated are appropriate for use in benefits estimation. Effects that are described too
broadly, or that cannot be linked to human well-being, will limit the ability of the
analysis to capture the full range of a policy’s benefits (United States EPA, 2010). It is
also important to determine to what extent the benefits can be fully attributed to the
met/hydro service. For example, most users will consider a range of information in
making decisions on the met/hydro service. Farmers deciding whether to plant
drought-resistant seeds or shift to alternative cultivation will take into account
production and market information before planting their crops.
6.5
SOCIOECONOMIC BENEFIT STUDY STEP 5:
ANALYSE THE VALUE OF BENEFITS – QUANTITATIVE
Building on the efforts described above, the next step in the analysis is to assign value
to the benefits identified and quantified, where feasible and practical. Economists
employ various demand-side methods to estimate the value of information (such as
forecasts provided by NMHSs), including:
–
Directly asking users of the information to subjectively assess the value of the
data: this method must be carefully designed and executed, using standard
economic approaches or the results may not be credible;
–
Inferring the value of the service based on observations of people’s behaviour
and the costs they voluntarily bear: with this method, economists can use data
collected from subjects or respondents to develop proxy prices for the
information. This data may include actions taken to avoid the impacts of
Chapter 6. Defining and measuring benefits
63
weather‑ and climate-related events, or the additional costs that people bear to
recreate in areas that have better forecast information;
–
Economic (decision) modelling of the situation in which the information is used:
economic modelling involves formulating mathematical relationships to
represent decisionmaking and the value (or cost) outcomes that result, both with
and without information. This makes it possible to calculate the value increase
attributable to the information;
–
Applying findings from similar studies: original studies to estimate the values
associated with the use of met/hydro services can require a significant amount of
time and financial resources. For this reason, researchers often use the benefittransfer approach to estimate these values. Benefit transfer involves the transfer
of existing economic values estimated in one context or study to estimate
economic values in a different context;
–
Data analysis, in which historical records are analysed or surveys conducted to
determine the actual difference made by that information (ex post): data analysis
requires that the data span a period of time, or space, or circumstances in such a
way that the information was available for some, but not all, of the situations
represented by the data.
Table 6.2 provides an overview of the various methods that can be used to value met/
hydro-related services, including non-market valuation techniques, economic
modelling approaches, avoided-cost assessments and benefit transfer. Each of these
methods is discussed in more detail below.
6.5.1
Non-market valuation techniques
As noted above, there are no market prices for many of the key outcomes associated
with the use of met/hydro services. Assigning monetary values to these outcomes will
therefore require the use of non-market valuation methods, including revealedpreference and stated-preference approaches. As noted in Table 6.2, these methods
rely on primary data collection to assess benefits.
Stated-preference methods
Stated-preference methods rely on survey questions that ask individuals to make a
choice, describe behaviour, or state directly what they would be willing to pay for the
non-market good being evaluated. The methods that use this type of data are referred
to as stated-preference methods because they rely on survey data that are stated in
response to hypothetical situations, rather than on behaviour observed in actual
markets.
Stated-preference methods are based on the notion that there is some amount of
market goods and services (which people buy with their income) that people would be
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Table 6.2. Valuation methods
Method
Non-market
valuation –
Stated
preference
Non-market
valuation –
Revealed
preference
Economic
modelling
Description
Contingent
valuation (CV)
– Survey-based elicitation of individuals’ preferences
and values (for example, WTP)
Conjoint
analysis
– Similar to CV, except respondents are surveyed
about a set of choices instead of a single WTP
question
Averting
behaviour
– Determines values based on expenditures that
would have been made to reduce impacts of
weather or climate events, but were avoided
because of improved met/hydro information
Travel cost or
expenditure
modelling
– Uses observed tourist and recreational trip-taking
behaviour to determine whether people pay more
to visit sites for which forecasts are available
– Can rely on other expenditures or costs incurred to
search for or obtain met/hydro information
Hedonic
analysis
– Uses observed housing, property, or labour market
behaviour to infer values for quality changes
Decision
analysis
– Analyses decisions and resulting values when
people have access to met/hydro services and when
they do not
– Typically paired with business or production models
Equilibrium
modelling
– Examines changes in supply and demand, and price
effects associated with use of met/hydro services
– Measures resulting gains/losses for producers and
consumers
Econometric
modelling
– Examines statistical relationships to determine
specific outcomes associated with the use of met/
hydro services
– Regression analysis is the most common form of
econometric modelling
Avoided-cost
assessment
– Evaluates benefits based on avoided costs of
weather and climate events due to better met/hydro
information, including avoided asset losses, lives
saved, and avoided morbidity impacts
Benefit transfer
– Applies results of existing valuation studies and
transfers them to another context (for example, a
different geographic area or policy context)
Chapter 6. Defining and measuring benefits
Advantages
65
Disadvantages
– Estimates use and non-use values
– Incorporates hypothetical scenarios
that closely correspond to policy case
– Time intensive and expensive to implement
– Challenging to frame survey questions that
elicit valid responses
– Potential response biases
– Uses observed data to conduct ex-post
analyses
– Tailored to specific policy case
– Expenditures easy to estimate through
surveys
– Values interpreted as lower bound estimates
because averting expenditures only capture
a portion of an individual’s WTP to avoid a
particular harm
– Uses observed data to conduct ex-post
analyses
– Tailored to specific policy case
– Measures use values only
– Collecting adequate data is often expensive
and time intensive
– Uses observed data to conduct ex-post
analyses
– Tailored to specific policy case
– Measures use values only
– Requires extensive market data
– Assumes that market prices capture the good’s
value
– Useful to examine decisions and
expected outcomes at household or
firm level
– Can be relatively simple to perform
depending on model employed
– Can be time and data intensive, depending on
model employed
– Requires sector expertise (for example,
agriculture, transport)
– Often assumes perfect information as a
simplifying measure
– Partial equilibrium modelling useful
to examine benefits of met/hydro
services for a specific sector
– Time and data intensive
– Expensive to implement
– Requires significant expertise
– Uses observed data to conduct ex-post
and ex-ante analyses
– Can require significant amounts of data and
expertise
– Can be applied in ex-post and ex-ante
analyses
– Relatively easy to implement
– Only represents partial value (for example, it
does not take into account benefits of met/
hydro services associated with increased
productivity and enjoyment)
– Relatively simple and inexpensive
– Accepted as a suitable method for
estimating order-of-magnitude values
for use and non-use benefits, in expost and ex-ante analyses
– Can generate potentially inaccurate and
misleading results
– Limited number of original studies
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willing to trade off so they can benefit from a non-market good. This is often measured
in terms of WTP for a non-market outcome, although the methods have also been used
to assess how much compensation people would be “willing to accept” to give up a
non-market good they already benefit from.
The advantages of stated-preference methods include the ability to estimate both use
and non-use values and to incorporate hypothetical scenarios that closely correspond
to the policy case through the use of a well-designed survey. The main disadvantage of
stated-preference methods is that it may be subject to systematic biases that are
difficult to test for and correct (United States EPA, 2010). Stated-preference methods
typically require the assistance of experts with experience in survey design and
economic modelling. These can be time intensive and expensive to implement.
The most widely used stated-preference technique has traditionally been the CV
method, where respondents are presented with information about a non-market good
or service (or changes in quality of the good or service) and asked to indicate how
much it would be worth to them. Contingent valuation surveys can ask respondents to
state directly what they would be willing to pay (open-ended CV), or whether they
would be willing to pay a specified amount (referendum CV, where the specified
amount varies across respondents). Another form of CV is to provide the respondent
with a series of dollar values and ask them to indicate which of the options represents
the maximum they would be willing to pay for the good or service being evaluated
(payment-card CV).
More recently, “choice experiments” have begun to be used more extensively to
estimate WTP. This is largely due to the potential biases associated with CV methods
and the lack of easily implemented procedures to mitigate these biases. In choice
experiment surveys consumers are presented with two or more options for a good or
service and are asked to state which option they prefer. By examining consumer
preferences for the attributes and prices associated with their preferred option, WTP
can be inferred by the analyst.
In the context of met/hydro services, several published studies have assessed
household WTP using stated-preference methods (mostly CV). For example, Anaman
and Lellyett (1996a) conducted a survey in the Sydney metropolitan area to estimate
the economic value households attach to basic public weather forecasts and warnings.
Results indicated that the average annual WTP for these services was about $A 24
(about US$ 19) per person. In a similar study, Lazo and Chestnut (2002) found the
median household WTP for current weather forecasts in the United States to be
US$ 109 per year. As described in more detail in Appendix E (case study 8), Lazo and
Croneborg (forthcoming), conducted a CV study to assess the potential benefits
associated with a proposal to improve weather services in Mozambique. Results of the
study indicated a mean annual WTP of about US$ 0.09 per individual for improved
weather forecast information. Aggregation of results across the Mozambican
population over a 50-year benefit lifespan suggested total PV benefits of over
US$ 50 million – significantly more than the projected fixed costs of the project of
about US$ 21 million.
Chapter 6. Defining and measuring benefits
67
Several studies have also assessed WTP for met/hydro services by businesses or sectors.
Rollins and Shaykewich (2003) used CV to estimate benefits generated by an
automated telephone answering device that provides weather forecast information to
commercial users in Toronto, Canada. Average value per call varied by commercial
sector from US$ 1.58 for agricultural users to US$ 0.44 for institutional users, with an
overall mean of US$ 0.87 per call.19 With roughly 13.8 million commercial calls
annually, benefits were estimated to be about US$ 12 million per year. Anaman and
Lellyett (1996b) also surveyed cotton producers to determine WTP for an enhanced
weather information service tailored to the cotton industry. At the time of the survey (a
drought period), average WTP for the service was about US$ 175. In addition,
producers indicated they were willing to pay an average of US$ 204 annually for the
use of the service during a period of good rainfall. Makaudze (2005) investigated the
value of seasonal forecasts to farmers in Zimbabwe via CV surveys. Results showed that
WTP for improved seasonal forecasts ranged from US$ 0.44 to US$ 0.55. Households in
wet districts revealed consistently lower WTP than those in drier districts.
Stated-preference methods typically provide average per-person or per-household
estimates for the survey respondents, which can be extrapolated to the wider
population to provide an indication of the total non-market benefits or costs of a policy
option. This requires making assumptions about the extent of the population that will
be affected by the policy change and whether people who chose not to respond to the
survey would also value the outcomes.
Revealed-preference methods
Willingness to pay can also be inferred from choices people make in related markets.
Methods that employ this general approach are referred to as “revealed-preference
methods” because values are estimated using data gathered from observed choices
that reveal the preferences of individuals. For instance, although there may be no
markets in which to buy and sell days of outdoor recreation, individuals often incur
costs to undertake direct recreational-use activities. For these types of uses, incurred
costs can be assessed to develop proxy “prices” for the activity. That information can
then be used to determine the demand curve for recreation-related services for which
value can be estimated. This approach uses observations of people’s behaviour or their
associated expenditures as indications of revealed preferences for the service.
The most common revealed-preference methods are “hedonic pricing”, “travel cost”
and “averting behaviour”. Within the context of met/hydro services, the hedonicpricing and travel-cost methods have limited application. Hedonic pricing can be used
to value a wide variety of factors that influence observed prices. For instance, in theory
it would be possible to infer the value of a weather forecast by comparing the price
difference between two newspapers, one that contained a forecast and one that did
not, with the papers being identical in every other attribute (should such a situation
ever occur).
19
Values converted from Canadian dollars to United States dollars based on an average 2003
exchange rate of 1.375 Canadian dollars.
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The travel-cost method accepts as a maintained hypothesis that economic demand
functions for recreation are revealed by the choices people make to travel to a
particular location. The essence of the method is recognition that users pay an implicit
price by giving up time and money to take trips to specific areas for recreational
activities (United States EPA Science Advisory Board, 2009). In relation to met/hydro
services, travel-cost methods could be used to estimate how much more people pay to
take recreational trips to areas that provide better forecasts.
The averting-behaviour method is more directly applicable to assessing the benefits of
met/hydro services. This method infers values from defensive or averting expenditures
(for example, actions taken to prevent or counteract the impacts of weather or climate
events). Because better weather forecasts may make such expenditures unnecessary,
this approach can measure the benefits of improved forecasts. This could include, for
example, installing storm shutters or temporary levee materials around a home to avert
impacts from potential flooding. These expenditures are relatively easy to estimate
through surveys.
Averting-behaviour methods can be best understood from the perspective of a
household production framework. To the extent that averting behaviours are
available, the model assumes that a person will continue to take protective action as
long as the expected benefit exceeds the cost of doing so. If there is a continuous
relationship between defensive actions and reductions in risks, then the individual will
continue to avert until the marginal cost just equals his/her marginal WTP (or marginal
benefits) for these reductions. Thus, the value of a small change in risk can be
estimated from (a) the cost of the averting behaviour or good, and (b) its
effectiveness, as perceived by the individual, in offsetting the loss in environmental
quality (United States EPA, 2010).
The averting-behaviour method typically generates values that may be interpreted as
lower bound estimates because averting expenditures only capture a portion of an
individual’s WTP to avoid a particular harm and generally does not take into account
the loss of utility from pain and suffering. The most common application of avertingbehaviour models has been the estimation of values for morbidity (illness) risk.
6.5.2
Economic decision modelling
Various economic modelling approaches can also be used to assess the benefits of
met/hydro services and information. These models can rely on primary and/or
secondary data as inputs to model decisionmaking and the value (or cost) outcomes
that result, both with and without information. Within the context of met/hydro
services, economists use models to determine the value of information for single
agents or entities (referred to here as decision analysis), as well as to determine how
the broad use of met/hydro services can impact local, regional or national economies
(through the use of equilibrium modelling). The following paragraphs describe these
two modelling approaches.
Chapter 6. Defining and measuring benefits
69
Decision analysis
Studies that employ economic decision models typically analyse a single agent or
entity that is responsible for making a decision(s) to maximize (or minimize) an
objective (for example, represented by a utility function, production function, cost–
loss model of two alternatives or other economic model). These studies assume that
the decisionmaker makes decisions based solely on the effect of the decisions on his/
her payoffs (Rubas et al., 2006).
In the context of met/hydro services, these studies often assume that decisionmakers
have some level of prior climate knowledge. Without updated climate information, the
decisionmaker uses his/her prior knowledge to make decision(s). If updated
information is provided, the decisionmaker will use this information to make optimal
choices. The value of met/hydro information is then equal to the difference between
the benefits when the information (that is, updated knowledge) is used, compared to
the benefits when prior knowledge or no forecast is used (Rubas et al., 2006).
The use of decision models is appropriate when the choice of a decisionmaker or entity
cannot affect an outcome for another decisionmaker. For example, a single agricultural
decisionmaker interested in adopting seasonal forecasts would have little impact on
supply or demand and would therefore have little impact on price (Rubas et al., 2006).
Decision models are typically paired with business or production models (for example,
crop growth simulation models or fisheries management models) to identify optimal
decisions under alternative forecast scenarios.
Many studies have used some form of decision model to estimate the value of met/
hydro services. For example, in the agricultural sector, Meza and Wilks (2004) estimate
the value of perfect sea surface temperature anomaly forecasts for fertilizer
management in Chile to be US$ 5 to US$ 22 per hectare for potato farmers, compared
to a no-forecast approach. In the transportation sector, Berrocal et al. (2010) found
that the use of probabilistic weather forecasts for predicting ice conditions reduced
costs for the Washington State Department of Transportation by 50% relative to the
use of deterministic forecasts.
In the energy sector, Hamlet et al. (2002) evaluated the use of long-lead streamflow
forecasts in the management of hydroelectric dams on the Columbia River in northwest United States. The authors found that use of these forecasts could increase energy
production by 5.5 million megawatt hours per year, resulting in a US$ 153 million
increase in net revenues (compared to shorter lead time snowpack forecasts). For this
study, the authors assume that monthly prices are “unaffected by the relatively small
shifts in energy production from spring to fall examined here” (Hamlet et al., 2002,
p. 98, as cited in Rubas et al., 2006). Several studies in the fisheries sector make similar
assumptions (for example, Costello et al., 1998; Kaje and Huppert, 2007).
While it may be acceptable to assume that the decisions taken by a single economic agent
or small number of businesses will not affect prices, it is inappropriate when considering a
large number of producers or a large impact on the supply and demand conditions of the
process. In these cases, other methodologies must be used (Rubas et al., 2006).
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Macroeconomic or equilibrium models
Equilibrium models recognize that the choices of different decisionmakers are
interlinked. For example, in the agricultural sector, if one producer uses seasonal
forecasts, prices will not change because the production of a single producer is very
small relative to total (for example, regional) production. However, as the number of
producers using seasonal forecasts increases, the change in total production will cause
price changes, which will result in changes in supply and demand – and prices – for
related goods and services. Producers who do not anticipate this change may not make
optimal choices (Rubas et al., 2006). Equilibrium models take these effects into
account, providing estimates of consumer and producer surplus as a measure of the
benefits to society.
When looking at how users respond to improved
or new information, we are typically limited to
partial equilibrium as opposed to general
In economics, general
equilibrium analysis (see Box 6.3). Typically,
equilibrium theory attempts to
general equilibrium models have not been used
explain the behaviour of supply,
to value climate services, likely due to their
demand, and prices in a whole
complexity and extensive information
economy with several or many
requirements. However, several studies have used
interacting markets, by assuming
that a set of prices exists that will
decision analysis and partial equilibrium models
result in an overall (or “general”)
to examine the value of met/hydro information
equilibrium. General equilibrium
for specific sectors (Rubas et al., 2006). For
theory is distinguished from
studies related to agriculture, analysts have used
partial equilibrium theory by the
crop-growth simulation models in conjunction
fact that it attempts to look at
several markets simultaneously
with decision theory models to develop
rather than a single market in
producers’ production responses from forecast
isolation.
use. The analysts then apply partial equilibrium
models to develop aggregate supply
relationships. Changes in aggregate supply caused by the use of met/hydro
information affect price, which is taken into account by individual producers
(represented in the model) when making decisions (Rubas et al., 2006).
Box 6.3: General
equilibrium theory
As reported by Rubas et al. (2006), a series of related studies have examined the effect
of ENSO-based climate forecasts on the agricultural sector using a previously
developed model of United States agricultural production. Chen and McCarl (2000)
and Chen et al. (2001) report that producer surplus decreases by using ENSO-based
forecasts (due to decreased prices associated with increased production), but
consumer surplus increases enough that overall social welfare increases. Chen et al.
(2002) report that using the five-phase ENSO definition almost doubles social welfare
gains compared to the more standard three-phase definition (Rubas et al., 2006).
Using a similar model, Adams et al. (2003) report the value of an ENSO-based system
to be US$ 10 million annually for Mexican agriculture. Mjelde et al. (2000) use a
previously developed dynamic model to show that use of seasonal forecasts in the
production agricultural sector will affect machinery manufacturers, food processors
and retailers, and the financial sector (Rubas et al., 2006).
Chapter 6. Defining and measuring benefits
71
In the water sector of Taiwan Province of China, Liao et al. (2010) developed a partial
equilibrium regional water economic model to evaluate the economic impacts of ENSO
events on a regional water market with and without the use of ENSO information.
Results showed that a water-management strategy based on transferring water among
different groups could potentially increase social welfare by as much as US$ 11.6 million
when ENSO information was provided.
6.5.3
Avoided cost/damage assessments, including avoided mortality
and morbidity impacts
Avoided costs can be an important part of valuing the range of benefits likely to be
generated by climate services largely using market information. For instance, these
benefits accrue from reducing or eliminating expenditures related to power generation
(for example, power companies increasing their production in anticipation of high
temperatures) or reduced evacuation costs. These costs can also be deferred to later
years. Using NPV analysis (discussed in more detail in Chapter 8) allows us to compare
benefits accrued in different years on a similar basis. The analyst must be alert to
potential issues, however, when using avoided costs as a proxy for benefits values.
Avoided costs can be used as measures of benefits when they would actually be
incurred in the absence of the climate services (for example, a power company
increases production to err on the safe side, but improved forecasting would have
changed that decision).
Several studies have calculated avoided costs associated with the use of met/hydro
services. For example, Considine et al. (2004) used a probabilistic cost–loss model to
estimate the incremental value of hurricane forecast information to oil and gas
producers in the Gulf of Mexico. Results showed that the value of a 48-hour forecast
amounted to US$ 8.1 million annually in terms of avoided costs and foregone drilling
time. Frei et al. (2014) found that the use of meteorological (weather) services by the
transportation sector in Switzerland would result in US$ 56.1 million to
US$ 60.1 million in avoided governmental spending. As detailed in Appendix E (case
study 6), von Grünigen et al. (2014) applied a simple decision model to assess the
avoided fuel and flight deviation costs for airlines due to the use of terminal
aerodrome forecasts (TAFs). Anaman et al. (2000) also studied the benefits of TAFs,
conducting an (ex-post) econometric analysis to assess avoided fuel costs associated
with the use of TAFs for Qantas Airways Limited. Results indicated that the
abandonment by the airline of mandatory requirement for aircraft to carry alternate
fuel in 1985, in favour of carrying such extra fuel based on weather forecasts, saved
between US$ 19 million and US$ 30 million per year in reduced fuel consumption (in
1993/1994 United States dollars).
The World Bank conducted a series of studies to assess the avoided costs associated
with large-scale modernization of NMHS services in 11 countries in Europe and Central
Asia (see Appendix E, case study 1). These studies rely on simplified approaches,
specifically sector-specific and benchmarking approaches, developed by the Bank to
compare order-of-magnitude benefits of reducing damages from weather-related
events to the costs associated with improving met/hydro services.
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The sector-specific method values the economic benefits that would accrue in weatherdependent sectors from modernization of NMHS agencies. This method relies on
available country data and surveys of national experts from NMHS agencies and
weather-dependent sectors to (a) estimate current sectoral losses from weather events,
and (b) determine the potential reduction in losses that modernization would achieve.
The World Bank also uses surveys to determine the costs associated with actions taken
by organizations and entities to prevent weather-related losses, both with and without
modernization. The Bank uses this information to compare the benefits of
modernization, expressed as the additional prevented losses from hazardous events
and unfavourable weather, to the costs associated with modernizing the NMHS and
implementing preventive measures. This comparison (that is, the incremental
reduction in weather-related losses compared to the costs of modernization)
represents the “economic efficiency” of met/hydro improvements, as defined by the
World Bank.
The World Bank has used the sector-specific approach to estimate both the direct and
indirect economic losses that would occur as a result of unfavourable weather events,
with and without modernization. Direct economic losses are those that are caused by
direct destruction, breakdown or damage to any types of property and tangible assets.
Indirect economic losses include losses that a business entity or economic sector suffers
because of decreased revenues or additional expenditures on production cycles.
Similar to the sector-specific approach, the benchmarking method assesses the losses
caused by earlier events and estimates the reduction in losses that could be achieved
with improved services. However, the benchmarking method provides a way to
address limited sector-level data and expertise on weather-related losses. This method
relies on expert opinion and readily available data to assess the vulnerability of the
country’s overall economy to weather-related events and obtain results about direct
damages caused by weather impacts.
Benchmarking is carried out in two stages:
–
–
Determining benchmarks: Using data and estimates from other countries and
expert judgment, the authors define and adjust the following two benchmarks
for each country:
–
The level of annual direct economic losses caused by met/hydro hazards
and unfavourable weather events, expressed as a share of gross domestic
product (GDP);
–
The level of annual prevented losses, with and without modernization,
expressed as a percentage of the total level of losses;
Correcting benchmarks: In this stage, data are adjusted to benchmarks
according to country-specific estimates of weather and climate conditions,
structure of the economy and other factors.
Chapter 6. Defining and measuring benefits
73
For the countries in Europe and Central Asia, the World Bank determined the level of
annual direct losses and annual prevented losses based on findings from studies
conducted in several countries (unlike the sector-specific approach, the benchmarking
approach only considers direct damages caused by weather impacts). These studies
showed that the mean annual level of direct losses from met/hydro hazards and
unfavourable events varies between 0.1% and 1.1% of GDP.20 The studies also showed
that the share of prevented losses may vary from 20% to 60% of total weather and
climate-related losses. Based on these parameters, the World Bank studies in the
countries covered yielded BCRs of between 1.8 and 9.2 for investments in improved
met/hydro services.
To assess the value of these basic parameters for a specific country, the Bank makes
adjustments to the average values based on in-country characteristics, including: the
weather dependence of the economy; meteorological vulnerability; the current status
of met/hydro service provision; national climate; agency capacity; and national
economic structure. These factors, and the extent to which they influence the
benchmarks, are estimated based on quantitative data and expert assessments. The
adjusted benchmarks are used to assess the marginal efficiency of met/hydro services,
with and without modernization.
The World Bank developed the sector-specific and benchmarking approaches to help
NMHS agencies provide understandable results to decisionmakers with limited time
and resources. However, these methods are severely limited in that they rely primarily
on expert opinion and data from other countries to determine the current level of
weather-related losses, the additional reduction in weather-related losses that
modernization would achieve, and the costs associated with mitigation options. Thus,
the results of the analysis are subject to potential biases and knowledge limitations of
the experts involved in the study. In addition, there is a limited amount of data
available to support expert findings. Despite these limitations, the World Bank finds
this method useful for providing order-of-magnitude estimates that help NMHS
agencies justify increasing public funds to support their services.
Several studies have used more detailed approaches to value the avoided costs
associated with the use of early warning systems for disaster management, including
the number of lives saved as a result of these systems. Economists often use the VSL to
estimate the monetary benefit of reducing premature mortality risk. For example, Ebi
et al. (2004) (see Appendix E, case study 3) determined that the use of early warning
systems during extreme heat events in the city of Philadelphia prevented 117 premature
deaths between 1995 and 1998. The dollar benefit of these prevented deaths was
estimated to be US$ 468 million, based on the EPA estimate of VSL at the time the study
was conducted.
When applying the VSL estimate, the key point is that a dollar value is not being placed
on any specific individual’s life per se. Instead, the values reflect information about
how individuals value modest changes in low-level risks of premature fatality. In other
words, VSL estimates represent WTP (or the willingness to accept) for small changes in
20
These figures represent the mean annual level of losses for a fairly long period of observations.
Losses for some specific year in some specific country may be well beyond the range given.
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very small risks that are spread over a large population. Currently, EPA recommends a
default central VSL of US$ 7.9 million (in 2008 United States dollars) to value reduced
mortality for all programmes and policies.
Avoided cases of illnesses can also be an important benefit associated with met/hydro
services (for example, heat-related illnesses and vector-borne diseases such as malaria
can be largely predicted based on climatic conditions). Willingness to pay to reduce
the risk of experiencing an illness is the preferred measure of value for morbidity
effects. As described in Freeman III (2003), this measure consists of four components:
–
Averting costs to reduce the risk of illness;
–
Mitigating costs for treatments such as medical care and medication;
–
Indirect costs such as lost time from paid work, maintaining a home and pursuing
leisure activities;
–
Less easily measured but equally real costs of discomfort, anxiety, pain and
suffering.
Researchers have developed a variety of methods to value changes in morbidity risks.
The three primary methods most often used to value morbidity are stated preference,
averting behaviour and cost of illness. Hedonic methods are used less frequently to
value morbidity from environmental causes (United States EPA, 2010).
Some methods measure individual WTP to avoid a health effect. Others can provide
useful data, but these data must be interpreted carefully if they are to inform
economically meaningful measures. For example, cost-of-illness estimates generally
only capture mitigating and indirect costs and omit averting expenditures and lost
utility associated with pain and suffering. Methods also differ in the perspective from
which values are measured (for example, before or after the incidence of morbidity),
whether they control for the opportunity to mitigate the illness (for example, before or
after taking medication) and the degree to which they account for all of the
components of total WTP.
6.5.4
Benefit transfer
Original studies to estimate stated preferences, avoided costs or other values
associated with the use of met/hydro services can require a significant amount of time
and financial resources. For this reason, researchers often use the benefit-transfer
approach to estimate these values. Bergstrom and De Civita (1999, p. 79) offer the
following definition of benefit transfer:
Benefits transfer can be defined practically as the transfer of existing economic values
estimated in one context to estimate economic values in a different context ... benefits
transfer involves transferring value estimates from a “study site” to a “policy site” where
sites can vary across geographic space and or time.
Chapter 6. Defining and measuring benefits
75
There are numerous challenges and cautions to consider when using benefit transfer.
While it is relatively simple to develop a benefit transfer-based monetary value
estimate of many types of benefits (for example, there is a relatively large amount of
literature on economic values for the impact of seasonal forecasting on agricultural
productivity), the approach can generate potentially inaccurate and misleading results,
even when a well-intentioned and objective analysis is being attempted. Obtaining
accurate and credible findings using the benefit-transfer method can be challenging in
that important differences often exist among the types of conditions studied in the
primary empirical research (that is, the study context for the published monetary
estimate) and the climate services context to which an NMHS may be trying to transfer
the results.
One such challenge is defining the appropriate “market” for the particular site. For
example, what are the boundaries for defining how many households are assigned a
benefit transfer-based value such as dollars per year to improve traveller safety?
Another challenge arises from the frequent need to attribute a benefit transfer estimate
to a large outcome (for example, avoiding a hurricane evacuation) using an estimate of
a fractional benefit to the whole (for example, the marginal mile of evacuation that was
avoided).
Despite these challenges, when implemented correctly with the recognition that the
estimates are not intended to be precise, benefit transfer is accepted as a suitable
method for estimating use and non-use benefits associated with climate services.
When time and resources allow, however, primary research specifically tailored to the
issue and site at hand is broadly considered a far better alternative.
There is a well-developed literature on how to correctly apply benefit transfer (for
example, Rosenberger and Loomis, 2003; United States Office of Management and
Budget, 2003; United States EPA, 2010). The following steps are recommended when
conducting benefit transfer (Lazo et. al., 2009; United States EPA 2010):
–
Describe the issue, including characteristics and consequences and the
population affected (for example, will impacts be felt by the general population
or by specific subsets of individuals such as users of a weather forecast product?);
–
Identify existing relevant studies through a literature search;
–
Review available studies for quality and applicability: The quality of the study
estimates will determine the quality of the benefit-transfer analysis. In assessing
studies for applicability, determine whether available studies are comparable to
the issue at hand. Guidelines for evaluating the usefulness of a particular study for
benefit transfer for a particular situation (based on guidance provided in United
States EPA, 2010) include:
–
Assess the technical quality of the study: The original studies must be
based on adequate data, sound economic and scientific methods and
correct empirical techniques;
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VALUING WEATHER AND CLIMATE:
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–
Ensure that the expected changes in site conditions are similar in
magnitude and type in the project being appraised and in those projects
from which the data are obtained;
–
Use studies that analyse locations and populations similar to those of the
project being evaluated if possible;
–
Carefully consider the cultural and economic differences between the
project location and the data source;
–
Transfer the benefit estimates: This step involves the actual transfer of benefits
over the affected population to compute an overall benefit estimate. The transfer
may simply involve applying a value to an average household as derived from a
primary study, or a more complex transfer of the benefits function derived
empirically by the original researchers. The transfer can also derive from a metaanalysis of multiple studies (see Box 6.4 for information on the different
approaches for transferring values from study cases to the policy case);
–
Address uncertainty: In addition to reporting the final benefits estimates from the
transfer exercise, the analyst should clearly describe all key judgments and
assumptions, including the criteria used to select study cases and the choice of
the transfer approach. The uncertainty in the final benefits estimate should be
quantified and reported when possible. Clearly describe all the judgments and
assumptions inherent in benefit transfer, as well as any other sources of
uncertainty and assess their potential impact on final estimates.
A limited number of published studies have used benefit-transfer techniques to
estimate values associated with climate services. Most notably, Hallegatte (2012; see
Appendix E, case study 4) estimated the potential benefits of providing early warning
systems in developing countries based on a study of benefits for similar services in
Europe. Taking into account differences in population, increased hazard risk due to
climate and geography, as well as increased exposure to weather due to the state of
infrastructure, the author estimated that upgrading early warning capacity in all
developing countries would result in between US$ 300 million and US$ 2 billion per
year of avoided asset losses due to natural disasters. In addition, it was estimated that
early warning systems would save an average of 23 000 lives per year (valued at
between US$ 700 million and US$ 3.5 billion per year using the Copenhagen
Consensus guidelines (Copenhagen Consensus Center, 2014)) and would add between
US$ 3 billion and US$ 30 billion per year in additional economic benefits.
Other studies have used benefit transfer to evaluate specific benefits. For example,
Weiand (2008) estimated the value of improved ocean observing data to recreational
fishermen in Florida using estimates of WTP for recreational fishing (per fish caught)
from existing literature. Costello et al. (1998) also used estimates from the literature to
determine the value associated with improved in-stream fishing in the United States
Pacific Northwest due to improved fishery (coho salmon) management with the use of
ENSO-based forecasts. Frei (2010) used benefit transfer to estimate the value for a
Chapter 6. Defining and measuring benefits
77
Box 6.4: Benefit-transfer approaches (United States EPA, 2010)
Unit value transfers are the simplest of the benefit-transfer approaches. They take a point
estimate for a unit change in value from a study case or cases and apply it directly to the
policy case. The point estimate is commonly a single estimated value from a single case
study, but it can also be the average of a small number of estimates from a few case studies.
Unit value transfers are useful for obtaining order-of-magnitude estimates of benefits, as
point estimates reported in study cases are typically functions of several variables, and
simply transferring a summary estimate without controlling for differences among these
variables can yield inaccurate results.
Function transfers also rely on a single study, but they use information on other factors
that influence value to adjust the unit value for quantifiable differences between the study
case and the policy case. This is accomplished by transferring the estimated function upon
which the value estimate in the study case is based to the policy case. This approach
implicitly assumes that the population of beneficiaries to which the values are being
transferred has potentially different characteristics, but similar tastes, to the original one and
allows the analyst to adjust for these different characteristics (United States Office of
Management and Budget, 2003).
Meta-analysis uses results from multiple valuation studies to estimate a new transfer
function. Meta-analysis is an umbrella term for a suite of techniques that synthesize the
summary results of empirical research. This could include a simple ranking of results to a
complex regression. The advantage of these methods is that they are generally easier to
estimate while controlling for a relatively large number of confounding variables.
Structural benefit transfer is a relatively new approach to benefit transfer that can
accommodate different types of economic value measures (for example, WTP, willingness to
avoid, or consumer surplus) and can be constructed in such a way that certain theoretical
consistency conditions (for example, WTP bounded by income) can be satisfied. This can be
applied to value transfer, function transfer, or meta-analysis; although applications to
function transfer are the most common. Structural transfer functions that have been
estimated have specified a theoretically consistent preference model that is calibrated
according to existing benefit estimates from the literature.
number of selected sectors (households, agriculture, energy) from weather services in
Switzerland to be in the region of hundreds of millions of United States dollars.
6.6
SOCIOECONOMIC BENEFIT STUDY STEP 6:
ANALYSE THE VALUE OF BENEFITS – QUALITATIVE
For some types of benefits, expressing their value in quantitative or monetary terms
may not be feasible or desirable. It is always important, though, to describe these
non-quantified benefits in a meaningful, qualitative manner. One way to do this, in
part, is by using a simple scale that indicates the likely impact on net benefits. For
example, an NMHS can qualitatively rank impacts on a five-point scale to reflect
non-quantified relative outcomes that span from relatively very small to very positive
(for example, a “1” may signify an outcome with small non-quantified benefits and a
“5” may represent a high level of non-quantified benefits). Qualitative ratings should
be accompanied by descriptions of the impact and should be explicitly carried through
the analysis.
78
6.7
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
CONCLUSIONS
This chapter describes the processes and methods that can be used to assess the
benefits of met/hydro services, including the general process for conducting benefit
analysis and methods and models used to quantify and monetize benefits. The
information provided in this chapter on the different approaches for estimating
benefits helps to provide a foundation for appropriately framing a benefit analysis.
There is a well-established toolkit of economic valuation approaches that can be used
to value non-market goods and services, including climate services.
When conducting benefit analysis, it may be necessary to apply several different
methods, particularly when conducting whole-of-service analyses. Different methods
often address different subsets of total benefits. In addition, the use of multiple
methods can provide for comparison of alternative measures of value when applied to
the same category of benefits. In many cases, NMHSs will not have the resources or
expertise to complete an original benefit study that relies on primary data collection
and/or extensive modelling. In these instances, benefit transfer can be a valuable tool
that can be used to provide reasonable estimates. “Double counting” is a significant
concern when applying more than one method, and any potential overlap should be
noted when presenting the results (United States EPA, 2010).
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frontier. Climate Research, 33:43–54.
United States Environmental Protection Agency (United States EPA), 2010: Guidelines for
Preparing Economic Analyses. National Center for Environmental Economics Office of Policy.
Washington, D.C.
United States Environmental Protection Agency Science Advisory Board, 2009: Web-accessible
materials on ecological valuation developed by or for the SAB Committee on Valuing the
Protection of Ecological Systems and Services (C-VPESS): Non-market methods – revealed
preference, http:/yosemite.epa.gov/sab/sabproduct.nsf/WebBOARD/C-VPESS_Web_
Methods_Draft?OpenDocument.
United States Office of Management and Budget, 2003: Circular A-4, https://www.whitehouse.
gov/omb/circulars_a004_a-4/.
von Grünigen, S., S. Willemse and T. Frei, 2014: Economic value of meteorological services to
Switzerland’s airlines: The case of TAF at Zurich airport. Weather, Climate and Society,
6:264–272.
Wieand, K., 2008: A Bayesian methodology for estimating the impacts of improved coastal
ocean information on the marine recreational fishing industry. Coastal Management,
36(2):208–223.
CHAPTER 7. DEFINING AND MEASURING COSTS
Chapter 1. Introduction
Chapter 2. Met/hydro services
Chapter 3. Purpose of SEB studies
Chapter 4. Designing SEB studies
Chapter 5. Economic essentials
Chapter 6. Benefits
Chapter 7. Costs
Chapter 8. BCA
7.1
INTRODUCTION
The concept of opportunity cost, introduced in
the previous chapter, provides the basis for
evaluating the resources used in the production
of met/hydro services. Most SEB studies will
include an analysis of costs to provide a basis of
comparison to benefits in order to inform
decisions on the net benefits of met/hydro
services. In addition, NMHSs may conduct
cost-effectiveness analyses to determine the
preferred investment option in providing a
specific type and quality of met/hydro service.
Chapter 9. Communications
This chapter provides a detailed discussion of
various cost terminology, covers the topics of
attribution and aggregation of costs, and
Chapter 10. Looking forward
examines different costing approaches that are
used in SEB studies. A basic understanding of cost types and terminology will help
NMHSs to more effectively develop SEB scopes, work with consultants, and
communicate SEB results to decisionmakers and other audiences. The chapter covers
SEB steps 3 to 6 in the 10-step approach (see Figure 4.2) for conducting a study.
7.2
CONCEPTS FOR DEFINING, MEASURING, ATTRIBUTING AND
AGGREGATING COSTS
This section presents different perspectives on how costs can be defined and
categorized. For many readers, terms such as costs, expenditures and outlays may
seem fully interchangeable, but there are important differences in their meanings.
Costs
Costs have already been defined in Chapter 5, but the concept is further detailed in this
chapter. Costs refer to the total amount of sacrifices made to accomplish a task or
produce a product or service. It can encompass purchased goods and services, labour
effort (working hours), use of goods from inventory, use of equipment, models and
buildings (capital stock) and use of public goods and non-monetized resources (for
example, the environment). Capital goods illustrate the distinction between
expenditure and cost. A capital good is purchased in one year and recorded as an
expenditure, but over time the capital good declines in quality or is depreciated and
this depreciation (often calculated as the initial cost divided by the capital good’s
expected useable life) is an annual cost.
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In organizations in which the basic tasks are funded from fixed annual budgets, there
is often a tendency to regard only efforts and purchases outside the basic task portfolio
as costs (that need commensurate extra funding from whatever source) or to regard
only purchases as costs. This supposition should be avoided in BCA. In BCA, either the
incremental cost or the total cost with respect to a considered bundle of services
should be included, regardless of whether these are covered from a basic budget or
from another source.
Expenditures
Expenditures refer to actual payments made with respect to the production of a good
or service during a certain time span. If a BCA only considers expenditures, not all costs
will necessarily be accounted for, either because some costs did not entail payments or
because costs were incurred outside the considered period. In practice there may also
be the inclination to only consider expenditures incurred by the organization in
producing met/hydro services, whereas the considered service production may also
entail expenditures elsewhere. For example, if purchases of an NMHS include
subsidized goods, the related costs of the government should be accounted as well.
The term “outlay” has the same meaning as expenditure.
Losses
Losses are another term closely related to costs. Losses are unintended costs; for
example, in case of damage to equipment or buildings. If the costs of production of a
good or service are not fully covered by revenues or by a budget, losses are incurred.
This means that somehow additional resources have to be found to compensate the
losses. Within an NMHS, it would mean that parts of a budget that were originally
allocated to other activities must be used to balance a loss.
7.3
SOCIOECONOMIC BENEFIT STUDY STEP 3:
IDENTIFY THE FULL RANGE OF COSTS
For the purposes of SEB studies, costs of met/hydro services can be distinguished
according to who incurs the costs. Regardless of whether met/hydro services are
provided to end users without charge, the society, that is, the national economy, incurs
cost when producing these services. These costs, inside the NMHS and elsewhere, have
to be identified. For met/hydro services, costs can be grouped by organizations
(NMHSs and commercial weather services) that produce basic and specialized services
and the various types of user communities that receive these services, process and
interpret the information and take decisions. User communities may include
individuals, households, businesses and other organizations. The costs incurred to
produce met/hydro services are familiar to NMHSs and commercial weather services,
but the costs of users may be significant and will need to be accounted for in BCA at
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Chapter 7. Defining and measuring costs
COMMUNICATION PROCESSES
Weather
Climate
Water
SERVICE PRODUCTION
Basic & specialized
services
Processing & data management
Weather/
climate/
water
Observations
Modelling
Forecasting
Service delivery
Research & development
NMHS & commercial
providers
User decisions &
actions
Outcomes
VALUEADDING PROCESSES
NMHS service production costs
Commercial weather service
provider costs
User costs
– Infrastructure investment
(especially observation
systems)
– Information retrieval and
processing (for example,
NMS, satellites)
– Information retrieval (and
data processing – for some
users)
– Observations and data
management
– Modelling and forecasting
– Interpretation of met/hydro
information
– Modelling and forecasting
– Product development and
research
– Information retrieval and
processing cost
(for example, satellites)
– Research and development
– Service delivery
– Service delivery
– Data management
– Infrastructure investment
(for some commercial
weather services)
– Modelling and
decisionmaking
– Costs of taking actions
based on met/hydro
information
Figure 7.1. Costs associated with the value chain
the national level. Figure 7.1 illustrates the types of costs that may be incurred by
producers and users of met/hydro services.
The listing in the table in Figure 7.1 provides a tentative idea of the prominence of cost
items (in descending order). However, due to diversity in – among others –
organizational status and size, product portfolio, and technological skill levels, costs
shares can vary appreciably within the groups of NMHSs and commercial weather
services, respectively.
Almost without exception, NMHSs have their own observation systems, implying the
need for investment and maintenance. The large amount of observation data added
every day requires advanced data management systems for NMHSs. Furthermore,
both commercial weather services and NMHSs acquire data from third parties, which
also incurs cost, even if the data as such are free. Both NMHS and commercial weather
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services incur costs for running forecast models. Both types of actors often also have
research and development activities, even though for NMHSs a more significant share
may go to research, whereas commercial weather services will spend a (much) larger
share on product development. Service delivery is important for NMHSs, but crucial for
commercial weather services. Most commercial weather services do not have a
significant amount of observation infrastructure, but some do. End users may incur
costs to retrieve and process information provided by NMHSs and commercial weather
services even if the information as such is free (see Figure 7.1).
National Meteorological and Hydrological Service and
commercial weather service costs
7.3.1
The costs associated with NMHSs and commercial weather services, listed in the table
in Figure 7.1, can be further differentiated according to the purchase of a variety of
goods and services, plus capital expenditures:
–
–
Labour (salary cost and additional cost of own employees), often subdivided into:
–
Direct labour (working hours clearly attributable to production tasks);
–
Overheads (labour in supporting services such as administration);
Purchased information services (for example, remote sensing and meteorological
data):
–
Fees for international cooperative bodies can be a significant share of the
total cost of NMHSs (for example, greater than 10%);
–
Purchased materials, energy, water, sanitation, and waste disposal services, fuel
for vehicles (typically consumed in one year);
–
Equipment and buildings/furnishings (for example, monitoring equipment,
communication equipment, computers and other IT equipment, vehicles, and the
like).
Next to overhead costs, which cannot be directly attributed to any productive activity,
there are so-called joint costs, which are attributable to a collection of productive
activities. Since joint cost is an important feature in NMHS costs, we will return to the
attribution issue in section 7.5.3. Other costs incurred during service generation, but
not observed by the NMHS, will be discussed in sections 7.5.4 and 7.5.6. Table 7.1 gives
an example of annual cost statements of the Royal Netherlands Meteorological Institute.
Usually, the production of any product or service entails both variable and fixed costs.
Variable costs vary according to the volume of production, whereas fixed costs remain
at the same level regardless of the output level. The classification is sensitive for the
period considered. For example, for periods up to a year, building costs are usually
constant. If, however, an entire project lifecycle is to be considered, some constant cost
items may show stepwise developments – for example, if an organization expands,
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Chapter 7. Defining and measuring costs
Table 7.1. Example summary of an annual cost statement of an NMS –
the Royal Netherlands Meteorological Institute (€ millions)
Cost items
2012
Staff
Material cost and services
purchased, of which:
2011
32.98
26.98
33.21
24.32
–Outsourcing
1.03
0.98
–Maintenance and
operations
4.03
4.28
– Rent and lease
3.36
3.29
–Contributions
(international)
13.07
12.00
–Remaining
5.49
3.76
Interest
0.28
0.21
Depreciation
2.75
2.32
62.98
60.05
TOTAL
Source: Royal Netherlands Meteorological Institute – Annual Report (2012)
building costs will rise by discrete levels. Similarly, the relation between variable cost
and production level may be more or less linear, but also non-linearity is possible – for
example, in the case that there are economies of scale in production. In meteorological
services there are also economies of scope, which means that the production of an
additional second type or new service has a lot of commonality in production.
7.3.2
User costs
User communities will incur similar types of costs as those of producers of met/hydro
services, particularly related to labour and purchased materials, energy, and the like.
Individuals and households using services may incur some of the same types of costs,
but on a smaller scale than businesses and other types of organizations. Businesses may
incur significant costs to take decisions based on met/hydro services. If the acquisition
and use of the information contained in a weather service product requires dedicated
equipment, labour effort and knowledge, these costs may deserve inclusion in the SEB
analysis of costs. For example, if favourable growing conditions are forecast, farmers
may decide to grow higher valued crops for which input costs are also higher than for
the crops they would grow in normal or drought years. Without the capacity to
respond to the forecast, the user would not be able to generate any benefit. This type
of cost is clearly more difficult to estimate than the costs to supply met/hydro services.
Another potentially large cost for users relates to access to met/hydro services. For
example, an internal assessment of road traffic weather service effectiveness in the FMI
covering the total annual cost of related media use in Finland was estimated at almost
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€ 1 million (Nurmi et al., 2013). The information content of weather services reaches
the users via a multitude of media channels. For individuals and households, some of
the mechanisms for accessing met/hydro services may be free (for example, radio,
television, specific displays in hotels and public places), while others may involve
quantifiable costs (for example, newspapers, SMS messages, cell phone and tablet
applications, e-mail subscriptions for tailored data and products). The charging for
access to information recently relates less to the public or private nature of the provider
and more to the degree to which the information is personalized or tailored to the user.
The business model of non-personalized media is based on advertisement income and
at times on annual subscription fees. For personalized media it is easier to charge a fee.
At the same time, a rise of new media use has been observed, with a higher share of
personalized delivery options (Elevant, 2010; Perrels et al., 2013a; Harjanne and
Ervasti, 2014).
Even if the services are available free of charge, their costs will be reflected in the costs
of the production and dissemination of this information by NMHSs, commercial
weather services, and television and radio stations. Where access to information is
available for a fee, there is the potential for double counting of these costs (incurred by
both the producer and user) and the analyst should avoid including the costs of
services incurred by users if accurate information is available on the costs of producing
and disseminating met/hydro services information and products.
There are other types of costs that should be identified even if they are not easily
quantified or are limited in magnitude. These might include:
–
Use of public goods (for example, use of state-owned land for observation sites
– within the government, access to these lands may be free of charge, but there is
an opportunity cost associated with the availability of these lands for these
purposes to the exclusion of others);
–
Opportunity cost of time for non-commercial users to acquire, learn how to
interpret and use met/hydro services information;
–
External costs – these are costs caused by certain actors imposed on other actors,
without the latter being compensated (sometimes a non-priced natural resource,
such as a river, functions as intermediate). The production of met/hydro services
usually do not generate external costs. However, the way that individuals,
households, or businesses respond to information could impose costs on others.
7.4
SOCIOECONOMIC BENEFIT STUDY STEP 4:
SCREEN COSTS AND SELECT THE ANALYTICAL APPROACH
The starting point in screening costs to be assessed in SEB studies is to recall the
purpose of the study as described in the study step 2. If the SEB study is focused on
whole of services, it will likely consider the full range of costs for providers and users
described in SEB study step 3. When the study concerns changes in existing services or
Chapter 7. Defining and measuring costs
87
new services, only the incremental costs to produce and disseminate the improved or
new services will be considered. For example, if an observation network is improved by
adding new stations, incremental costs may include construction costs, costs of new
monitoring and communication equipment, labour to operate and service new
stations and additional costs to manage the higher volume of monitoring data.
While this may be a straightforward budgeting exercise for the NMHS or commercial
weather services, estimating incremental costs for user communities can be quite
challenging because the analyst must understand the types of actions that will be
taken by users and the scale of use of the improved or new service. The estimation of
incremental user costs will often require the analyst to make assumptions about user
decisions and uptake of the improved/new services and possibly consider a range of
assumptions in sensitivity analysis performed once benefits and costs have been
evaluated and compared (see Chapter 8).
For most cost items, estimates can be made of per-unit costs of the element; for
example, the unit cost of labour (per hour, day, or the like). When the total production
costs and output volume (for example, number of warnings of a given type) are
known, the unit costs of a certain service can be established. The unit costs may serve
as a basis for establishing a charge for that service. If costs and output are not 100%
proportional, the unit cost will change when the level of output changes, and therefore
one should be cautious when a charge is based on the unit cost. The unit cost of the
service can also be regarded as the average cost of that service.
7.5
SOCIOECONOMIC BENEFIT STUDY STEP 5:
ANALYSE THE VALUE OF COSTS – QUANTITATIVE
Some economic studies require more precise estimations of costs than others,
depending upon the questions to be answered by the analysis. Studies that are applied
at a high aggregation level or that are of an explorative nature usually do not require a
high precision of costs. With regard to justification of investments, the need for
precision increases when the decisionmaking proceeds towards well-specified concrete
alternatives. If accounting systems are adequate, precision should not create major
problems in case of retrospective studies. In the case of acquisition of new equipment,
due attention should be paid to maintenance costs in addition to the initial investment
cost and expected performance level.
The challenge is to arrive at an acceptable representation of the costs of the selected
met/hydro service(s) at each production or delivery link in the value chain. Since some
costs may be shared with other service products or even with the entire organization,
the locally mandated accounting system will determine in part how precisely costs can
be allocated to selected services. Also the way state-owned facilities, such as office
buildings, are charged – if at all – to public organizations affects the costing picture.
The legal status of an organization affects the way costs are reported. Private
companies with share capital have to follow international and national rules on
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accounting practices. Public organizations are subject to national rules on accounting
in public organizations, while European Union regulations (or those of other
transnational agreements) may also affect accounting practices of public organizations.
For example, in many countries the cost of public sector products within an NMHS is
assumed to be “competition neutral”, meaning that it should exactly reflect the costs
of the efforts made to produce the public sector product and avoid overstating or
understating of joint costs (see section 7.5.3).
7.5.1
Treatment of capital costs
In many public sector organizations, capital investments are budgeted as a one-off
cost, that is, the acquisition is paid for in the first year. In this case, no capital
accounting is applied and as a consequence there is no depreciation (reflecting the
aging and upcoming need for renewal of equipment). As acquisitions are funded from
the annual budget, the SEB analyst has to decide whether depreciation should still be
reflected in the assessment or instead the actual budget cash flow should be presented
in the cost calculation (see Box 7.1).
The capital stock can be valued in different ways. Common approaches are historical
cost (that is, the original purchase cost) and replacement cost (the amount needed to
replace the equipment by a current up-to-date version). Similarly, stocks can be valued
in different ways, for example, based on the average value or based on the historical
values when bought, or based on current or expected prices. The choice of the
valuation base depends firstly on the available accounting data, but also on the
purpose of the study (investment appraisal or judging past performance), and on
methodological choices in the BCA (Chapter 8).
7.5.2
Treatment of prices
It is common practice in socioeconomic valuations to correct for inflation. In other
words the analysis is often carried out in real prices. The uncorrected (inflated) prices
are called nominal prices. The use of real prices means that all costs (and benefits) are
expressed according to a price level of one particular base year – usually referred to as
constant prices adjusted to a specific, typically recent year. Correction for inflation is
not the same as discounting towards a certain base year (see Chapter 8).
In forward-looking valuations, including investment appraisal, real prices are also used.
Apart from more detailed investment appraisal, forward-looking valuations can often
simply assume away inflation and apply constant prices. However, in countries where
high inflation rates and/or notable differences in inflation rates between product
groups are assumed to persist, it is better to start with nominal prices.
The inflation rate is also relevant for the financing cost of new equipment, when
funded by a loan or from a reserve (a kind of accumulated savings), which otherwise
– in principle – could produce a yield. A loan means that the debt gets smaller in real
terms, when there is inflation. Furthermore, in the case of a fixed long-term nominal
89
Chapter 7. Defining and measuring costs
interest rate, inflation may imply that the real interest costs are low or are decreasing
over time. Short-term nominal interest rates tend to follow the inflation rate.
If a part of NMHS costs are due to purchases or service fees abroad, the behaviour of
the exchange rate can significantly influence the costs. In principle the same applies to
revenues, but generally, for most NMHSs, sales abroad tend to be much smaller than
purchases abroad. If the national currency depreciates, the costs of purchases abroad
increases for the NMHS. Some countries with heavily regulated foreign exchange
practices may also apply differentiated exchange rates. Variation in exchange rates
constitutes a risk over and above other cost overrun risks of investment projects.
Box 7.1: Assessing the costs of a new observation network in Nepal
The capacity-building project for the Nepalese Department of Hydrology and Meteorology,
funded by the Finnish Ministry of Foreign Affairs, required a preliminary appraisal of the
costs and benefits of modernizing the observation system. This project included installing
101 automated observation stations and three Doppler radars over the course of nine years.
The summary of the cost build-up is shown below. During the project, it was emphasized
that the network would need maintenance, including recalibration, as well as more support
for data processing services. Both activities would require notable and lasting labour input,
as is shown in the table. Labour cost data and labour force requirements were established in
cooperation with the Nepalese Department of Hydrology and Meteorology. For the
depreciation of the equipment (in NPV), a lifetime of 10 years is assumed. The costs are
expressed in constant prices of 2011. The procedure to calculate NPV is explained in
Chapter 8.
Preliminary cost assessment of modernization of the Nepalese Department
of Hydrology and Meteorology (millions of Nepalese rupees)
2013 2014 2015 2016 2017 2018 2019 2020 2021
Operational costs
Met services
1.08
1.62
2.16
2.70
2.70
2.70
2.70
2.70
2.70
Maintenance
0.75
1.19
1.31
1.44
1.59
1.76
1.93
2.23
2.53
Data management
0.54
0.81
1.08
1.35
1.35
1.35
1.35
1.35
1.35
Total operational costs
2.4
3.6
4.5
5.5
5.6
5.8
6.0
6.3
6.6
Number of stations
5
17
29
41
53
65
77
89
101
Annual number of new
stations
5
12
12
12
12
12
12
12
12
25
60
60
60
60
60
60
60
60
Total investment costs
25
60
160
60
160
60
160
60
60
Depreciation costs
2.5
8.5
24.5
30.5
46.5
52.5
68.5
74.5
80.5
Investment costs
Automatic stations
Radars
Source: Perrels (2011)
100
100
100
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7.5.3
Attributing joint costs
Joint costs refer to costs made for facilities, which are serving multiple weather
information production chains. Examples include the costs of the weather observation
system, costs of weather data processing and modelling, costs of maintenance services,
costs of buildings and of general supporting staff (for example, administration,
catering, transport, and the like). Joint costs are an important feature in the costing of
weather, climate and hydrological services.
Fees for international cooperative bodies (such as the European Organization for the
Exploitation of Meteorological Satellites) are a special kind of joint cost, as the fee may
also reflect a member country’s ability to pay and/or reciprocity regarding both the use
and supply of data. The total costs for an NMHS for all these international cooperative
bodies together can be significant. For example, according to the financial statement
of 2013 of FMI, a share of 6% (approximately € 4.5 million) of the total budget was
allocated to these costs. This cost item can be treated in the same way as other joint
costs.
Joint costs constitute an important characteristic in the cost structure of met/hydro
services. A significant part of the overall costs of basic services has to do with the
observation system, data processing and basic (multi-purpose) modelling, of which
the output is serving many products of the NMHS directly or indirectly. On top of that,
there are the typical overhead costs related to administration. Cost attribution can be
based on:
–
Volume flows (share in the number of messages, maps, and the like);
–
Value flows (share in direct costs);
–
Expected profit contribution;
–
Cost carrying capacity (that is, a compromise solution which aims to minimize
effects on service product use across a portfolio of information products); it may
also be related to welfare maximization of the supply of a collection of weather
services (“Ramsey pricing”).21
The allocation of joint cost can be based on operating hours of certain services, on
some kind of generalized output unit, on the share of direct total costs of an activity as
part of all direct costs of a department or service package, or on the share of value
added for a particular service. The first two attribution approaches can be calculated
21
Ramsey pricing is a pricing policy used to determine prices charged by monopolistic firms or
public service providers, such as telecommunications or met/hydro services. Rather than a
government requiring providers to charge only the marginal cost of their services, which may not
be financially feasible due to economies of scale, joint costs, and other issues, when Ramsey pricing
is applied individual service prices are raised above marginal cost based on the service’s price
elasticity of demand. Price increases over the marginal cost are lower for services with more elastic
demand, and higher for services with more inelastic demand (also called the inverse elasticity
rule). This approach seeks to maximize social welfare without diminishing the financial well-being
of the relevant firm or service provider (Oum and Tretheway, 1988).
Chapter 7. Defining and measuring costs
91
Box 7.2: Analysing costs to improve efficiency in Haiti
Met/hydro services in Haiti are currently fragmented across several institutions in charge of
collecting, storing, processing, analysing and disseminating data. These include the
National Center for Meteorology, the National Service for Water Resources, the National
Observatory on Environment and Vulnerability, the National Center for Geographical and
Spatial Information and the National Coordination for Food Security. With support from a
number of partners including the World Bank Group, WMO, the Inter-American
Development Bank, the European Union, USAID and the United Nations Development
Programme, the Government of Haiti is aiming to reform, strengthen and user focus the
weather, climate and hydrological services. As a component of the World Bank Group’s
investment analysis, it was determined that by consolidating the currently disparate
observation systems into a coherent national network, optimization would lead to reduced
operations, maintenance and data management costs. With current network operations
constituting some 85% of total costs, reducing these even by a limited degree will have a
substantial impact on cost efficiency. While the value of services will also be increased, it was
recognized that without financial planning to adequately cover annual operations and
maintenance costs (which are in fact greater than the network’s capital value), the impacts
of reform and investment will not be sustained (World Bank, forthcoming).
Similarly, cost assessment can also reveal economic efficiencies to be gained through
regional cooperation. For example, through cross-border data sharing, technology transfer
and capacity-building in the Mekong River Basin, individual NMHSs such as the Lao People's
Democratic Republic Department of Meteorology and Hydrology could reduce investment
needs for modernization by up to 40% (World Bank et al., 2013).
rather straightforwardly; for example, a particular joint cost item may represent an
input to four different types of warnings. For a volume flow-based approach, cost is
attributed to each type of warning as a simple proportion of the number of warnings,
or adjusted if one or more warnings would likely involve a smaller or larger share of
inputs and costs. A value-based attribution is similar, but depends on the relative cost
share of each type of warning included in total costs. The latter two approaches,
expected profit contribution and cost carrying capacity, require more elaborate
background work.
7.5.4
Assigning prices to public goods and subsidized goods
For all costs, the first option is to use observed prices for purchases and reported costs
for labour. However, if products are subsidized, the actual costs to society are higher
than the observed price. Examples relevant for service chains are energy and the
shared use of land. The difference between the paid charge and the actual market price
(or a realistic estimate of the opportunity cost) should be added to the social cost of the
met/hydro service chain.
The co-use of land is quite often a contentious issue in the costing of meteorological
and hydrological observation networks in as far as observation stations are located on
land owned by a third person. In this case, it is helpful to recall the opportunity cost
principle introduced in Chapter 5. If the owner of the land has arguably valuable
alternative use opportunities for the land parcel used for observations, compensation
for foregone value may be justified.
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Another phenomenon is cross-subsidization. This may mean that an organization is
using surplus income from sales in a certain product group to compensate for losses in
another product group. Cross-subsidization may be observed when (a) a supplier can
charge high prices for certain products when there is no competition, and/or (b) a
supplier is allowed to apply (joint) cost attribution in a way that allows keeping prices
for some products quite low, while raising those of others.
7.5.5
Opportunity costs of public funds
If new services require significant investments, the method of financing the
investments can also affect the eventual cost to society and must be considered.
Financing frameworks can affect (a) the time profile of funding and payback period of
a project; (b) the applicable interest or discount rate; (c) the opportunity cost of public
funds. The time profile and the applicable discount rate are not cost items per se, and
depend on many organizational and institutional characteristics of the project – the
NMHS, the ministries involved and the credit rating of the country. The third factor, the
opportunity cost of public funds, is relevant if a new project implies an additional claim
on public finance resources. A government can fund additional public expenditures by
a loan, by raising taxes and by raising non-tax revenues such as royalties from mining.
All these options will affect a country’s macroeconomy and thereby result in costs to
society. A loan means that interest has to be paid, and if taxes are not raised this may
mean that some other part of the state budget has to be reduced. If the investment is
truly productive, tax revenues will go up in the long run and thereby the reduced
budget segment can be recouped. Yet, at least temporarily, the loan has a negative
effect on the macroeconomy. Furthermore, if the government is already heavily
indebted, interest rates may go up, which would harm the economy in general. Extra
taxation generally reduces economic growth. Raising non-tax revenues, such as
royalties, is in principle the least harmful for a country up to the point where companies
would start to rate the resulting profitability as too low. The acknowledgement of the
opportunity cost of public funds should not be understood as a general plea against
raising public revenue. Publicly funded services such as basic schooling and health care
increase welfare. Nevertheless, the opportunity cost of additional public revenue
raising merits being weighed against what it may reduce elsewhere in the economy.
Altogether the opportunity costs of public funds are rated as being quite high, both in
Organization for Economic Cooperation and Development (OECD) countries (Massiani
and Pico, 2013) and in developing countries (Auriol and Walters, 2012), in which a
given sum spent in public funding may demand a multiple of 1.2 or 1.3 of that sum (or
more) from the economy. The cited authors warn in both cases, however, that these
are multi-country and multiannual averages. Country- and project-specific estimates
may result in quite different estimates (both up and down). Opportunity costs are high
within the public sector, especially in developing countries. Even though BCRs are
often high for improvements in meteorological services of developing countries
(World Bank, 2008; Perrels et al., 2013b), they are equally high when spent on public
health care, sanitation or basic education. In other words, the opportunity cost of
public funds is one reason that a BCR well above 1 is necessary to attain support for
higher expenditure/investment levels (see Chapter 8).
Chapter 7. Defining and measuring costs
7.5.6
93
Substituting capital for labour (automation)
Modernization usually brings about significant changes in the type and amount of
labour used as well as in the relation between labour and capital. In the long run, such
modernization generates significant extra benefits for the society at large, but there may
be social costs to be accounted for as a result of changes in the types of labour required
and the locations where labour is situated. For example, a transition from labourextensive to automated observation systems will likely eliminate jobs requiring less
skilled labour in rural areas, and replace them with fewer, higher skilled jobs in central
locations. Thus, the modernization of the NMHS and its employment consequences fits
into a larger picture of urbanization in developing countries and a concomitant
migration flow from rural to urban areas (see, for example, Revi et al., 2014).
The transition of manual weather and hydrologic observation stations to automated
ones implies a significant loss of paid work for station assistants, unless the assistants
are re-educated for other tasks or quickly find other work of at least equal pay. So far,
this aspect is not, or is minimally, discussed in socioeconomic project assessments of
modernizations of NMHSs. Within the scale of NMHS projects, it seems nevertheless
justified to pay attention to this potentially significant socioeconomic effect, even if it
diminishes after several years.
To meaningfully represent the employment effects as costs in a socioeconomic
valuation, it should become clear to what extent:
–
Employees lose their jobs (without quickly finding employment with
comparable pay);
–
Employees are offered other jobs (with differentiation in possible income losses);
–
Employees are trained for new jobs and tasks (in the NMHS);
–
New jobs are created (with differentiation by skill and wage level);
–
Decrease and increase of employment in the NMHS is spatially segregated.
And also:
–
The estimated duration of unemployment;
–
The average level of the (monthly) unemployment benefit paid out by the state or
local authority or another semi-public agency. Also early retirement schemes and
lay-off compensations paid by the NMHS should be considered, if clearly related
to the project.
Eventually the societal cost of employee redundancy can be represented in terms of the
cost to public funds of (a) unemployment fees paid out (n persons × m months × fee
level); (b) early retirement schemes (n persons × y years × pension); (c) re-schooling
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costs. An alternative approach is to assess the sum of all incurred (net) income losses
attributable to the project.
7.5.7
Uncertainty
Even though uncertainty is usually a larger problem for the valuation of benefits, cost
figures can be uncertain as well. Investment costs tend to be underestimated. Also the
opportunity costs (see section 7.5.5) of public funds can be mentioned, as these
cannot be assessed precisely. Furthermore, in the case of a long-term project, changes
in technology, regulations and in the labour market typically introduce uncertainty in
the cost estimates. A typical solution is the use of sensitivity analysis, by deviations
based on historical observations (for example, +/- 15%). The latter type of margin can
also be obtained through an expert elicitation process such as a Delphi approach. For
truly large projects a scenario approach could be chosen, for example, exploring
different extents and timetables of deployment in conjunction with different evolutions
in the foreseen use of the new services.
7.6
SOCIOECONOMIC BENEFIT STUDY STEP 6:
ANALYSE THE VALUE OF COSTS – QUALITATIVE
For some types of costs, expressing their value in quantitative or monetary terms may not
be feasible or desirable (as per the screening in SEB study step 4). It is always important,
though, to describe these non-quantified costs in a meaningful, qualitative manner.
One approach involves the specification of a simple scale that indicates the likely
impact on net project costs. Impacts can be qualitatively ranked on a 5-point scale,
ranging from –2 to +2, to reflect unquantified relative outcomes that span from very
negative to very positive (for example, a “ –1” may signify an outcome with moderate
unquantified costs and a “ + 2” may represent a high unquantified cost). Qualitative
ratings should be accompanied by descriptions of the impact and should be explicitly
carried through the analysis. For costs or benefits that may have a significant positive
or negative effect on decisions on the net benefit of a project, additional analysis could
be taken to better characterize or even quantify those impacts. For instance,
non-market valuation techniques (stated preference), stakeholder interviews, or expert
elicitation (for example, through Delphi consultation rounds or group elicitation and
decision support systems), may help to shed further light on the societal significance of
the cost effect. Chapter 8 presents more information on those methods.
7.7
CONCLUSIONS
The identification and quantification of costs of met/hydro services production and
dissemination is in general familiar to NMHSs and commercial weather services and
thus relatively easy to undertake in an SEB analysis. Nevertheless, the analysis of costs
Chapter 7. Defining and measuring costs
95
provides challenges related to the treatment of investment costs, joint costs, public
and/or subsidized goods or services, and the treatment of costs related to, for example,
the automation of certain aspects of met/hydro services delivery such as observations.
User costs, especially when SEB studies focus on ex-ante assessments of improved or
new products, can be particularly challenging and may require the analyst to make
assumptions about user responses that can be carried forward to sensitivity analysis of
benefit–cost results.
REFERENCES
Auriol, E. and M. Walters, 2012: The marginal cost of public funds and tax reform in Africa.
Journal of Development Economics, 97(1):58–72.
Elevant, K., 2010: Social Media and Weather Surface Observing Technologies and Systems: Expanding
the Synoptic Network Through Web 2.0. WMO Technical Conference on Meteorological and
Environmental Instruments and Methods of Observation, Helsinki, 30 August–1 September.
Harjanne, A. and T. Ervasti, 2014: Analysis of user trends and behaviour in online and mobile
weather and climate services. FMI reports No. 2014/10. Helsinki, Finnish Meteorological
Institute.
Massiani, J. and G. Pico, 2013: The opportunity cost of public funds: Concepts and issues. Public
Budgeting and Finance, 33:96–114.
Nurmi, P., A. Perrels and V. Nurmi, 2013: Expected impacts and value of improvements in
weather forecasting on the road transport sector. Meteorological Applications, 20:217–223.
Oum, T.H. and M.W. Tretheway, 1988: Ramsey pricing in the presence of externality costs.
Journal of Transport Economics and Policy, 22(3):307–317.Perrels, A., 2011: Social economic
benefits of enhanced weather services in Nepal. Report for the Finnish Nepalese Project
(FNEP), commissioned by the Ministry of Foreign Affairs.
Perrels, A., A. Harjanne, V. Nurmi, K. Pilli-Sihvola, C. Heyndricx and A. Stahel, 2013a: The
contribution of weather and climate service innovations in adaptation to climate change
and its assessment. Report for deliverable 2.2. ToPDAd Consortium.
Perrels, A., T. Frei, F. Espejo, L. Jamin and A. Thomalla, 2013b: Socio-economic benefits of
weather and climate services in Europe. Advances in Science and Research, 1:1–6.
Revi, A., D.E. Satterthwaite, F. Aragón-Durand, J. Corfee-Morlot, R.B.R. Kiunsi, M. Pelling, D.C.
Roberts and W. Solecki, 2014: Urban areas. In: Climate Change 2014: Impacts, Adaptation, and
Vulnerability. Part A: Global and Sectoral Aspects (C.B. Field, V.R. Barros, D.J. Dokken, K.J.
Mach, M.D. Mastrandrea, T.E. Bilir, M. Chatterjee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B.
Girma, E.S. Kissel, A.N. Levy, S. MacCracken, P.R. Mastrandrea and L.L. White, eds.).
Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental
Panel on Climate Change. Cambridge, Cambridge University Press.
World Bank, 2008: Weather and Climate Services in Europe and Central Asia: A Regional Review.
World Bank working paper No. 151. Washington, D.C.
———, forthcoming: Draft project appraisal document – Strengthening Hydro-Meteorological
Services project. Washington, D.C.
World Bank, World Meteorological Organization and United Nations Office for Disaster Risk
Reduction, 2013: Country Assessment Report for Lao PDR: Strengthening of Hydrometeorological
Services in Southeast Asia, http://www.unisdr.org/files/33988_
countryassessmentreportlaopdr[1].pdf.
CHAPTER 8. BENEFIT–COST ANALYSIS
Chapter 1. Introduction
Chapter 2. Met/hydro services
Chapter 3. Purpose of SEB studies
Chapter 4. Designing SEB studies
Chapter 5. Economic essentials
Chapter 6. Benefits
Chapter 7. Costs
Chapter 8. BCA
Chapter 9. Communications
Chapter 10. Looking forward
8.1
INTRODUCTION
Benefit–cost analysis is a method for comparing
the benefits and costs of a project, programme
or investment over time and determining
whether or not it improves or diminishes societal
well-being. This economic information can then
be considered as one of several factors that will
help NMHSs or funding authorities take funding
decisions on met/hydro services. Benefit–cost
analysis involves a systematic appraisal of a
programme (whole of services or specific met/
hydro services) in order to quantify the full
range of social, economic and environmental
benefits and costs in monetary terms. The
analysis can also be used for choosing among
alternative approaches to achieving programme
goals.
Building on concepts introduced in Chapter 5, Chapter 8 provides an expanded
discussion of BCA decision criteria and the selection of discounting rates. Following
this discussion, the remainder of the chapter focuses on SEB study steps 7, 8 and 9 in
conducting an economic analysis (see Figure 4.2).
The primary reason for undertaking a BCA is to implement an accepted and unbiased
economic analysis that considers all of the positive and negative impacts (characterized
as benefits and costs) of a planned or potential investment or planned expenditure to
support decisionmaking. In some countries or jurisdictions a BCA may be required by
law for evaluating investments exceeding a certain financial threshold. Such an analysis
can also be used as a framework for understanding and fully articulating those benefits
and costs using a systematic approach that helps the analyst identify uncertainties and
biases about the impacts of an investment.
8.2
BENEFIT–COST ANALYSIS CONCEPTS
8.2.1
Benefit–cost analysis decision criteria – Net societal benefit
For evaluating policy options, the fundamental principle of BCA is “choose the
alternative with the greatest net societal benefit”. This must include the possibility of
“doing nothing” or not implementing any project in the case where the costs
outweigh the benefits for the investments under consideration. Two key questions in
implementing this principle are (a) what does “net societal benefit” mean, and
(b) how do NMHSs measure it?
Chapter 8. Benefit–cost analysis
97
Net societal benefits
Net societal benefits are generally defined as the total benefits minus the total costs.
But as discussed in the theory of economic valuation, benefits and costs are
measurements of underlying utility at an individual level and thus aggregating to a
societal level requires relating changes in welfare across all individuals. This presents a
quandary as it is fundamentally impossible to measure utility changes on the same
scale across all individuals (utility is subjective and means something different to each
individual). Therefore, BCA proposes and uses rules for aggregating utility changes
across individuals.
The rule used initially for BCA stated that the programme improves the welfare of
society if it makes at least one person better off and no one worse off. This approach is
unfeasible because there are very few programmes that leave no one worse off (for
example, in the case of meteorological programmes paid for through taxation, some
tax payers may be worse off if they never use meteorological information yet are still
taxed in part to pay for met/hydro services). A more operational decision rule states
that a programme has positive net benefits if the gainers could compensate the losers
and still be better off. This rule is often called the Kaldor-Hicks compensation test.22
This rule does not require that compensation should actually be made to losers, but
only that the net benefits would be positive even if losers were compensated for their
losses.
Criticisms of the use of BCA for decisionmaking when some individuals lose and others
gain are usually related to ethical issues about the aggregation and comparison across
individuals – or distributional issues. Building on results from BCA, policymakers quite
often balance societal and distributional considerations beyond those captured in a
BCA. Recognizing that BCA may only be one part of the decisionmaking process, it is
important to explain the approach commonly used during the analysis. This focuses on
the summation (adding up) of benefits and costs across the time frame of the
programme and thus involves a process called “discounting”.
8.2.2
Selecting the discount rate
As discussed in section 5.6, the benefits and costs of providing met/hydro services
often vary from year to year. The discount rate is used to adjust these uneven future
streams to the present to facilitate calculation of PVs to account for inflation and rate of
time preference between the present and future magnitudes. This section provides a
brief discussion of the process of selecting a discount rate to use in SEB studies.23
22
See Just et al. (1982) for a discussion of the Kaldor-Hicks compensation test, also known as the
Kaldor-Hicks compensation principle.
23
Some of the concepts and decisions related to the discount are technical issues critical to
undertaking a valid BCA and may require further guidance from governmental or policy
authorities or qualified economists. This is especially true for very long time horizons such as may
be involved with climate change decisionmaking. See, for instance, Goulder and Williams (2012).
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Economic theory suggests that in a world with no inflation, no taxes, no financial
transaction costs, and zero risk, there would be a clear signal about what discount rate
to use. If consumption today came at the expense of investments in the future, the
opportunity cost of capital should be used to discount the stream of future benefits
and costs. In that case, the discount rate should be equal to the rate of return that
could be earned by investing the money. For example, if inflation is expected to be 4%
in the future, and there is a 3% risk-free real return on capital, the real discount rate
would be 3% and the nominal discount rate would be 7% (3% + 4%). But if the use of
funds or resources today predominantly displaces future consumption (instead of
investments), a social rate of time preference will be more suitable as the discount rate.
There are often regulatory and other practical aspects to the choice of discount rate,
and economists and policymakers do not always agree about the correct discount rate
to apply to project valuations. For BCAs of NMHSs, which are generally investments
made for broad public benefit, it may be most appropriate to use a real, net-of-tax,
social rate of time preference as a real discount rate to convert all values to their present
worth. But justifications can be made for a range of rates, from a zero discount rate to a
rate that reflects the private costs of capital.
Some argue for a zero discount rate, believing that discounting underestimates project
benefits or costs that may occur far into the future (affecting future generations), or
that include irreversible outcomes (for example, species extinctions). In a highly
publicized British Government study (The Economics of Climate Change: The Stern Review
(Stern, 2007)) the author argues for powerful and urgent actions to mitigate climate
change, such as carbon pricing, on the premise that the future economic costs of
unabated climate change (roughly 5% of global GDP annually) will far exceed the costs
of climate change mitigation actions in the present (roughly 1% of global GDP
annually). Importantly, his calculation is based on using a discount rate of just 0.1%,
which places virtually equal value on costs and benefits accruing to both present and
future generations.
Some leading economists, such as W.D. Nordhaus of Yale University, dispute the use of
such a low discount rate, arguing that it is not consistent with current market place real
interest and savings rates, and thus cannot be used to justify the high level of climate
change mitigation expenditures proposed by Stern (Nordhaus, 2007).
Similar to Nordhaus, many economists suggest that the discount rate should reflect
prevailing interest rates on low-risk bonds, because such risk-free, net-of-tax rates best
reflect the rate of social time preference. This might be reflected by the real cost of
capital to municipal agencies in raising capital through bonds, or by the cost of longterm federal government bonds. Some advocate using the private cost of capital,
believing that the project’s funds might be otherwise invested in private ventures, and
that therefore, this measure reflects the true opportunity cost.
Due to differing viewpoints on the correct discount rate and how it should be best
calculated, discount rates tend to vary widely among different countries and lending
institutions. Zhuang et al. (2007) surveyed the discount rates used for public projects
in 14 countries around the world, finding rates as low as 2%–3% in developed nations
Chapter 8. Benefit–cost analysis
99
such as the United States and Germany, and as high as 12%–15% in developing
countries such as Pakistan and the Philippines.
Multilateral development banks also apply variable discount rates that generally tend
to fall more closely in line with the higher rates used in developing countries. The
World Bank provides guidance on calculating the discount rate in its Handbook on
Economic Analysis of Investment Operations (Belli et al., 1998). The Bank notes that it has
traditionally used a notional discount rate of 10%–12%, but its task managers may use
a rate outside this range as long as it is justified in the country assistance strategy.
The Asian Development Bank specifies its discount rate policy in its Guidelines for the
Economic Analysis of Projects (Asian Development Bank, 1997). Similar to the World
Bank, rates used at the Asian Development Bank may vary across sectors, countries and
timescales, but tend to be 10%–12% at minimum. The other major multilateral
development banks (the Inter-American Development Bank, the African Development
Bank and the European Bank for Reconstruction and Development) also tend to use
rates in the range 10%–12% (Zhuang et al., 2007).
There is a broad and growing literature on appropriate discount rates and functional
forms to use for discounting that are especially relevant to long-term decisionmaking
(for example, intergenerational decisions, as may be relevant to climate change issues).
This publication does not examine that literature but readers may find the following
papers of interest: Aalbers (2009); Gollier and Weitzman (2009); Baum and Easterling
(2010); Weitzman (2012).
8.3
SOCIOECONOMIC BENEFIT STUDY STEP 7:
SUMMARIZE AND COMPARE ALL BENEFITS AND COSTS
Following SEB study steps 5 and 6 (discussed in Chapters 6 and 7), the analyst has all
the quantitative and qualitative information on the stream of costs and benefits that
have been estimated for the change in met/hydro services. Step 7 involves two distinct
calculations. First, all costs and benefits must be adjusted and aggregated into PV
terms employing a discount rate specified in regulations or agreed to by the NMHS
and government decisionmakers. Second, the analyst will compare the two PV terms,
typically by applying the net benefits or the BCR decision criterion. This section
provides detailed discussion of the development of PV sums and the comparison of
quantified benefits and costs, followed by discussions of qualitative benefits and costs,
and distributional issues.
8.3.1
Net present value and project decision criteria
Most investments or planned expenditures will involve costs that vary from year to year
and an uneven stream of benefits. Whether a single investment, or multiple
investments with varying temporal profiles of costs and benefits are to be evaluated,
the discount rate is used to adjust future values to the present to determine the
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investment’s PV of costs and benefits. If both benefits and costs are involved, the NPV
of the investment is determined by subtracting the PV of the costs from the PV of the
benefits. If the NPV of a project is greater than zero, the PV of the benefits is greater
than the PV of the costs. The NPV of different projects can be compared if they are
adjusted to a standard monetary basis, for example, 2010 United States dollars.
Assessment of NPV of different projects allows direct comparisons of project values
regardless of possible differences in the timing of benefits and costs for each project.
The Kaldor-Hicks compensation test can be stated in NPV terms: if the NPV is positive,
the project is acceptable and should be undertaken; if the NPV is negative, it does not
provide an improvement in societal well-being and should not be pursued.
Table 8.1 presents a simplified numerical example of discounting and calculation of
NPV. The dollar values for benefits and costs shown are entirely made up for illustrative
purposes only to show the impact of the use of different discount rates. The first
column indicates the year during which benefits and costs are projected to occur. The
next two columns under the heading “Discount rate = 0%” indicate the temporal flow
of annual benefits and costs estimated at the current year dollar. Implicitly presenting
these as undiscounted is the same as using a discount rate of 0%. Then, the discounted
benefits and costs for each year are shown using discount rates of 3% and 7%,
respectively. These are calculated using the following formula for benefits:
PV benefitst =
Bt
(1 + r )t
where PV benefits is the PV of the benefits from year t, B is the dollar value, and r is the
discount rate. For instance, referring to Table 8.1, using the PV of year 5 benefits using a
discount rate of 3% is:
PV benefitst =
50
(1 + 0.03)5
=
50
1.1593
= $ 43.13
The PV of costs in year t (PV costs) is calculated using costs, C, rather than benefits:
PV costst =
Ct
(1 + r )t
In Table 8.1, the total discounted value of benefits and costs are summed and recorded
in the row “Total PV”. The NPV is then calculated by subtracting the total PV costs from
the total PV benefits and this is recorded in the row labelled “NPV”.
Without discounting, it can be seen that for r = 0%, the NPV is US$ 35.00. When
applying a discount rate of 3%, this NPV decreases to US$ 20.08. At a rate of 7%, the
NPV becomes US$ –8.16. Using the criteria that a positive NPV indicates that a project
is worth doing and a negative NPV indicates a project should not be undertaken, this
101
Chapter 8. Benefit–cost analysis
Table 8.1. Simplified example of discounting
Discount rate = 0%
Year
Benefits
Discount rate = 3%
Costs
PV benefits
Discount rate = 7%
PV costs
PV benefits
PV costs
0
0.00
100.00
0.00
100.00
0.00
100.00
1
25.00
50.00
24.27
48.54
22.68
45.37
2
50.00
10.00
47.13
9.43
41.16
8.23
3
50.00
10.00
45.76
9.15
37.35
7.47
4
50.00
10.00
44.42
8.88
33.89
6.78
5
50.00
10.00
43.13
8.63
30.75
6.15
225.00
190.00
204.71
184.63
165.84
174.00
Total PV
NPV
35.00
20.08
–8.16
example shows the importance of the choice of the appropriate discount rate. In this
case, with identical constant dollar benefits and costs, an increase in the discount rate
from 3% to 7% would change the decision on whether or not to undertake this project.
As can be seen in Table 8.1, whether an investment will yield positive net benefits may
depend on the choice of discount rates used in the analysis. The analyst is advised to
undertake sensitivity analysis as described later in this chapter to examine the impact
of different rates of discount on the decision. If positive net benefits are observed over a
reasonable range of discount rate, the analysis can be considered to be robust with
respect to choice of discount rates.
As a final note on discounting, the formula for NPV is simply the sum of the difference
in PV of benefits and costs:
NPV = NP benefits − NP costs =
T
Bt
∑ (1 + r )
t =0
t
−
T
Ct
∑ (1 + r )
t =0
t
=
T
Bt − Ct
∑ (1 + r )
t =0
t
The symbol Σ (Greek letter sigma) means that the benefits and costs are added up over
all time periods from the present year, denoted t = 0, up to and including the final year
in which benefits and costs are estimated, t = T.
In the preceding discussion, it was indicated that NPV is the appropriate measurement
for decisionmaking in BCA. Alternative ways of summarizing the outcome of a BCA
include BCRs and internal rates of return (IRRs). These measures use exactly the same
benefit and cost measures as in the NPV approach but summarize them a little
differently.
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For the BCR, simply divide the present value of benefits by the present value of costs
(rather than subtracting the present value of costs from the present value of benefits as
in NPV):
T
BCR =
NP benefits
NP costs
=
Bt
∑ (1 + r )
t =0
t
Ct
T
∑ (1 + r )
t
t =0
A decision rule for use of the BCR is that any project with a BCR larger than 1.0 is worth
undertaking (that is, improves societal welfare) and any project with a BCR less than
1.0 is not worth pursuing. As an example, using exactly the same benefit and cost flow
indicated in Table 8.1, Table 8.2 shows the calculation of the BCR (for just the 3%
discount rate example). In this case the BCR is calculated to be approximately 1.1.
A limitation to use of the BCR is that is does not indicate the magnitude of the
investment. If only BCR measures are used to choose between investments, the
investment with the highest BCR may be a small, low-cost investment and generate
insignificant benefits to users. However, when there is a budget constraint on public
investment funds, BCR will facilitate comparisons between investments in met/hydro
services as opposed to other public investments.
Alternatively, the IRR is the rate of discount (r) such that the NPV of the project is zero
(if such a rate exists). Thus, we solve the following equation for the rate (r) that will
make NPV equal to zero. In some sense, the IRR represents the return on the
investment. If the IRR is greater than the societal rate of time preference the project is
said to increase societal benefit (that is, it is a good investment for society):
Table 8.2. Example of benefit–cost ratio
Discount rate = 3%
Year
PV benefits
PV costs
0
0.00
100.00
1
24.27
48.54
2
47.13
9.43
3
45.76
9.15
4
44.42
8.88
5
43.13
8.63
Total PV
204.71
184.63
BCR
204.71/184.63 = 1.109
103
Chapter 8. Benefit–cost analysis
NP benefits − NP costs =
T
Bt
∑ (1 + r )
t =0
t
−
T
Ct
∑ (1 + r )
t =0
t
=
T
Bt − Ct
∑ (1 + r )
t =0
t
= 0
A limitation of the IRR is that in some projects it is possible to have multiple IRRs that
will make the equation equal to zero and it is not clear which IRR to use for
decisionmaking. Similarly to the BCR, the IRR also does not indicate the absolute
magnitude of the project.
In general, it is recommended at a minimum to report the NPV from the analysis. The
BCR can also be reported as this number is often used by policymakers and may be
easily understood by individuals unfamiliar with the concept of NPV.
8.3.2
Reporting qualitative benefit and cost information
In addition to reporting the results of the analysis of benefits and costs using one or
more of the three decision criteria presented in the previous section, the analyst
should also present a listing of those benefits and costs that have not been quantified
in the SEB study. In some cases, not all benefits will be quantified with government
decisionmakers. These non-quantified benefits will generally fall into two categories:
(a) benefits that would normally be monetized but are not for the SEB study because
of limited resources or time constraints; (b) benefits that are difficult to monetize. In
terms of costs, estimation of the costs of NMHSs is straightforward but costs for users
to take actions based on met/hydro services may entail resources and time that are
unavailable for the SEB study. Some benefits estimation methods, such as CV
methods, attempt to elicit net benefits information, reducing the need to have
benefits and costs information available for user communities. In addition, estimation
of external costs resulting from user community decisions will typically be beyond the
scope of the SEB study.
For all of the non-quantified benefits and costs, the analyst should provide an
assessment of their likely magnitudes and if possible a ranking of all terms, and indicate
how the various terms, if quantified or quantifiable, would likely impact on the net
benefits, BCR, or IRR calculations that have been presented for the SEB study.
8.3.3
Distributional issues
The methods used for BCA described so far are based on the approach that adding
benefits and costs to derive NPVs reaches a socially optimal outcome regardless of who
bears those costs or realizes the benefits. In essence this approach is blind to the
conditions of the affected individuals or of social norms about equity and distributional
issues. Often, regulatory analysis or BCA studies take this approach (Robinson et al.,
2014). However, it is important to consider that benefits or costs may accrue to specific
groups, sectors or regions and such differences would not be considered “fair”. For
instance, a tax may be imposed on all people in a country to support an improved met/
hydro service, but the benefits may only accrue to a smaller portion of the population
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that has access to forecast information (for example, has televisions) and the ability to
use that information to improve their well-being or profits.
If distributional or equity considerations are to be considered in the SEB study, they
should at a minimum be qualitatively identified and described so that decisionmakers
are aware of them when using the information from the BCA. More advanced
approaches to distributional issues can include applying different “weights” to benefits
or costs depending on to whom they accrue. For instance, if high-income individuals
are most likely to benefit at the expense of poorer people, weights inversely
proportional to income (for example, as a ratio to average income) may be applied to
the benefits and costs in the aggregation process. Taking our prior formula for


calculating NPV, we can incorporate individual weights,  YY  , which is average income
divided by the individual’s income. This is then multiplied by each individual’s benefits
and costs and added up across all individuals (that is, the additional summation from
i = 1 through i = I):
i
NPV = NP benefits − NP costs =
I
 Y  Bit
−

t
t =0  i  (1 + r )
T
∑ ∑  Y
i =1
I
 Y  Ct
=

t
t =0  i  (1 + r )
T
∑ ∑  Y
i =1
I
 Y  Bt − Ct

t
t =0  i  (1 + r )
T
∑ ∑  Y
i =1
There are a number of equity issues involved in choosing a correct set of weights to use
in such distributional BCAs that should be very explicit, as the choice of such a
weighting approach can be easily manipulated to reach some desired outcome that
may not be consistent with public policy processes.
8.4
SOCIOECONOMIC BENEFIT STUDY STEP 8:
LIST ALL OMISSIONS, BIASES AND UNCERTAINTIES
In this step, all omissions, biases and uncertainties associated with the estimated
benefits and costs are explicitly documented. Omissions will mainly relate to user
groups for which benefits and costs have not been quantified. The analysis may have
been truncated to include a subset of user communities. For those not included in the
analysis, it would be useful to list the user communities omitted and the types of
decisions and actions they might take in response to service information. As discussed
in Chapter 6, there are a number of potential biases associated with benefits methods
such as CV. Whenever possible, the analyst should describe the nature of the bias and
how it may have affected the analysis and calculation of benefits.
The analyst should also document key assumptions that underlie the estimate of benefits
or costs. For example, for a new met/hydro service, assumptions may be required about
the rate of adoption of the new service, as well as the types of decisions that users would
be expected to take in response to it. Since benefits of new services will typically lag
behind investments to develop the services, the rate of adoption would be expected to
rise over time. Assumptions may also be required to determine how benefits are to be
Chapter 8. Benefit–cost analysis
105
attributed to the change in services as opposed to other types of information as users
will often consider multiple types of information before taking actions.
These types of assumptions, combined with omissions and biases, will engender
uncertainty about the magnitude of benefits and costs estimates. In addition to
highlighting uncertainties and their sources in the SEB study results, the analyst may
provide analysis indicating whether different uncertainties are likely to result in
underestimates or overestimates of benefits and costs. By explicitly identifying and
analysing these uncertainties (by conducting sensitivity analysis (SEB study step 9,
below)), analysts will often deflect potential criticism of the BCA by honestly
recognizing the limitations of the analysis.
8.5
SOCIOECONOMIC BENEFIT STUDY STEP 9:
CONDUCT SENSITIVITY ANALYSES ON KEY VARIABLE VALUES
Sensitivity analyses on key variables of benefit and cost estimates is conducted with the
aim of exploring and communicating the impact of assumptions, uncertainties, or
natural variability in the SEB study results. Sensitivity analyses are used to identify
which assumptions or uncertainties have the largest impact on the outcome of the
analysis (for example, to identify which assumptions might change the net benefits of
an option from positive to negative or to alter the ranking of options in terms of their
relative net benefits).
Two potentially significant sources of imprecision in value estimates should be noted.
One is variability – the natural variations in an estimate resulting from its properties or
the forces acting on it. For instance, met/hydro services never predict weather
perfectly and thus there will be imprecision in the value of information simply due to
the natural variability in the atmosphere. Thus, no valuation study should indicate the
value of “perfect information” except as a potential upper-bound estimate of the value
of information. The other source of imprecision is uncertainty about an estimate that
arises from our lack of knowledge about the true value (for example, is the value of
improved weather forecasts US$ 25 per household or is it US$ 250?). Both variability
and uncertainty can lead to imprecise estimates and both are reasons why estimates
should be represented with a range of values instead of just a single value. Although a
single “best estimate” or mean value can be used, sensitivity analysis will help to
identify and explore the range of possible values. Using a range of values instead of
only a single estimate can avoid any perception that the analysis is tilted towards a
desired outcome. It will also help to indicate how certain NMHSs are about the results
of the analysis (for example, a narrow confidence interval as opposed to a very broad
confidence interval around the central estimate of the NPV).
In many cases it is important to explore the impact of uncertainties or key assumptions
(such as the choice of discount rates or the use of benefit transfer-based estimates – or
even whether an NMHS programme will improve the quality of information that users
receive) using sensitivity analysis. Using this approach, the value of a key input variable
can be systematically changed to see how it affects the outcome of the analysis. The
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change in results can illuminate how important the impact of uncertainty in a
particular variable is to the outcome. Sensitivity analysis is often performed by varying
a particular input by equal amounts greater to and less than the current value.
For example, if we choose a discount rate of 9% for the main analysis, we might vary
that value in increments of 3 percentage points from 0% to 15% for the sensitivity
analysis. Table 8.3 shows an example of a sensitivity analysis for the discount rate
applied in this fashion to the range of benefits and costs. Other key variables should
also be considered in sensitivity analysis. For instance, if it is uncertain whether or not a
particular forecasting method will work, or how well, the BCA sensitivity analysis
evaluates NPV under different potential outcomes of the forecasting method.
Sensitivity analysis (also called “scenario analysis” 24) is an important tool for helping
met/hydro services understand the effect of uncertainty. By examining different
conditions with different values from the range of uncertainty for key variables, we can
determine whether the uncertainty in the underlying variables is important to the
ultimate outcome of the analysis or the decisions to be made based on the analysis.
This knowledge can help us focus future research efforts on the most productive
Box 8.1: Monte Carlo method
The Monte Carlo method is useful in situations where multiple sources of variability or
uncertainty can have profound impacts on estimates of benefits, risks, costs, or all three. The
Monte Carlo method can be applied when the range and likelihood of plausible values for
the key variables are understood well enough to characterize those values with a probability
distribution. The Monte Carlo method can easily be used to reproduce the analysis in a
computerized algorithm and can be especially useful when multiple variables can
potentially interact to establish the true character of the risk being studied.
In Monte Carlo analysis, one should start by characterizing probability distributions for key
input variables using data and knowledge developed through experience. For first
approximations, it is often sufficient to assume relatively simple distributions for many types
of phenomena (for example, uniform, triangular, normal or log–normal distributions). The
distributions of any two variables, however, are usually treated as independent of each
other. If the variables always move together – either in the same or opposite directions – the
variables may not be independent and their joint relationship must be accounted for in the
analysis. The Monte Carlo method uses computers to draw a large number (for example,
more than 1 000) of random samples for each possible combination of variable values. The
random draws are guided by the probability distributions, such that more probable
outcomes are drawn more frequently than less probable outcomes. The analysis is then
replicated for each sample draw of input variables and a final output is obtained for these
inputs. When the final outputs for all sample draws are gathered together, the result is a
probability distribution of the final output, based on the combined probabilities of each of
the underlying input values. This result can give decisionmakers useful insights about the
likelihood of a given outcome (for example, what the probability is that a project’s NPV will
be positive when the NPV outcome is influenced by several variables whose values are
uncertain).
Source: Black et al. (2009)
24
Scenario analysis is more common in financial analysis for investments. Some definitions indicate
that scenario analysis involves setting uncertain variables as maximum values and assessing the
outcomes – essentially evaluating the worst and best case scenarios.
107
Chapter 8. Benefit–cost analysis
Table 8.3. Sensitivity analysis applied to discount rate
Discount rate (%)
PV monetized benefits*
PV costs*
Monetized net benefit (as NPV)*
0
49 000–51 500
30 000
19 000–21 500
3
39 500–41 700
26 000
13 500–15 700
6
29 500–34 000
22 000
7 500–12 000
9
15 950–21 300
16 000
(50)–5 300
12
8 500–14 000
11 000
(3 500)–3 000
15
2 500–8 000
8 000
(5 500)–0
* Thousands of US$.
topics, improving the BCA at the same time. The example in Table 8.3 looks at the
sensitivity with respect to a single uncertain variable (in this case the discount rate).
Often, however, several variables in the analysis may be uncertain and should be
evaluated together in terms of their joint impact on potential outcomes. One useful
approach to the case of multiple variable uncertainty, the Monte Carlo simulation or
analysis, is outlined in Box 8.1.
Sensitivity or scenario analysis is somewhat different from evaluating different projects
or courses of action. As mentioned previously, if the agency has the option (or
potential) of either supporting ongoing operations and maintenance costs or not
supporting them, this could significantly impact the long-term flow of benefits from a
project. While this may often be evaluated under the rubric of sensitivity analysis, it
may really be a situation of evaluating two different future conditions or essentially
different programmes.
Sensitivity analysis generally involves replicating the analysis under different conditions
of potential outcomes of key variables. These are generally characterized with some
degree of probability and thus involve risk as opposed to uncertainty. For instance, it
be may be unclear how much a new radar facility will improve forecast quality in a
certain region of a country and thus different values of the potential improvements (for
example, low, medium, and high values of the improvements) should be evaluated
with sensitivity analysis. Uncertainty is defined as not knowing the probability
distribution of potential outcomes or not knowing what the whole range of outcomes
may be. For instance, in an ideal situation, data would be available for statistically
estimating confidence intervals for benefit or cost estimates. Statistically estimating
confidence intervals, however, may not be possible. When data are available to make
this possible, ranges are developed for an estimate by stating the upper and lower
bounds. When bounding of an estimate is not possible, we can at least characterize
uncertainty qualitatively by describing the sources of uncertainty and stating whether
an estimate developed is likely to over- or underestimate the true value.
It may also be useful to use sensitivity analysis to determine at what level of a key
variable the decision outcome would change (for example, the level of forecast
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improvement related to a new radar at which the NPV changes from positive to
negative). Expert judgment may then be used to evaluate how likely in the real world
that level of the key variable will be.
8.6
CONCLUSIONS
The comparison of benefits and costs represents the final major step in conducting the
SEB study and provides the decisionmaker with an economic measure of the value of
the proposed investment to society. As noted, careful selection of the discount rate to
be applied in calculating net values for benefits and costs can have a major impact on
the outcome of the BCA. In general, with high discount rates, for investments with
significant front-end costs it will be more difficult to demonstrate net benefits. The
presentation of the quantitative results, listing and analysis of non-quantified benefits
and costs, discussion of omissions, biases, assumptions and uncertainty, and analysis of
sensitivity of results to alternative specification of uncertainties, affords the
decisionmaker an opportunity to determine how robust the results are and will help
NMHSs communicate the SEB results to a range of audiences.
REFERENCES
Aalbers, R., 2009: Discounting investments in mitigation and adaptation: A dynamic stochastic
general equilibrium approach of climate change. CPB discussion paper No 126. The Hague,
CPB Netherlands Bureau for Economic Policy Analysis.
Asian Development Bank, 1997: Guidelines for the Economic Analysis of Projects. Manila, Asian
Development Bank.
Baum, S.D. and W.E. Easterling, 2010: Space-time discounting in climate change adaptation.
Mitigation and Adaptation Strategies for Global Change, 15(6):591–609.
Belli P., J. Anderson, H. Barnum, J. Dixon and J. Tan, 1998: Handbook on Economic Analysis of
Investment Operations. Washington, D.C., World Bank.
Black, J., N. Hashimzade and G.D. Myles, 2009: A Dictionary of Economics. Third edition. Oxford,
Oxford University Press.
Gollier, C. and M.L. Weitzman, 2009: How should the distant future be discounted when
discount rates are uncertain? http://idei.fr/doc/by/gollier/discounting_long_term.pdf.
Goulder, L.H. and R.C. Williams, 2012: The choice of discount rate for climate change policy
evaluation. Washington, D.C., Resources for the Future, http://rff.org/RFF/Documents/
RFF-DP-12-43.pdf.
Just, R.E, D.L. Hueth and A. Schmitz, 1982: Applied Welfare Economics and Public Policy. Englewood
Cliffs, New Jersey, Prentice-Hall, Inc.
Nordhaus, W.D., 2007: A review of the Stern Review on the Economics of Climate Change.
Journal of Economic Literature, XLV:686–792.
Robinson, L.A., J.K. Hammitt and R. Zeckhauser, 2014: The role of distribution in regulatory
analysis and decision making. Regulatory policy programme working paper RPP-2014-03.
Cambridge, Massachusetts, Mossavar-Rahmani Center for Business and Government,
Chapter 8. Benefit–cost analysis
109
Harvard Kennedy School, Harvard University, http://www.hks.harvard.edu/var/ezp_site/
storage/fckeditor/file/RPP_2014_03.pdf.
Stern, N.H., 2007: The Economics of Climate Change: The Stern Review. Cambridge, Cambridge
University Press.
Weitzman, M., 2012: The Ramsey discounting formula for a hidden-state stochastic growth
process. Environmental and Resource Economics, 53(3)309–321.
Zhuang, J., Z. Liang, T. Lin and F. de Guzman, 2007: Theory and practice in the choice of social
discount rate for cost-benefit analysis: A survey. ERD working paper series No. 94. Manila,
Asian Development Bank.
CHAPTER 9. SOCIOECONOMIC BENEFIT STUDY STEP 10:
COMMUNICATING THE RESULTS OF SOCIOECONOMIC
BENEFIT STUDIES
Chapter 1. Introduction
9.1
INTRODUCTION
The benefits provided to society through
meteorological and hydrological services are
Chapter 3. Purpose of SEB studies
widely accepted as being substantial, and are
especially evident in extreme weather, climate
Chapter 4. Designing SEB studies
and river conditions. However, they are not
usually expressed numerically following a
Chapter 5. Economic essentials
rigorous economic valuation exercise. Thus,
Chapter 6. Benefits
there is a particular need to devise a specific
communication strategy around the preparation
Chapter 7. Costs
and execution of an SEB study. Even before the
Chapter 8. BCA
study begins, this strategy should be designed
to ensure that the results of the study are
Chapter 9. Communications
communicated effectively internally as well as
externally to the relevant decisionmakers, a wide
variety of stakeholders and to the public. The
Chapter 10. Looking forward
overall communication objective is to create a
strong and consistent message coming from the NMHS that gains or maintains public
support as well as generating greater diffusion of weather-related information from the
met/hydro services. Chapter 9 covers the final step of the 10-step process – formulating
and communicating results to decisionmakers and stakeholders.
Chapter 2. Met/hydro services
This chapter, a follow-up to guidance on designing the SEB study in Chapter 4, will
focus on the different elements of a communication strategy, from identifying the most
appropriate audiences to working with the various communication media to greatest
effect, as well as ensuring that the SEB study lessons learned are best employed.
An NMHS communication strategy should focus first on practicalities – what message
is to be conveyed related to the SEB study implementation and results, who is to be
reached, what sort of delivery channels are to be used and how are these to be best
utilized. Although communication strategies are discussed in the penultimate chapter
of the publication, these should be developed in parallel with the detailed scope of
work to ensure they are timely and appropriate at each step in the SEB study
implementation and outreach.
9.2
USER INTERACTION, SATISFACTION AND VALUE
As outlined in Chapter 3, rather than attempt a whole-of-service study, in many cases it
will be easier to both measure and illustrate the economic value generated by forecast,
warning, and other information and advisory services that are provided to a specific
client or a specific sector. The benefits and costs from a forecast or a warning are easier
to define than those associated with the range of decisions also affected by met/hydro
services. Following an SEB study, therefore, there exists an opportunity to tell a
CHAPTER 9. SOCIOECONOMIC BENEFIT STUDY STEP 10:
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111
comprehensive story about the economic benefits that derive from weather
information in these circumstances. By storytelling, or translating the study’s data into
narratives, a greater success in reaching your intended audiences can be created.
However, for an NMHS to use these instances as an example of their beneficial
outcome presupposes an excellent working relationship between the organization and
the client or sector in question.
The interaction of an NMHS with its users must be a two-way process and involve a
focus from both parties to learn more about the business of the other; it takes time and
consistent communication. The NMHS staff need to know and understand the business
of the client to be able to tailor the available weather information most effectively. The
client needs to understand not just the potential afforded by meteorological guidance
but also the limitations of such guidance. Deep interaction between NMHSs and their
clients should lead to a high level of user satisfaction. During this time, an NMHS
should constantly monitor, formally or informally, the level of this satisfaction. It is only
then that the question of user value should be approached.
Understandably, a commercial enterprise may not be willing to reveal to a service
provider (in this case, an NMHS), or to the public, the detailed financial information
which would allow the full value provided through meteorological services to be
identified. It is imperative that any communication of SEB study results deriving from
such specific clients or sectors should be fully cleared with the users in question before
being released to the public or employed in any other communication context.
9.3
UNDERSTANDING AND INTERPRETING SOCIOECONOMIC
BENEFIT STUDY RESULTS
9.3.1
Policy aspects
Any consideration of the results of an SEB study should be prioritized in the context of
the definition of the organization’s role and mission. This definition may have been
determined through one of a number of processes:
–
There may be a meteorological law that stipulates the role and responsibilities of
the NMHS (Rogers and Tsirkunov, 2013);
–
There may be a governmental or ministerial order or a similar formal decision that
defines these roles and responsibilities;
–
In the absence of these there will be established practice which can be
augmented by reference to authoritative documentation, such as the WMO
guidance on the role and operation of NMHSs (WMO, 2013).
While a definition of the role and responsibilities of an NMHS will not normally
delineate the expected economic benefits explicitly, the anticipated societal benefits
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will usually be articulated in this definition, or may be inferred from it. This definition
can provide a benchmark against which the results of an SEB can be measured.
Emphasis on how the NMHS is meeting its public duty commitments needs to be a key
aspect of any campaign to communicate the outcomes of an SEB study.
Many NMHSs follow policies based on the commercialization of weather data. In some
cases, these policies are established by central government as part of a cost recovery
programme, whereby users of publicly funded information contribute to the costs of
collecting that information. However, an SEB study may allow a more rounded, holistic
view to be taken of the value of weather data, whereby the total value to a national
economy of well-delivered meteorological and hydrological products and services can
be set against the cost of providing those services. In the commercialized model, the
total value of meteorological data is established by what the market will pay for that
information, which is often only a fraction of the total cost of data acquisition and
collection. A model which can estimate the entirety of the economic contribution
made through NMHS products and services, including some estimation of the value of
archived information for future use, provides a more realistic measure of the value of
those entities.
9.3.2
Economic aspects
Climate services have recently come to the forefront due to the establishment of GFCS
by WMO. This initiative is partly a response to the increasing threat to lives and
livelihoods posed by climate change, but the concept of climate services is not. Climate
services involve the provision of meteorological and related information on climate
timescales (months, years, decades and centuries). These data are typically highly
statistical in nature, providing information on the mean and extreme values of
specified weather parameters, or on the statistical likelihood of certain thresholds (for
example, low temperatures, or rainfall accumulations) being reached or exceeded.
Going beyond economic valuations must likely include narratives of experience; this
will strengthen the expert analysis by distilling the information in an understandable
form. While economic benefits can be quantified in numerical form that will be
important when communicating the outcomes of an SEB study, there are other,
broader, societal benefits which are more difficult to quantify, but which are
nonetheless real and substantial. Among these are the “convenience benefits”, which
accrue when people schedule their daily or weekly activities to take advantage of good
weather and avoid inclement conditions. It may be difficult to aggregate these benefits
across society in any meaningful way, although some suggested approaches are
discussed in Chapter 6 and featured in case studies in Appendix E. Nevertheless, such
benefits can be communicated effectively through these narratives and stories that
flow from the experiences of real people. The more the narratives can relate to a
greater number of people the better, as it will lead to a greater appreciation of the
value of good meteorological advice and guidance. Narratives have often been
supported by expert commentary from psychologists and similar, and framed with
quantitative analysis of the overall benefits from met/hydro services.
CHAPTER 9. SOCIOECONOMIC BENEFIT STUDY STEP 10:
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Routine forecast services provided to members of the public and to specific agencies or
commercial entities are core functions of NMHSs. It is through these services and the
surrounding interactions with users that an NMHS can establish and build a reputation
for reliability, credibility and service quality. It is therefore important that a study team
includes these routine services in some manner and equally important that the
communication of the outcomes relating to these services be given significant
emphasis.
These routine services are the strongest connection an NMHS has with its user base, and
form the fundamental underpinning of the strength of the NMHS brand. The derived
benefits will frequently be more societal than purely economic, but as outlined in
Chapter 6 these benefits can be quantified, albeit not always in a fully economic sense.
Ideally, the communication of, and discussion around, SEB study outcomes will be
related to some established baseline for comparison purposes, such as past studies in
the country or similar studies in other countries, sectors or regions. However, this will
rarely result in directly comparable studies and the interpretation and understanding
will need to take full account of key differences.
At the other end of the weather spectrum are the severe weather and hydrological
events, which are now more often referred to as high-impact weather. Warnings of
high-impact weather are the most basic task of any NMHS and contribute directly to
the mission of all governments to ensure the safety and security of its citizens.
While substantial benefits are provided by NMHSs through routine meteorological and
hydrological services, especially significant societal benefits will likely arise in the
context of periods of severe or high-impact weather. Such foreknowledge can facilitate
some measure of control among members of the public faced with severe weather
events, as opposed to the feeling of powerlessness when the impacts of severe weather
or flooding arrive without adequate advance warning.
Statistics available in the Atlas of Mortality and Economic Losses From Weather, Climate and
Water Extremes (1970–2012) (WMO, 2014) indicate a significant fall-off in the number of
lives lost to weather hazards during recent decades. These figures suggest that the
NMHS community has been successful in promulgating warnings that allow people to
be moved away from approaching danger. However, the trend of economic losses due
to weather-driven disasters has been increasing rather than decreasing over time. It is
much more difficult to move economic resources (for example, property) away from
the path of an approaching hazard, or to protect them effectively. Thus the
amelioration of economic losses from high-impact weather due to weather warnings
will probably be greatest in saving lives or preventing injury. There will usually be some
measurable benefit from the removal of mobile economic assets from the path of a
hazard (motor vehicles or livestock, for example, or the moving of electrical goods and
soft furnishings to higher floors in a property when flooding threatens).
The communication of economic benefits deriving from warnings of high-impact
weather will thus be best served through a mix of numerical economic benefits and
narratives which relate to actual experiences. The broader societal benefits, as noted
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above, relate to the improved psychological outcomes among those who have
experienced weather disasters but who have had some control in the mitigation of risk
due to forewarning, and can also be cited. The very large sums typically expended on
infrastructure, and guided by long-term planning, provide a basis for describing and
communicating the benefits that can be derived from climate services. As an analogy,
planning is akin to mapping the future and the costs of climate services are part of the
necessary cost in drawing that map.
9.4
SOCIOECONOMIC BENEFITS STUDY RESULTS TRANSLATED INTO
AN AUDIENCE MESSAGE
An SEB study can be a rich source of information for the management team of an
NMHS. This information can guide decisions, strategies and actions on a number of
levels. This section examines in turn a number of means to best utilize the results of an
SEB study when discussing with external audiences.
Public and private advocacy
Elaborating the case for resources: All NMHSs rely on core funding from government,
whether this is provided directly or by means of service-level agreements or similar,
which relate to the core public tasks of the organization. In addition, many NMHSs
derive funding from other government agencies or bodies in exchange for the
provision of defined services. In all cases, the NMHS which can plausibly demonstrate
that it provides good value for money (whether societal or economic in character) is in
a better position to argue for retention of, or an increase in, its existing resources.
Advocacy to the public: Every NMHS must develop a strong degree of credibility and
trust with the public. Primarily, this is necessary to ensure that the public takes proper
account of forecasts and warnings and takes appropriate actions. Unless actions are
taken, the potential benefits of met/hydro services will go unrealized. There is a
virtuous circle or feedback loop here; increasing the confidence of the public in the
services provided through an NMHS will increase the uptake of services and the
translation of guidance into actions and decisions. The positive outcomes will increase
the confidence of the public still further and lead to yet higher uptake of services and
improved outcomes at the end of the value chain. No matter where an NMHS stands in
the confidence of the public it can engage in improving this confidence and, hopefully,
commence this positive feedback process.
To achieve this, part of the message that an NMHS needs to communicate to the public
is that it has used public resources wisely and efficiently, and that it represents a net
contributor to the economic and societal well-being of the nation. An NMHS with a
positive public profile will be more likely to gain positive response to resource requests.
Advocacy to key users: While direct advocacy by an organization on its own behalf is
valuable, third-party advocacy by other agencies and organizations is infinitely more
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so. Typically, NMHSs provide services to organizations in both the public and private
sector, including energy utilities, water and sanitation companies, roads and transport
agencies, environment agencies, radiological protection institutes, and the like, as well
as to private companies engaged in many spheres of economic life. If these
organizations can become advocates for the greater investment of resources in the
NMHS, their leaders’ views will then carry significant weight. While an SEB study may
well focus on some of these organizations or sectors in particular, the demonstration of
positive economic and/or societal benefit deriving from such a study will be of interest
to all such organizations and will help to raise the profile and the prestige of the NMHS
in question.
Advocacy to the aviation community: The case of aviation deserves special mention.
Most NMHSs provide services to aviation in accordance with the “Chicago
Convention” of the International Civil Aviation Organization (ICAO) (ICAO, 2014) and
recover their costs, or a portion thereof, through the imposition of en-route and
landing charges on airline operators. Increasingly these charges are set by regulators
who have a brief to minimize the charges levied while maintaining adequate safety of
air travel through air navigation support services. When presenting a case to the
regulator for the proper allocation of resources to support aviation meteorology, an
SEB study is an important tool. Increasingly, such tools will be needed to counter the
trend of discounted pricing within the aviation industry.
9.5
INTERNAL AND EXTERNAL INTERPRETATION OF THE
SOCIOECONOMIC BENEFIT STUDY
9.5.1
Internal audience
Operational meteorology is a multilayered enterprise and, within an NMS, one can
expect to find a range of perspectives and interpretations of SEB study results. The
collective wisdom in any organization can be substantial, if it is properly assimilated.
The senior managers of the NMHS will likely be instrumental in commissioning the SEB
study, and they will need to use the outcomes effectively to argue for adequate
resources for the sustainable development of the organization. They will need to pick a
number of clear, consistent messages from the study outcomes and emphasize these in
discussion with officials from the parent department, officials from the finance ministry,
politicians, and the like, as well as making notes with staff concerning relevant
narratives for later use.
It will be important to consider and decide in advance who will be the key
spokesperson of the NMHS in promoting the study through the media. This might be
the director or some other senior manager, but it must be a person who is comfortable
in dealing with journalists, who is effective at making presentations to groups, and
who can confidently deliver on-air interviews. This person must be given time to
become thoroughly familiar with the study and its results, and be provided with
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resources (graphics artists, web specialists, and the like) to enable effective
presentation across the wide range of communication platforms. Where an organization is distributed geographically, it will be especially important to
engage the regional managers and regional staff in the process of interpreting and
communicating the results of the SEB study. The methods of circulating information
will vary greatly depending on the size of the NMHS, but could include presentations
to staff, team meetings, newsletters, intranet, and the like. It will be vital for senior and
regional managers to gather together in seminars to learn of, and discuss, the SEB
results. The regional managers should then organize meetings at regional and local
level to keep all staff fully informed.
Front line staff will have an important role in the communication process – this is
especially true of forecasters, climatologists, and applications developers who, through
their daily work, have direct contact with many of the users of the NMHS. Their
contacts and relationships with users may prove an invaluable resource when seeking
to identify and collect “stories” or narratives of individual experiences that will add
colour and depth to the statistical results of the SEB study.
For those NMHSs which are large enough to have their own internal capability in the
areas of media liaison and public relations, these staff will also be a key resource in this
regard. Indeed, it should be the public relations staff who have a responsibility for
designing the overall communication strategy around the SEB study and results. They
should be consulted at an early stage in the planning of the study, and can support the
efforts throughout implementation.
9.5.2
External audiences
Governmental bodies, and especially finance or public service ministries, will be a key
target for effective communication of SEB study outcomes, which should be
disseminated in varying methods depending on the target audience. Sending a paper
or electronic copy of the report does not constitute adequate communication,
although this of course is necessary to provide detail and material for reference. A more
proactive approach will be required. The finance people will need to see the numbers,
but these can be given greater impact through well-chosen graphics used to illustrate
key findings. Ideally, there should be presentations to relevant officials in a seminartype format, in which the key messages are presented, the detail is readily available,
and the questions and concerns of the officials can be answered and teased out in
discussion afterwards.
As noted earlier, public service users of meteorological services can be very effective
advocates for NMHSs within government structures. Many public service users
(emergency management community, military, energy utilities, and so on) will have
annual meetings, conferences or other regular events. Especially at a regional or local
level, these are tremendous opportunities for an NMHS to address key user groups, to
tell them about advances in meteorology and help them identify the tangible benefits
that quality meteorological services can generate.
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As with public sector users, private sector users are often best addressed within their
own social and communication structures, through conferences and seminars. To
impact a private sector audience, it will be advisable to prepare illustrations of actual
and potential economic benefits deriving from met/hydro services, and to make every
effort to demonstrate the economic and societal contribution of an NMHS. The private
sector often views public sector bodies in general as inefficient.
User communities in the aviation sector pose a particular challenge because of the
unique nature of that business, where safety is paramount and economics is
fundamental. Aviation has become much more complex since the days when the
provision of the significant weather chart, the aviation routine weather report, the
terminal aerodrome forecast, and the significant meteorological information
constituted adequate service. Economic aircraft routing is a key concern, while the
working of a busy airport poses a myriad of meteorological challenges. If the SEB study
has specifically addressed the aviation sector, then there will be considerable material
to communicate to this constituency. If not, then the information may not be of great
relevance, but may still help inform where improved meteorological services can offer
economic benefit.
Many NMHSs will have existing media partners in the public or private sectors with
which they work to disseminate weather forecasts and warnings. An SEB study which
illustrates societal and/or economic benefit to the general public (as opposed to
specific sectors) represents a good news story for these media partners and an NMHS
should encourage these partners to advertise the positive outcomes of the study. The
co-benefits of the story will help strengthen and deepen the working and institutional
relationship between the two organizations.
When the SEB study has been completed, the media liaison staff who work within the
NMHS itself should initiate a media campaign to communicate the outcomes, which
should be focused on societal and economic benefits generated by the NMHS. Some of
this may be soft in nature, such as informal meetings with journalists to outline the
results and consider news angles. Alternatively, there might be a more formal
presentation of the results and outcomes through a press conference, with associated
press packs provided that will help journalists to prepare and illustrate their stories.
Information is best disseminated when drip-fed over a longer period of time.
Marketing and sales staff will play an important role by demonstrating to existing
clients the range of positive outcomes which can flow from good use of weather
information, and in illustrating to potential clients the value of taking a professional
service from their NMHS. They will need to be selective in using the study outcomes,
matching the individual statistics and stories with the business needs of their client
contacts. More information about engaging external audiences is provided in
section 9.7.
The elements of a communication strategy are discussed below, but the vital point is
that it should deliver clear, coherent and consistent information about the SEB study
and its outcomes to a wide range of audiences – from key decisionmakers in funding
agencies through staff members and users to the general public.
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AUDIENCE DIVERSIFICATION AND VARYING DISTRIBUTION
CHANNELS
Any SEB study must be carefully planned, starting with the initial concept and
following on to refining the aims and objectives, selection of the study team,
implementation of the study itself, analysis of the findings, and publication of the
results. It might be tempting to think of the publication of results as being the end of
the exercise, but it is, in many ways, only a beginning if the study is to be more than
a purely academic exercise. Indeed, the communication of SEB study results should
not be thought of as a one-off activity. The occurrence of a high-impact
meteorological or hydrological event, among other opportunities, will offer new
occasions on which SEB results can be presented in a manner that generates further
focus and attention.
News media: When approaching the communication of technical information to and
through the news media, there is a need to consider carefully the style of the media
and the likely time that will be allocated to covering the story. At one end of the scale
will be the tabloid media or popular press and their broadcast equivalent, the “sound
bites”, required for short, snappy news bulletins aired on radio stations. These media
will need simple headline facts, such as “Hydro/met service delivers X dollars of benefit
for every dollar of public money spent”. For these media, this sort of story will not be a
highlight of their output; the best that can be hoped for in terms of coverage is a few
short paragraphs.
At the other end of the scale will be the analytical articles such as will be found in the
financial or editorial pages of the press and trade and professional magazines and
journals. The broadcasting equivalent might be a long (five to ten minute) interviewbased item on a current-affairs radio programme (or, less frequently, a television
programme).
While the statistics will be important, it will be desirable to augment and illustrate
them with narratives or stories about specific examples of benefits. The narratives will
more likely make it to print or onto the airwaves if supplementary information is
provided such as background briefing material, fact sheets, a potential headline of the
story, some narratives of good examples of benefits (if these are available) and the
contact details of the NMHS person who can provide further information or be
interviewed on the topic.
The media gets many “story ideas” proposed to it, often by professional public
relations firms acting on behalf of clients, and stories from NMHSs will need to
compete for attention if they are to be selected.
Television/Internet: These are primarily visual media, and as such the primary “driver”
of a story will be the quality of the graphical treatment. For television, a narrative or
story illustrating positive examples of benefit experienced by individuals, businesses or
user communities will also be of value. A television report on the results of an SEB study
might contain four distinct elements:
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–
A headline giving the key findings of the study;
–
An interview with a user who has a good story to tell;
–
Graphics showing the benefits – perhaps by sector – in a visual manner;
–
An interview with an NMHS representative who can comment on and
contextualize the study (and make the case for increased investment).
119
Almost all NMHSs host their own websites, which by their nature will usually attract a
significant audience seeking weather information and forecasts. Links to the SEB study
and results can be placed on the main page, but need to be positioned in a
promotional capacity, attracting users to click through to the pages featuring the study
results. That page should be largely graphical, with the minimum of explanatory text;
the more detailed information can be placed in subsidiary pages where those with
particular interest can access and peruse it.
Electronic/social media/blogs: In the very crowded environment of social media,
stories typically command a very short attention span and have to compete with a vast
array of other content. Here, the strategy might be to place a few simple headline
stories on networks such as Twitter with links back to the pages of the NMHS website
or an online social media source, which carry the full detail of the study as described
above. Social media has a role in being a “signpost” to the more detailed treatment of
the story elsewhere. Interest in the story can be elevated by using well-known
personalities, who regularly blog or tweet, to carry the story or make reference to it,
with appropriate links back to the source material. Creating a lot of interest in a story
on social media is also a means to generate interest in the story within the conventional
media, who source many of their stories on social media and will need to cover stories
that trend strongly in this market.
9.7
TARGET AUDIENCES
Funding agencies: While all of the communication strategies and plans are important,
those aimed at funding agencies and the like are perhaps most important of all, in that
they can leverage significant benefit for the NMHS. The communication to funding
agencies does not exist in a vacuum, however; the more broadly based communication
through the mainstream media will affect and inform the attitudes and decisions of
individuals within funding agencies. However, decisions to allocate funds will need to
be supported by specific, targeted information. This can be communicated graphically,
but will need to be backed up by detail concerning the SEB study’s funding,
methodologies and findings.
If the findings are to influence funding decisions they will need to be specific about the
sectoral benefits, and possibly inform where funding might best be applied. If there
are inferences that can reasonably be made that support increased investment in, for
instance, the ground observation network, weather radar, or forecaster provision and
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training, then these should be highlighted. If supported by the outcomes of the SEB
study, a detailed assessment of what investments need to be made will significantly
improve the chances of leveraging increased funding as it demonstrates an analytical
approach by NMHS management.
Users: The publication of an SEB study for the user community of an NMHS is an
opportunity to broaden and deepen the communication between service suppliers and
their clients. Initially, this might be by means of a newsletter-type publication, and
significant users will expect to be directed towards a more detailed assessment of the
study. Therefore, opportunities should be created for the user community to meet with
both the team who worked on the study and relevant NMHS personnel in a seminar or
workshop setting, where users have the opportunity to ask questions and to probe
interests and concerns. These occasions may also lead to increased business
opportunities for the NMHS, as users gain a greater awareness of the range of benefits
which may be afforded by more targeted use of weather information in their businesses.
Academic users/reviewers: This is a very specific community who may be interested in an
SEB study in terms of both methods and results, and as references for guiding future work.
In general, this community will be served through the traditional means of published
papers and academic lectures. In a country where studies of meteorological services have
not previously been carried out – and there are many – the publication of such a study
represents an opportunity to engage economists and public policy experts who may not
have considered NMHSs as a topic of interest (Perrels et al., 2013). In this manner, a study
can catalyse further work, perhaps looking in more detail at different user sectors, or at
the benefits of state investment in NMHSs vis-à-vis other public sector service providers.
While NMHSs typically have a high public profile, their value isn’t necessarily conveyed as
a similar high priority for funding. As a result, it may be beneficial to encourage and
sustain interest in met/hydro services amongst those in the academic community who are
often key influencers of politicians and other senior decisionmakers in government.
As well as promoting the results of an SEB study, subsequent seminars and lectures for
the academic community will need to focus on the methodologies employed and the
resources consumed in preparing the study, as these details will assist those academics
who might choose to engage in further studies, either by replicating the methodology
in a different context or attempting to verify the findings using complementary
methodologies. When presenting studies and results to academia, it will be important
also to communicate clearly that appropriate academic rigour was brought to the
exercise and to the analysis.
Press release/media interview: It is important for an NMHS to realize that while the
media are largely a means of mass communication to a large cohort of listeners and
viewers, these journalists can also be used to speak directly to policymakers, who are
usually avid consumers of the mass media and take a keen interest in the topics that
appear. Every press release, for example, may lead to a newspaper article that is read by a
minister or a senior decisionmaker. Recognizing that every news story has a “shelf life”
and that interest will fade in time (a week is a long time for a story to survive in the media)
the communication strategy should be to maximize media coverage over a short period,
ideally aligned with key decisionmaking timetables in funding agencies or departments.
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Recycling lessons learned into the education of younger meteorologists: The education
of meteorologists in general, and forecasters in particular, is normally focused
exclusively on the physical sciences and rarely touches on user needs and
requirements. The availability of an SEB study offers the opportunity to build this
element into meteorological education; both to confirm to students the value of their
chosen career and to help them better identify opportunities for the application of
meteorological science to societal needs. Indeed, it may inspire students to develop
new and innovative weather services that better match meteorological information to
user needs.
A summary of the possible points of interaction with a range of stakeholders is
provided in Table 9.1.
Table 9.1. Socioeconomic benefit study audiences and opportunities for engagement
Audience
Opportunities
Engagement options
Public authorities
Public authorities are influential
advocates for improved
meteorological infrastructure
Regulators review the NMHS
service provisions, especially
aviation
Service users and taxpayers expect
efficiency, so publicize realized
benefits and potential benefits
Public fund investment
decisionmakers are interested in
service efficiency. An SEB study
can help balance pressures to
excessively commercialize weather
data and services; it provides
information on the overall
economic benefits to society
– Finance ministry
– Numbers, graphs, visuals.
Emphasize economic benefit
– Aviation industry
– Annual meetings or specially
convened seminars
– Business leaders
– Media, conferences, and
professional clubs
–Politicians
– Respond to voters, and politics
is local. Run local campaigns in
tandem
– Science funding agencies
– Scientific quality and evidence
of economic benefit crucial.
Formal presentations
– Opinion shapers
– Journalists, etc., should be
approached for one-onone meetings; background
materials/press packets
recommended
Regulator
Service users
Funding
authorities
Media partners
Emergency
managers
Civil society
As existing users of weather
services and existing channels
of communication to end users,
they are likely to be interested in
the “good news story” which the
publication of an SEB study would
represent
Emergency managers have a
strong interest in the resilience
of weather services generally
and NMHSs in particular. Their
voice carries considerable weight
with decisionmakers – especially
investment in meteorological
infrastructure
Communication with civil society
will likely be through the mass
media and specific strategies for
maximizing publicity
–Emergency management users,
stakeholders
– One-on-one meetings,
conferences.
Publication of articles in trade
journals
– General public
– Address through the media
with local NMHS staff or
presentations to town council
meetings, etc.
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9.8
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ANALYSING THE OVERALL SUCCESS OF A SOCIOECONOMIC
BENEFIT STUDY COMMUNICATION STRATEGY
Not all the elements in a communication strategy will work equally well, and some
measure is needed by which an NMHS can assess what is working and what is not. Of
course, the ultimate test will be whether sustainable funding is achieved, but this may
take years to evolve and analyse. In the shorter term, some more accessible measures
are required.
A good place to start is by defining at the outset a list of metrics that the SEB study
communication strategy manager will track (that is, activity, reach, engagement and
impact). These can be direct measures, such as minutes of radio airtime or column
inches in the printed press. There is a wealth of statistics available through website
analytics, downloads, re-tweets, and the like. Numbers of presentations made to
conferences and professional groups can be counted, and the direct audience
estimated, as well as focus group and survey-based qualitative and quantitative
information tracked and analysed (Public Library of Science, 2014). By doing this, the
NMHS will have access to data for reporting back via information graphics and
assessments. These may include, for example, trends throughout a campaign, or
number of audience members reached for specific sectors of the external audience (for
example, regional emergency management personnel). As part of the overall
communication strategy of an NMHS, these results should be included in
presentations, especially to public and funding authorities, regulators and service
users. With access to analytical information about how met/hydro services are directly
benefiting its wide array of users, an NMHS will be well-placed to discuss and promote
its services to local, regional or countrywide audiences in varying sectors.
9.9
CONCLUSIONS
This chapter has outlined the critical role that good communication can play in the
successful use of SEB studies in advocacy, in building and maintaining public support,
and in strengthening the NMHS brand. It has looked at the different audience
segments, both external and internal, that an NMHS might wish to reach and has also
reviewed the optimum manner of presentation appropriate to a variety of
communication media. Identification of key target audiences and tailoring the
communication strategy accordingly will greatly assist the usefulness and impact of an
SEB assessment.
REFERENCES
International Civil Aviation Organization, 2014: The Convention on International Civil Aviation.
Annex 3: Meteorological Service for International Air Navigation, http://www.icao.int/
safety/airnavigation/NationalityMarks/annexes_booklet_en.pdf.
CHAPTER 9. SOCIOECONOMIC BENEFIT STUDY STEP 10:
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123
Perrels, A., T. Frei, F. Espejo, L. Jamin and A. Thomalla, 2013: Socioeconomic benefits of weather
and climate services in Europe. Advances in Science and Research, 10:65–70, doi:10.5194/
asr-10-65-2013.
Public Library of Science, 2014: Article-level metrics measure the dissemination and reach of
published research articles, http://www.plos.org/innovation/article-level-metrics/.
Rogers, D. and V. Tsirkunov, 2013: Weather and Climate Resilience: Effective Preparedness through
National Meteorological and Hydrological Services. Directions in Development. Washington,
D.C., World Bank.
World Meteorological Organization, 2013: The Role and Operation of National Meteorological and
Hydrological Services (EC-65, 2013). Executive Council sixty-fifth session, Annex II, 15–23
May, Geneva, ftp://ftp.wmo.int/Documents/PublicWeb/mainweb/meetings/cbodies/
governance/executive_council_reports/english/pdf/1118_en.pdf#page=245.
———, 2014: Atlas of Mortality and Economic Losses From Weather, Climate and Water Extremes
(1970–2012) (WMO-No. 1123). Geneva.
CHAPTER 10. LOOKING FORWARD
Chapter 1. Introduction
Chapter 2. Met/hydro services
Chapter 3. Purpose of SEB studies
Chapter 4. Designing SEB studies
Chapter 5. Economic essentials
Chapter 6. Benefits
Chapter 7. Costs
Chapter 8. BCA
Chapter 9. Communications
Chapter 10. Looking forward
Met/hydro services enhance economic
development and will no doubt play a crucial
role in how we adapt to changes the future
brings. Those changes may well be substantial.
A recent report (Global Commission on the
Economy and Climate, 2014) reminds us that
over the next 15 years global production
(defined as GDP) will grow by more than half, a
billion more people will come to live in cities,
and rapid technological advance will continue
to change businesses and lives. In addition,
climate change is already having serious
economic consequences, especially in more
exposed areas of the world. The SEB analysis
described in this publication can help identify
priority needs for investments to ensure reliable
met/hydro services.
The Madrid Conference of 2007 (see Chapter 1), a substantial milestone of global
collaboration for improving practice, inspired a burst of interest in SEB studies of met/
hydro services, for example the work undertaken in Europe under the WMO Regional
Association VI (summarized in Perrels et al., 2013a). Since then and at least partially
motivated by the Madrid Conference, new levels of collaboration between WMO and
development partners, particularly the World Bank Group, are facilitating not only
better and more knowledge exchange, but also increased investment in modernizing
met/hydro services. It is hoped that this publication will further drive an intensification
of these efforts.
This publication endeavours to raise awareness, increase understanding and provide
practical guidance for evaluating, demonstrating and enhancing the benefits of met/
hydro services. While it attempts to capture the currently available wealth of
experience and expertise across different countries, sectors and disciplines, it is not the
end point for developing global knowledge on SEB analysis of met/hydro services.
Rather it is another substantial milestone.
10.1
GUIDING INCREASED BENEFIT DELIVERY BY NATIONAL
METEOROLOGICAL AND HYDROLOGICAL SERVICES
10.1.1
Supporting sustainable development through better-informed
services
Met/hydro services play a key role in building more resilient societies and should be
recognized as such. However, beyond the obvious appeal for advocating with financial
Chapter 10. Looking forward
125
decisionmakers, politicians and the public, the core value of SEB analysis of met/hydro
services lies in the process rather than the final numerical results. Application and
utilization of such analysis should be treated as a continuous process that leads not
only to improvement of the effectiveness of NMHSs, but of performance in conducting
and exploiting SEB analysis methodologies themselves. These processes are sources of
valuable information for improving the effectiveness of services in all phases of the
value chain and prioritizing focal areas of service innovation (Perrels et al., 2013b).
Public financing is increasingly under pressure and will likely continue to be for the
foreseeable future (International Monetary Fund, 2014), raising the need for welldesigned, targeted and communicated SEB studies. The economic context in which they
operate should be understood by NMHSs, and they should regularly review how they use
their limited resources to improve cost efficiency while meeting priority user demands.
Particularly in middle- and low-income countries, NMHSs would benefit from routine
inclusion in national development, poverty reduction and climate adaptation plans. If
national accounting systems and macroeconomic equilibrium models consider
potential, realized and avoided impacts of weather and climate, government budgets
and financial plans will likely include provisions for providing and enhancing met/
hydro services. This foresight is, however, currently not usually the case; for example,
national accounting does not adequately measure disaster impacts (United Nations
Office for Disaster Risk Reduction, 2013) or natural capital assets (Wealth Accounting
and the Valuation of Ecosystem Services, 2014); the optimal management of both,
however, require met/hydro services. A changing climate makes consideration of
anticipated benefits essential for the future.
Better SEB studies will therefore not only send a strong message of the need for
adequate resourcing for the delivery of met/hydro services, but will also contribute to
guaranteeing the sustainability of such services as part of longer-term development.
While the World Bank Group is convinced that modernizing NMHSs in developing
countries is a high-value investment requiring sufficient scope to be transformative, it
also emphasizes that government commitment to sustained financing of operations
and maintenance of basic met/hydro services is needed.
10.1.2
Decisionmaking needs good data
Data and information availability, in addition to resource availability, will always be a
limiting factor for selecting the type and framing the detail of an SEB study. To build
confidence with stakeholders in processes and results, three important approaches
should be employed:
(a) Recognize limitations from the beginning;
(b)Transparently justify and document assumptions used to offset data
shortcomings;
(c) Corroborate results through application of multiple methods.
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For SEB analysis, NMHSs should approach the collection and management of the
required data in a similar fashion to met/hydro data. Long-term commitment and
investments are needed to ensure reliable and regular acquisition of socioeconomic
information through a mix of approaches. Systems are needed for data quality
management and consistency, and a transparent and open approach (for example,
through a willingness to share) helps ensure reliability through external review and
use, ultimately building confidence in both the input information and resultant studies.
Therefore, NMHSs need to be proactive in assembling the data for SEB studies, which
may entail a change of mindset and explicit commitments of resources (see Chapter 4).
It cannot be expected that an NMHS would hold all necessary data, so closer
collaboration will be needed with relevant partners/agencies such as ministries of
finance and national statistical offices.
10.1.3
Increasing value with better access to services
It is clear that if met/hydro products are not being used, they have no value. The value
chain used in this publication indicates that value is only realized once information is
collected, processed, delivered and a decision or action is taken based on the
information. It follows that the more met/hydro products are used, the more value
they will deliver. Efforts to increase use should therefore be pursued.
In 1995, WMO and its Members recognized that to better enable provision of services
to help protect life, property and well-being, certain meteorological data should be
freely exchanged at the international level (WMO, 1995). This was followed by similar
considerations regarding hydrological data four years later (WMO, 1999).
Characterizing basic meteorological data and services as public goods, resulting in a
liberal approach towards data policy with free-of-charge provision of infrastructure
data and products, is very likely to generate greater SEBs (Weiss, 2002). As
consumption under open-data policies is non-rival, the marginal cost of supplying
information to additional users is close or equal to zero, and the costs of exclusion from
use (that is, controlling proliferation of charged data) are too high, if not impracticable
(Rogers and Tsirkunov, 2013).
Despite delivering clear contributions to social welfare and positive public and private
externalities, 25 the concept that using public financing to provide free met/hydro data
and basic services increases economic value is not always immediately apparent to
governments. However, experience shows that an open-data policy, meaning
information is both technically accessible and legally licensed to permit commercial
and non-commercial use and reuse without restrictions (World Bank, 2014), tends to
lead to a dramatic increase in the use of the data. In 2006, the Norwegian
Meteorological Institute decided to stop charging for weather and climate data to
facilitate a broader use of its data and products. In addition to adopting open-data and
open-access policies, in 2007 it partnered with the Norwegian National Broadcaster to
25
Also called "external benefits" or "external economy", this refers to positive effects on a third
party who/that did not make the decision of applying an open-data approach; for example
sectoral and business opportunities through data refinement and reuse for user-specific products.
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Chapter 10. Looking forward
Average daily access
(millions)
20
15
10
5
0
2008
2009
2010
2011
2012
2013
2014
Figure 10.1. Growth in usage of the Norwegian Meteorological Institute's
web services following adoption of open-data (2006) and
open-access (2007) approaches
Source: Adapted from Figure 6 of Lyng et al. (2014)
foster commercial free and easier domestic and international access to its data and
products, for both use and reuse, through the Internet. This policy has not only led to
exponential increases in the use of the Norwegian Meteorological Institute’s data and
products (see Figure 10.1), but has contributed to the institute having the best public
reputation of all Norwegian governmental institutions for nine years running (based
on official annual polls), as well as high staff morale (Lyng et al., 2014).
Modern technology enables increased access to met/hydro products and services. It is
important that NMHSs rapidly embrace evolving innovations to ensure continued and
growing product use, as FMI has done to adapt to domestic tripling of smartphone
ownership from 2011 to 2014, and a quadrupling of tablet ownership from 2012 to
2014, as shown in Figure 10.2 (Harjanne and Ervasti, 2014).
Average monthly web users
(millions)
4
Total Internet users
3
2
Desktop web access
1
Mobile apps
Mobile web
0
2010
2011
2012
2013
2014
Figure 10.2. Growth in mobile and mobile application users of the Finnish
Meteorological Institute’s web products, 2010–2014
Source: Adapted from Figure 2 of Harjanne and Ervasti (2014)
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Increasing value with better utilization of services
Just because met/hydro products and services are being accessed and used more does
not necessarily mean they are being fully or better exploited. If information is
misunderstood or misinterpreted, it could even lead to poor decisionmaking, resulting
in negative value. The third World Climate Conference highlighted that capacitybuilding to disseminate, communicate, understand and utilize met/hydro services is as
important as the need to further develop met/hydro services themselves, reflected as a
key element of the Global Framework for Climate Services (World Climate
Conference-3, 2009).
Assumptions of perfect decisionmaking based on all the information available are
generally not realistic. For example, if a perfect agrometeorological forecast is
provided for the growing season, it is unlikely that farmers will cultivate the optimal
crops at the optimal times (Stewart, 1997; Letson et al., 2001). By jointly exploring
shortcomings both in met/hydro products and the decisions they inform, NMHSs
teams and their partners can optimize investments and therefore benefits realized
through shared roles.
The higher the quality of met/hydro services, the more value they can deliver. In a
mutually reinforcing modernization strategy, SEB studies will help inform the design
and implementation of investments to improve services, leading to increased
recognition, use and therefore value of services. Scientific and technological advances
should be operationalized for maximum benefit. For example, probabilistic forecasts
enable better decisionmaking than deterministic forecasts in the case of early warning
by allowing false alarm rates to be set to levels acceptable to stakeholders, as opposed
to strict threshold-driven targeting (Pappenberger et al., 2014). Efforts such as the
WMO World Weather Research Programme’s High Impact Weather Project
(HIWeather), which aims to increase resilience by improving impact forecasts and
enhancing their communication and utility in social, economic and environmental
applications, should be pursued to increase met/hydro service benefits at local,
national, regional and global levels.
National Meteorological and Hydrological Services rely on efficient data and
information exchange from global to local levels, within the overall framework of
WMO WWW. Global models provide input for regional models which, in turn, provide
guidance for national/local forecasting. Such cascading approaches ensure that all
NMHSs have access to the latest technology and methodologies, without burdening
most NMHSs with the high costs of maintaining and operating global and regional
numerical modelling systems. Currently, the viability of such global services depends
on the voluntary contribution of the advanced service providers. The structure is under
increasing stress from budget constraints, especially in the major traditional provider
countries. To support these systems and improve the weather and met/hydro services
available to the developing world, it would be worth exploring public financing
models for global goods, utilizing a number of approaches described in this
publication.
Chapter 10. Looking forward
10.2
129
ENHANCING THE QUALITY AND UTILIZATION OF
SOCIOECONOMIC BENEFIT ANALYSIS
Increasingly, NMHSs need to confront new realities in their operational contexts, and
not just those related to public financing. Specifically, rapid changes and innovations in
information technology; globalization of societal, economic and technological systems;
and the changing climate are some of the key processes facing met/hydro service
providers. These present both risks and opportunities, and economics as a discipline
can help NMHSs navigate changes in an optimal manner. Risk management should be
a powerful instrument for development, not only by building resilience, but also by
taking advantage of opportunities for improvement (World Bank, 2013).
Every country, no matter what the level of development or capacity of the NMHS, can
benefit from strengthening its application and utilization of SEB assessments of met/
hydro services. The continuum of approaches outlined in this publication provides
opportunities to employ methods across a range of resource and expertise availability.
The capacity for SEB analysis exists in all countries, either within or outside their
NMHSs. The sourcing and leveraging of this capacity must depend on the scope of the
decision to be informed.
10.2.1
Linking communities
Met/hydro SEB assessment requires an interdisciplinary approach that brings together
a number of different expert groups and stakeholders. The strengthening of linkages
between the met/hydro and socioeconomic technical communities is of particular
importance, as are joint approaches to communicating results externally.
Associated with the partners and efforts engaged in the development of this
publication, it is planned to establish a website to ease accessibility to it, but more
importantly to provide a platform for the exchange of ideas, experiences and new
studies.
The Global Framework for Climate Services – with its primary focus on better access
and use of climate information by users, encouragement of global, free and open
exchange of climate-relevant data as international public goods, and basis in
partnership – provides a broader platform within which to promote the use of SEB
studies to improve met/hydro services. Spin-offs from GFCS, such as the Climate
Services Partnership (http://www.climate-services.org/) have already engaged key
members of the extended community to better link efforts (Pappenberger et al., 2014).
10.2.2
Monitoring and evaluation
Analysis of SEBs should form an integral component of the monitoring and evaluation
systems of NMHSs. Existing systems may need to be adapted to better capture the
relevant baselines and the user decisions being made utilizing met/hydro products and
services. Monitoring must, therefore, include outcomes and results, not just outputs
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Box 10.1: Using crowdsourcing to monitor use and satisfaction
in the United Kingdom
The United Kingdom Met Office currently uses social media networks such as Facebook and
Twitter, as well as the organization’s website, to monitor the effectiveness of, and to
improve, weather and climate services. This monitoring technique enables the Met Office to
better understand how their forecasts are perceived and allows engagement with the public
in real time. Social media reports are also used to assess the impacts of the weather and
these are added to evidence collected to assess warnings. The Met Office regularly reviews
monitoring and evaluation systems to ensure they are taking advantage of the latest
technology, combined with more traditional methods (radio, television and print) to ensure
a holistic approach to understanding the needs of the public, emergency responders and
private sector.
Source: Pinder (2014)
such as the number of forecasts made or warnings sent. In most cases, this last phase
of the value chain is outside the direct responsibility of the NMHS, lying primarily with
the users. Monitoring and evaluation partnerships are thus needed.
New technologies to monitor and assess uptake, use, satisfaction and ultimately the
benefits of data from met/hydro products and services should be employed – for
example crowdsourcing (see Box 10.1), big data, cloud computing, and the like. The
further along the value chain that data can be captured (referring again to outcomes
and results), the better the SEB analysis will be informed.
The tools, assumptions, and processes of SEB analysis can always be improved. Ex-post
SEB studies on met/hydro services are therefore needed to improve future
performance. This could involve, among other activities, continuous monitoring,
collection of data to revisit methodologies, integration with non-economic methods
(for example, other social sciences), and identification of new benefits, all under a
continuous process.
10.3
GOALS FOR THE FUTURE
As national implementation of the 2014 WMO Strategy for Service Delivery is pursued,
SEB analysis will become increasingly important to inform planning and investment in
NMHSs with the ultimate goal of improving services. Concurrently, a number of global
processes and agreements will likely help raise the profile and urgency of
strengthening met/hydro services, including the post-2015 framework for disaster risk
reduction, the post-2015 sustainable development goals, the New Universal Climate
Agreement in 2015 (under the auspices of the United Nations Framework Convention
on Climate Change) and continued development and implementation of GFCS.
Considering this growing interest and demand, the agencies and authors involved in
this publication envision a number of developments over the next few years.
Chapter 10. Looking forward
131
To achieve the strengthening of these services, the community of practitioners working
in the field should expand and diversify, facilitated by interactive web platforms and
resources. This network should include experts from a number of disciplines including
met/hydro services, economics, social sciences, public administration and more, and
ranging across professional responsibilities from managers to technical specialists, and
researchers to civil society representatives. It is hoped that professional societies, for
example those focusing on issues such as meteorology and environmental economics,
will actively engage and move the effort forward.
The methodologies described in this publication, potentially added to and improved
upon through interactive knowledge-sharing, will be applied in as many countries as
possible. This effort will generate more experiences and case studies, eventually
providing a knowledge base covering all relevant sectors and contexts. The existing
case studies should also be revisited to assess the application and performance of
approaches, informing refinements of methodologies and assumptions.
To achieve these goals, the pool of people across disciplines available to provide
technical support and training should be widened. Relevant managers and staff will
benefit from the integration of the training of SEB analysis methodologies within
WMO, NMHSs and partners. It would be particularly valuable if the WMO Regional
Training Centres were to introduce basic modules in meteorological economics across
a range of their professional and technical training courses. To further support national
capacity, twinning arrangements for lower capacity NMHSs to benefit from the
expertise of higher capacity NMHSs could also be facilitated.
To support longer-term utilization and refinement of SEB analysis for met/hydro
services, it is hoped that the academic world better takes up the topic to maximize the
exposure and interest of the next generation of met/hydro professionals. This
publication, for example, could be translated into a teaching resource. Students of
economics, public management, meteorology, hydrology and many more disciplines
could benefit from, but also contribute to, inclusion of the topic in academic curricula.
None of the above will be possible without dedicated financial resources, and such
resources can only be made available if the SEB agenda is considered a priority by the
involved parties. Both NMHSs and their governing ministries will need to allocate
budgets, as will development partners in their programmes and projects. As the age
old expression goes, “one has to spend money to make money”; this wisdom also
applies to utilizing SEB assessment to improve cost efficiency of met/hydro services.
With the case studies reviewed in this publication indicating that met/hydro services
deliver benefits relative to costs of ratios ranging from 2 to 1 to 36 to 1, clearly there are
great benefits in assessing and understanding how to optimize the value of met/hydro
services. It is therefore worth investing in a better understanding of how to invest!
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Harjanne, A. and T. Ervasti, 2014: Analysis of User Trends and Behaviour in Online and Mobile Weather
and Climate Services. FMI reports no.2014:10. Helsinki, Finnish Meteorological Institute.
International Monetary Fund, 2014: World Economic Outlook October 2014: Legacies, Clouds,
Uncertainties. World Economic and Financial Surveys. Washington, D.C.
Letson, D., I. Llovet, G.P. Podestá, F. Royce, V. Brescia, D. Lema and G. Parellada, 2001: User
perspectives of climate forecasts: Crop producers in Pergamino, Argentina. Climate Research,
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Lyng, K., A. Sund and H. Futsaether, 2014: Open Data at the Norwegian Meteorological Institute. MET
report commissioned for the World Bank Group. Oslo, Norwegian Meteorological Institute.
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Perrels, A., A. Harjanne, V. Nurmi, K. Pilli-Sihvola, C. Heyndricx and A. Stahel, 2013b: Sector
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Pinder, N., 2014: Personal communication. 17 October 2014.
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Climate Forecasts (R.W. Katz and A.H. Murphy, eds.). Cambridge, Cambridge University Press.
United Nations Office for Disaster Risk Reduction, 2013: From Shared Risk to Shared Value –
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Wealth Accounting and the Valuation of Ecosystem Services, 2014,
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Weiss, P., 2002: Borders in Space: Conflicting Public Sector Information Policies and Their Economic
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Resolution 40. Geneva.
World Climate Conference-3, 2009: Conference statement: Summary of the expert segment.
World Climate Conference-3, 31 August–4 September. Geneva.
World Meteorological Organization, 1995: Abridged Final Report with Resolutions of the Twelfth
World Meteorological Congress (WMO-No. 827). Resolution 40. Geneva.
———, 1999: Abridged Final Report with Resolutions of the Thirteenth World Meteorological Congress
(WMO-No. 902). Resolution 25. Geneva.
APPENDIX A. GLOSSARY OF TECHNICAL TERMS
Note:
In certain instances, the authors have summarized or edited glossary definitions as needed
for contextualization.
Adaptation: The process of adjustment to actual or expected climate and its effects. In
human systems, adaptation seeks to moderate or avoid harm or exploit
beneficial opportunities. In some natural systems, human intervention may
facilitate adjustment to expected climate and its effects. “Incremental
adaptation” refers to adaptation actions where the central aim is to maintain
the essence and integrity of a system or process at a given scale.
“Transformational adaptation” refers to adaptation that changes the
fundamental attributes of a system in response to climate and its effects
(Intergovernmental Panel on Climate Change (IPCC), 2014).
Adaptation benefits: The avoided damage costs or the accrued benefits following the
adoption and implementation of adaptation measures (IPCC, 2007).
Agrometeorology: The study of the interaction between meteorological and
hydrological factors, on the one hand, and agriculture in the widest sense,
including horticulture, animal husbandry and forestry, on the other
(WMO, 1992). Agrometeorology is a sub-field of meteorology and includes
agroclimatology.
Atmosphere: Gaseous envelope which surrounds the Earth (WMO, 1992).
Avoided cost method: A valuation method that assesses actual or imputed costs for
preventing environmental deterioration by alternative production and
consumption processes, or by the reduction of or abstention from economic
activities (OECD, 2008); for example, measuring the benefits of reduced air
pollution by assessing the cost of installing indoor air purifiers.
Basic services: Those services provided by National Meteorological and Hydrological
Services in discharging their governments’ sovereign responsibility to protect
the life and property of their citizens, to contribute to their general welfare and
the quality of their environment and to meet their international obligations
under the Convention of the World Meteorological Organization and other
relevant international agreements (WMO, 1990).
Benchmarking: A process in which a business evaluates its own operations (often
specific procedures) by detailed comparison with those of another business
(especially a competitor), in order to establish best practices and improve
performance; the examination and emulation of other organizations' strengths
(Oxford English Dictionary).
Benefit: A quantified gain of an action (Tietenberg and Lewis, 2009; from benefit–cost
analysis).
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Benefit–cost analysis: The quantification of the total social costs and social benefits of
a policy or a project, usually in money terms. The costs and benefits concerned
include not only direct pecuniary costs and benefits, but also externalities,
meaning external effects not traded in markets. These include external costs,
for example, pollution, noise and disturbance to wildlife, and external benefits
such as reductions in travelling time or traffic accidents. Benefit–cost analysis is
often used to compare alternative proposals. If the total social benefits of an
activity exceed total social costs, this can justify subsidizing projects that are
not privately profitable. If the total social costs exceed total social benefits, this
can justify preventing projects even when these would be privately profitable
(Black et al., 2012; from cost–benefit analysis).
Benefit transfer: Transferring benefit estimates developed in one context to another
context as a substitute for developing entirely new estimates (Tietenberg and
Lewis, 2009).
Climate: Synthesis of weather conditions in a given area, characterized by long-term
statistics (mean values, variances, probabilities of extreme values, and the like)
of the meteorological elements in that area (WMO, 1992).
Climate change: Climate change refers to a change in the state of the climate that can
be identified (for example, by using statistical tests) by changes in the mean
and/or the variability of its properties, and that persists for an extended
period, typically decades or longer. Climate change may be due to natural
internal processes or external forcing such as modulations of the solar cycles,
volcanic eruptions and persistent anthropogenic changes in the composition
of the atmosphere or in land use (IPCC, 2014).
Climate data: Historical and real-time climate observations, along with direct model
outputs covering historical and future periods. Information about how these
observations and model outputs were generated (metadata) should
accompany all climate data (WMO, 2014a).
Climate information: Climate data, climate products and/or climate knowledge
(WMO, 2014a).
Climate prediction: A climate prediction or climate forecast is the result of an attempt
to produce (starting from a particular state of the climate system) an estimate
of the actual evolution of the climate in the future, for example, at seasonal,
interannual or long-term timescales. Because the future evolution of the
climate system may be highly sensitive to initial conditions, such predictions
are usually probabilistic in nature (IPCC, 2014).
Climate projection: A climate projection is the simulated response of the climate
system to a scenario of future emission or concentration of greenhouse gases
and aerosols, generally derived using climate models. Climate projections are
distinguished from climate predictions by their dependence on the emission/
concentration/radiative-forcing scenario used, which is in turn based on
Appendix A. Glossary of technical terms
135
assumptions concerning, for example, future socioeconomic and technological
developments that may or may not be realized (IPCC, 2014).
Climate product: A derived synthesis of climate data. A product combines climate data
with climate knowledge to add value (WMO, 2014a).
Climate scenario: A plausible and often simplified representation of the future climate,
based on an internally consistent list of climatological relationships that has
been constructed for explicit use in investigating the potential consequences
of anthropogenic climate changes, often serving as input to impact models.
Climate projections often serve as the raw material for constructing climate
scenarios, but climate scenarios usually require additional information such as
the observed current climate (IPCC, 2014).
Climate services: The provision of climate information in a way that assists
decisionmaking by individuals or organizations. A service requires appropriate
engagement along with an effective access mechanism and must respond to
user needs (WMO, 2014a). Note: This publication uses the term met/hydro services
as opposed to climate services, except when the term climate services is germane to
the topic under discussion, for example, in relation to GFCS and CSP.
Climate variability: Climate variability refers to variations in the mean state and other
statistics (such as standard deviations, the occurrence of extremes, and the
like) of the climate on all spatial and temporal scales beyond that of individual
weather events. Variability may be due to natural internal processes within the
climate system (internal variability), or to variations in natural or
anthropogenic external forcing (external variability) (IPCC, 2014). See also
climate change.
Climatology: Study of the mean physical state of the atmosphere together with its
statistical variations in both space and time as reflected in the weather
behaviour over a period of many years (WMO, 1992). Climatology is a subfield
of meteorology.
Conjoint analysis: A survey-based technique that derives WTP by having respondents
choose between alternate states of the world where each state of the world
has a specified set of attributes and a price (Tietenberg and Lewis, 2009).
Consumer surplus: The excess of the benefit a consumer gains from purchase of a good
or service over the amount paid for the good or service (Black et al., 2012).
Contingent ranking: A valuation technique that asks respondents to rank alternative
situations involving different levels of environmental amenity (or risk). These
rankings can then be used to establish trade-offs between more of the
environmental amenity (or risk) and less (or more) of other goods that can be
expressed in monetary terms (Tietenberg and Lewis, 2009).
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Contingent valuation: A survey method used to ascertain WTP for services or
environmental amenities (Tietenberg and Lewis, 2009).
Cost: The value of the inputs needed to produce any good or service, measured in
some units or numeraire, generally money (Black et al., 2012).
Cost-effectiveness: The achievement of results in the most economical way. This
approach assesses efficiency by checking whether resources are being used to
produce any given results at the lowest possible cost. Cost-effectiveness is
most relevant as a concept of efficiency in cases such as the provision of
defence, education, health care, policing or environmental protection, where it
is sometimes difficult to measure the monetary value of the results achieved
(Black et al., 2012).
Customer (of meteorological or hydrological services): The person or organization
which pays for products and services and agrees on the specifications for
delivery through a customer–supplier agreement or service-level agreement.
The customer may or may not be the user (WMO, 2014b).
Customer satisfaction survey: A survey designed to measure how products and
services supplied by a company (or met/hydro service provider) meet or
surpass customer expectation (American Marketing Association, 2014; from
“customer satisfaction”).
Demand: The desire and ability to acquire a good or service, or the quantity of a good
or service that economic agents are willing to buy at a given price
(Black et al., 2012).
Discounting: Placing a lower value on future receipts than on the present receipt of an
equal sum. The fundamental reason for discounting the future is impatience:
immediate consumption is preferred to delayed consumption (Black et al.,
2012; from “discounting the future”).
Discount rate: The interest rate at which future benefits or costs are discounted to find
their present value (Black et al., 2012). See also discounting.
Double counting: An error that occurs when a total is obtained by summing gross
amounts instead of net amounts. For example, finding the total product of an
economy by adding up the gross sales of each enterprise, without subtracting
purchases of inputs from other enterprises, involves double counting. As firms
buy large amounts of fuel, materials, and services from one another, simply
adding gross outputs results in double, or multiple, counting of output.
Double counting is avoided by subtracting purchased inputs from gross
output to get value added for each enterprise. The national product is total
value added (Black et al., 2012).
Economic efficiency: A general term that expresses the notion that all available
resources are allocated optimally. Economic efficiency in this sense is purely
Appendix A. Glossary of technical terms
137
descriptive, and does not provide a precise definition or test. Pareto efficiency
is a formalization of the concept of economic efficiency that provides a method
of testing for efficiency (Black et al., 2012).
Economies of scale: The factors which make it possible for larger organizations or
countries to produce goods or services more cheaply than smaller ones.
Economies of scale that are internal to firms are due to indivisibilities and the
division of labour. Economies of scale that are external to firms, but operate at
the national level, arise from similar causes; there is scope for more specialist
services in a larger economy than in a small one (Black et al., 2012).
Economies of scope: The benefits arising from engaging in related activities. These are
similar to economies of scale, but whereas with economics of scale cost savings
arise from carrying out more of the same activity, with economics of scope cost
savings arise from engaging in related activities (Black et al., 2012).
Efficiency: Obtaining the maximum output for given inputs. Efficiency in consumption
means allocating goods or services between consumers so that it would not be
possible by any reallocation to make some people better off without making
anybody else worse off. Efficiency in production means allocating the available
resources between industries so that it would not be possible to produce more of
some goods or services without producing less of any other (Black et al., 2012).
Ex ante: Literally translated from Latin: from before. The term describes activities (for
example, actions, decisions, formation of expectations) that are undertaken
before the state of nature is revealed. For instance, an ex-ante SEB study
involves the analysis of potential benefits of a new or improved met/hydro
service before it is actually available to user communities. Ex ante is contrasted
with ex post, meaning as viewed after the event (Black et al., 2012).
Ex post: Literally translated from Latin: from after. The value of a variable, or of a
decision made, as it appears after the outcome of randomness has been
realized, that is, what actually occurred. Ex post is contrasted with ex ante,
which means looking at things before the event (Black et al., 2012).
Expenditures: Spending, by consumers, investors or the government. Consumer
expenditure is restricted to purchasing real goods and services; acquiring
assets of making transfers to others by individuals does not count as
expenditure. Government expenditure is treated differently; some government
expenditure is on real goods and services, but government interest payments
and transfer payments to individuals, such as pensions, are counted as
government expenditure, and government spending is not clearly divided
between current and capital account items, possibly because these are hard to
distinguish. National expenditure is what a country spends (Black et al., 2012).
Exposure: The presence of people, livelihoods, species or ecosystems, environmental
functions, services, and resources, infrastructure, or economic, social, or cultural
assets in places and settings that could be adversely affected (IPCC, 2014).
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External cost: A cost arising from any activity which does not accrue to the person or
organization carrying out the activity. Negative externalities (external costs)
cause damage to other people or the environment, for example by radiation,
river or air pollution, or noise, which does not have to be paid for by those
carrying out the activity (Black et al., 2012; from “externality”). See also
externality.
Externality: A cost or benefit arising from any activity which does not accrue to the
person or organization carrying out the activity. Negative externalities
(external costs) cause damage to other people or the environment, for
example by radiation, river or air pollution, or noise, which does not have to be
paid for by those carrying out the activity. Positive externalities (external
benefits) are effects of an activity which are pleasant or profitable for other
people who cannot be charged for them, for example fertilization of fruit trees
by bees, or the public’s enjoyment of views of private buildings or gardens
(Black et al., 2012).
Forecast: A statement of expected meteorological (or hydrological) conditions for a
specific period and for a specific area or portion of air space (WMO, 1992).
Global Framework for Climate Services: A global partnership of United Nations and
international agencies (led by WMO), governments, regional organizations
and stakeholders, established by unanimous decision at the third World
Climate Conference held in 2009 that seeks to enhance the production and
application of climate services worldwide (WMO, 2014a).
Hazard: The potential occurrence of a natural or human-induced physical event or
trend, or physical impact, that may cause loss of life, injury, or other health
impacts, as well as damage and loss to property, infrastructure, livelihoods,
service provision, and environmental resources (IPCC, 2014).
Hedonic pricing: The method of pricing a good for estimating the value of the
individual characteristics that form the good. For example, a house would be
seen as comprised of a number of rooms, a garden, and a location. The values
of the characteristics are summed to derive a price for a good (Black et al.,
2012).
Hindcast: A retrospective forecast issued by a model based on information available at
a prior time (Planque et al., 2003, p. 213).
Hydrology: Science that deals with the waters above and below the land surfaces of
the Earth, their occurrence, circulation and distribution, both in time and
space, their biological, chemical and physical properties, and their interactions
with their environment including their relation to living beings (WMO, 2012a).
Hydrology is often subdivided into “scientific” and “operational” hydrology.
Hydrological cycle: Succession of stages through which water passes from the
atmosphere to the Earth and returns to the atmosphere: evaporation from the
Appendix A. Glossary of technical terms
139
land, sea or inland water, condensation to form clouds, precipitation,
interception, infiltration, percolation, runoff, accumulation in the soil or in
bodies of water, and re-evaporation (WMO, 2012a).
Hydrological services: The provision of information and advice on the past, present
and future state of rivers, groundwater and other inland waters, including but
not limited to streamflow, river and lake levels, and water quality (this
publication).
Hydrometeorology: Study of the atmospheric and land phases of the hydrological
cycle, with emphasis on the interrelationships involved (WMO, 2012a).
Joint costs: Costs which are shared by two or more products. It may be possible for a
firm to measure the marginal cost of each product separately, but joint costs
make it impossible to measure the average cost of each product (Black et al.,
2012).
Loss: The result of a business operation where expenditures exceed receipts. Business
losses may arise internally, through failure to produce enough of anything the
market will buy to cover production expenses, or externally, through failure of
others to pay bills due, or to repay debts. (Black et al., 2012).
Macroeconomics: The macro aspects of economics, concerning the determination of
aggregate quantities in the economy. Macroeconomics considers what
determines total employment and production, consumption, investment in
raising productive capacity, and how much a country imports and exports. It
also asks what causes booms and slumps in the short run, and what
determines the long-term growth rate of the economy, the general level of
prices, and the rate of inflation. Macroeconomics considers how these matters
can and should be influenced by government through monetary and fiscal
policies (Black et al., 2012).
Marginal benefit: The additional benefit from an increase in an activity. This is the
addition to total benefit resulting from a unit increase if it varies discretely, or
the addition to total benefit per unit of the increase, if it varies continuously.
Marginal private benefit is marginal benefit accruing to the person or firm
deciding on the scale of the activity, excluding any external benefits; marginal
social benefit includes external benefits as well as private benefits accruing to
the decisiontaker (Black et al., 2012).
Marginal cost: The additional cost from an increase in an activity. This is the addition
to total cost resulting from a unit increase in output if it varies discretely, or the
addition to total cost per unit of the increase, if it varies continuously. Marginal
cost may be short run, when only some inputs can be changed, or long run,
when all inputs can be adjusted. Marginal private cost is marginal cost falling
on the person or firm deciding on the scale of the activity, excluding any
external costs; marginal social cost includes external costs as well as private
cost falling on the decisionmaker (Black et al., 2012).
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Meteorology: The science of the atmosphere dealing in particular with its structure
and composition, interactions with the oceans and land, movements
(including weather-forming processes), weather forecasting, climate variability
and climate change (WMO, 1996).
Meteorological services: The provision of information and advice on the past, present
and future state of the atmosphere including information on temperature,
rainfall, wind, cloudiness, air quality and other atmospheric variables and on
the occurrence and impacts of significant weather and climate phenomena
such as storms, floods, droughts, heatwaves and cold waves (this publication).
Met/hydro services: The provision of weather, climate, and hydrological information
and products. See also climate services.
Microeconomics: The micro aspects of economics, concerning the decisionmaking of
individuals. Microeconomics analyses the choices of consumers (who can be
individuals or households) and firms in a variety of market situations. Its aim is to
explore how choices should be made, and to provide an explanation of the
choices that are made. Microeconomics also considers economics composed of
individual decisionmakers, and studies the existence and properties of economic
equilibrium. The effect of government choices upon consumers and firms is also
analysed, with the aim of understanding economic policy (Black et al., 2012).
Monte Carlo method: A method of investigating the behaviour of economic models
which are too complicated for analytical solutions to be possible. A system is
started off at a large number of initial positions chosen at random, and
followed through a numerical simulation to see how it evolves. Monte Carlo
methods can be used to check whether a system has an equilibrium, and
whether this is stable for any starting point, or some limited region of possible
starting points (Black et al., 2012).
National Hydrological Service: An organization with national responsibility for river,
lake and other hydrological observation, data management, research,
modelling and streamflow forecasting and warning responsibilities (WMO,
1992, 2000, 2001, 2012b). The functions of the NHS are similar to those of the
National Meteorological Service but focused mainly on the surface phase of
the hydrological cycle; NHSs are often located with water supply or river
management ministries.
National Meteorological and Hydrological Service: Refers to an NMS or NHS, or an
organization which combines the functions of both (WMO, 1992, 2000,
2012b). The plural, NMHSs, refers to multiple organizations (NMHS, NMS,
and NHS).
National Meteorological Service: An organization established and operated primarily
at public expense to carry out those national meteorological and related
functions which governments accept as a responsibility of the state in support
of the safety, security and general welfare of their citizens and in fulfilment of
Appendix A. Glossary of technical terms
141
their international obligations under the Convention of the World
Meteorological Organization (WMO, 1992, 2000, 2012b; Zillman, 1999).
The primary functions of an NMS are usually identified as observation, data
archival, research, service provision and international cooperation.
Net benefits: The excess of benefits over costs resulting from some allocation
(Tietenberg and Lewis, 2009).
Net present value: The present value of a security or an investment project, found by
discounting all present and future receipts and outgoings at an appropriate
rate of discount (see discount rate). If the NPV calculated is positive, it is
worthwhile investing in a project (Black et al., 2012).
Non-excludability: A property of a good or service that exists when no individual or
group can be excluded from enjoying the benefits that good or service may
confer, whether they contribute to its provision or not (Tietenberg and
Lewis, 2009).
Non-market goods and services: Goods and services not distributed through markets
(Black et al., 2012, from “non-marketed economic activities”), for example,
clean air and water, scenic vistas and beach visits.
Non-market valuation: The economic valuation of goods and services not distributed
through markets (Black et al., 2012; from “non-marketed economic activities”).
Methods can be based on either revealed-preference or stated-preference
methods, and assessed either directly or indirectly.
Non-rivalry: A property of a good or service that exists when consumption by one
consumer does not reduce the quantity available for consumption by any other
(Black et al., 2012; from “public good”).
Nowcast: A description of current weather and a short-period (one to two hours)
forecast (WMO, 1992).
Numerical weather prediction: The forecasting of the behaviour of atmospheric
disturbances by the numerical solution of the governing fundamental
equations of hydrodynamics, subject to observed initial conditions. Electronic
computers and sophisticated computational models are required (Geer, 1996).
Oceanography: The science of the ocean, including its composition, circulation and
behaviour, and the observation, description and forecasting of characteristic
ocean phenomena on various time and space scales. It is often subdivided into
physical, chemical and biological oceanography (Holland and Pugh, 2010).
Operational hydrology: (a) Measurements of basic hydrological elements from
networks of meteorological and hydrological stations: collection, transmission
processing, storage, retrieval and publication of basic hydrological data;
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VALUING WEATHER AND CLIMATE:
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(b) hydrological forecasting; (c) development and improvement of relevant
methods, procedures and techniques in those areas of activity (WMO, 1996).
Opportunity cost: The cost of something in terms of an opportunity forgone.
Opportunity cost is given by the benefits that could have been obtained by
choosing the best alternative opportunity. For example, for a farmer the
opportunity cost of growing wheat is given by what they would have earned if
they had grown barley, assuming barley is the best alternative (Black et al., 2012).
Pareto efficiency: A form of efficiency for an economic allocation. An allocation is
Pareto efficient if there is no feasible reallocation that can raise the welfare of
one economic agent without lowering the welfare of any other economic
agent. The concept of Pareto efficiency can be applied to any economic
allocation whether it emerges from trade, bargaining, strategic interaction, or
government imposition (Black et al., 2012).
Prediction: The act of making a forecast of a future occurrence, such as a weather
event, or the forecast itself (Geer, 1996). In established meteorological usage,
“prediction” is essentially interchangeable with “forecast”, although some
preferred usages exist for some timescales.
Present value: The value today of a future payment, or stream of payments, discounted
at some appropriate compound interest – or discount – rate (Downes and
Goodman, 2010). See also discount rate.
Price elasticity: The ratio of a proportional change in quantity supplied or demanded
to a proportional change in price. The price elasticity of supply is
E­s = (p/q)(dq/dp), where p is price and q is quantity. The price elasticity of
demand is often defined as Ed = – (p/q)(dq/dp) so that it is positive, but the
minus sign is not universally used (Black et al., 2012).
Producer surplus: The excess of total sales revenue going to producers over the area
under the supply curve for a good. If the supply curve is perfectly elastic there
is no producer surplus, but if the supply curve is upward-sloping, those
productive resources which would have stayed in the industry at a lower price
earn quasi-rents (Black et al., 2012).
Public good: A good that no consumer can be excluded from using if it is supplied and
for which consumption by one consumer does not reduce the quantity
available for consumption by any other. The first property is referred to as
non-excludability, whereas the latter is termed non-rivalry. As a consequence
of these properties, public goods cause market failure (Black et al., 2012).
Public weather services: Those basic weather and related services provided, usually by
the NMS, for the benefit of the public (WMO, 1999).
Ramsey pricing: A pricing policy that maximizes economic welfare subject to firms
achieving given profit targets. If all firms produce with constant returns to
Appendix A. Glossary of technical terms
143
scale and must break even, then Ramsey pricing reduces to marginal cost
pricing. If firms have increasing returns to scale and must break even then the
markups of the Ramsey prices over marginal cost are inversely related to the
elasticity of demand. Ramsey pricing has been investigated in the context of
public sector monopoly and regulated private sector natural monopoly (Black
et al. 2012).
Resilience: The capacity of a social-ecological system to cope with a hazardous event
or disturbance, responding or reorganizing in ways that maintain its essential
function, identity, and structure, while also maintaining the capacity for
adaptation, learning, and transformation (IPCC, 2014).
Revealed-preference methods: Methods for valuating non-market goods and services
based on actual observable choices and from which actual resource values can
be directly inferred. These methods can be direct (such as market prices or
simulated markets) or indirect (such as travel costs and hedonic pricing)
(Tietenberg and Lewis, 2009, p. 39).
Risk: The potential for consequences where something of value is at stake and where
the outcome is uncertain, recognizing the diversity of values. Risk is often
represented as probability of occurrence of hazardous events or trends
multiplied by the consequences if the events occur. Risk results from the
interaction of vulnerability, exposure, and hazard (IPCC, 2014).
Scarcity: The property of being in excess demand at a zero price. This means that in
equilibrium the price of a scarce good or factor must be positive (Black et al.,
2012). Scarce goods or services are limited in availability.
Sensitivity analysis: The study of how the uncertainty in the output of a model (such
as a BCA) can be apportioned to different sources of uncertainty in the model
input (Saltelli, 2002).
Social benefit: The total benefit from any activity. This includes benefits accruing
directly to the person or firm conducting the activity, as well as external benefits
outside the price system accruing to other people or firms (Black et al., 2012).
Social cost: The total cost of any activity. This includes private costs which fall directly
on the person or firm conducting the activity, as well as external costs outside
the price system which fall on other people or firms (Black et al., 2012).
Social welfare: The well-being of society. This can be measured by a social welfare
function (Black et al., 2012).
Social welfare function: (a) The level of welfare in an economy or society expressed as
a function of economic variables. Social welfare is expressed as a function of
the aggregate consumption levels of goods. Alternatively, an individualistic
social welfare function is a function of individual utility levels. (b) A process for
aggregating individual preferences into social preferences (Black et al., 2012).
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Special weather services: Those services beyond the basic service aimed at meeting
the needs of specific users and user groups, and which may include provision
of specialized data and publications, their interpretation, distribution and
dissemination (WMO, 1990).
Stated-preference methods: Methods for valuating non-market goods and services in
which respondents are directly asked about their WTP for a good or service,
such as the preservation of a species. These methods can be direct (such as
contingent valuation surveys) or indirect (such as contingent ranking or
conjoint analysis) (Tietenberg and Lewis, 2009, p. 39).
Supply: The amount of a good or service offered for sale. The supply function relates
supply to the factors which determine its level. These include the price of the
good, the prices of factor services and intermediate products employed in
producing it, the number of firms engaged in producing it, and their levels of
capital equipment (Black et al., 2012).
Trade-off: The requirement that some of one good or one objective has to be given up
to obtain more of another. The need to trade off goods or objectives against
one another is a sign of economic efficiency; if it is possible to get more of one
good without accepting less of another, or to achieve one objective without
sacrificing another, the economy is not Pareto efficient (Black et al., 2012).
Transaction costs: The costs incurred in undertaking an economic exchange. Practical
examples of transaction costs include the commission paid to a stockbroker for
completing a share deal, and the booking fee charged when purchasing
concert tickets. The costs of travel and time to complete an exchange are also
examples of transaction costs. The existence of transaction costs has been
proposed as the explanation for many of the economic institutions that are
observed. For example, it has been argued that production occurs in firms
rather than through contracting via the market because this minimizes
transaction costs. Transactions costs have also been used to explain why the
market does not solve externality problems (Black et al., 2012).
Travel cost method: A pricing method that seeks to estimate a money value on the
basis of the amount that people actually pay (in money and time) to gain
access to beautiful sites, wilderness and so on, or to avoid various forms of
damage and degradation. The costs incurred by visitors to a site are used to
determine a demand curve for the recreational value they place upon that site.
This can be the basis for estimates of the value of the site, and hence of the
significance in monetary terms of benefit or damage to or loss of availability of
the site (OECD, 2008).
Triple bottom line: Using ecological and social criteria for measuring organizational
success, in addition to financial performance (Allen and Lieberman, 2010, p. 82).
Uncertainty: A consciousness of limited knowledge about present facts or future
events. There is a formal distinction between risk and uncertainty: risk applies
Appendix A. Glossary of technical terms
145
when probabilities can be assigned to the likely occurrence of future
outcomes; uncertainty applies when probabilities cannot be assigned
(Black et al., 2012).
User (of meteorological or hydrological services): The individual, organization
or intermediary who receives the product and services and bases his or her
decisions on them. For the delivery of public weather services, members of the
public will ideally have their needs considered by an organization or
representative body, although in reality this is often done in an ad-hoc manner
based on different information-gathering methods such as surveys or focus
groups, involving little direct contact with individual members of the public
(WMO, 2014b).
Value added: The amount by which the value of information, services or goods is
increased at each stage of its production (Oxford English Dictionary).
Value chain: The process or activities by which value is added to information, services
or goods, from production to final use or consumption (Stevenson and
Waite, 2011).
Value of information: The value of the outcome of action taken with the information
less its value without the information (West and Courtney, 1993, p. 230).
Verification: A process for determining the accuracy of a weather or climate forecast
(or prediction) by comparing the predicted weather with the actual observed
weather or climate for the forecast period (Glickman, 2000).
Vulnerability: The propensity or predisposition to be adversely affected. Vulnerability
encompasses a variety of concepts including sensitivity or susceptibility to
harm and lack of capacity to cope and adapt (IPCC, 2014).
Weather: State of the atmosphere at a particular time, as defined by the various
meteorological elements (WMO, 1992).
Weather forecast: A statement of expected meteorological conditions for a specific
time period and for a specific area (Geer, 1996). A weather forecast usually
specifies the various meteorological elements and phenomenon on a day-byday basis out to the predictability limit of a few weeks.
Weather service: The provision of weather forecasts and warnings about hazardous
conditions, and the collection, quality control, verification, archiving and
dissemination of meteorological data and products (WMO, 1992).
Whole-of-service assessment: A comprehensive assessment of all of the services
provided by a given entity, as opposed to an assessment of one or more
specific services (this publication).
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Willingness to pay: The maximum amount that an economic agent is willing to pay to
acquire a specific good or service. The WTP is private information but may be
obtained using revealed-preference methods or stated-preference methods
(Black et al., 2012).
World Weather Watch: The coordinated international system for the collection,
analysis and distribution of weather information under the auspices of WMO
(Geer, 1996).
World Meteorological Organization: A specialized agency of the United Nations
established for the meteorological and related purposes set down in Article 2
of the 1950 Convention of the World Meteorological Organization as
subsequently amended (WMO, 2012b; Geer, 1996). Through a 1975
amendment, it was given United Nations system responsibility for operational
hydrology. Its membership consists of national governments who carry out its
responsibilities through a World Meteorological Congress and a number of
other subsidiary constituent bodies, including an elected Executive Council.
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Black, J., N. Hashimzade and G.D. Myles, 2012: A Dictionary of Economics. Third edition. Oxford,
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Downes, J. and J.E. Goodman, 2010: Dictionary of Finance and Investment Terms. Hauppauge, New
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Holland, G. and D. Pugh, 2010: Troubled Waters: Ocean Science and Governance. New York,
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APPENDIX B. METEOROLOGICAL, HYDROLOGICAL AND
RELATED SERVICES
INTRODUCTION
B.1
Meteorological, hydrological and related services involve the provision of information
and advice on weather, climate, river, lake, ocean and other environmental conditions
as a basis for decisionmaking to increase the benefits and reduce the costs of
environmental impacts on human activities and of human impacts on the
environment.
The basic concept of met/hydro service provision and application for societal benefit is
shown schematically in Figure B.1 (and explained in more detail in Chapter 2).
In the absence of the services, the various meteorological and related influences and
phenomena (left-hand box of Figure B.1) impact on the weather-, climate- and
water-sensitive socioeconomic sectors and activities (top horizontal arrow) to
produce a range of favourable and adverse outcomes. With a service provision
system in place (lower part of Figure B.1), the information provided on past, present
and expected future meteorological, hydrological and related conditions enables
better-informed decisions and resulting actions (for example, disaster preparedness
VALUE
Weather
Basic
and
special
services
User
decisions
and
action
Outcomes
Benefits
and
costs
Climate
Water
Processing and data management
Service
delivery
Observations
Modelling
Forecasting
Research and development
Figure B.1. The production and delivery of met/hydro and related services
(lower part of diagram) and the value chain (upper part of diagram)
through which these services deliver economic value (benefits minus costs)
to user communities (see Chapter 2)
149
TS
TO
TA
LB
EN
EF
I
ST
O
LC
TA
O
T
S
TOTAL ECONOMIC VALUE OF BENEFITS AND COSTS
Appendix B. Meteorological, hydrological and related services
C
B
Q*
INCREASING VOLUME / LEVEL OF METEOROLOGICAL SERVICES
Figure B.2. Total value of the costs and benefits of meteorological and related
service provision as a function of the volume and level (including quality)
of service provided (WMO, 2009a). The greatest excess of benefits over costs is
achieved for the level of service (Q*) for which the slopes of the total cost and
benefit curves are the same, that is, at the point of intersection
of the marginal cost and benefit curves (see Chapter 5)
and well-timed crop fertilizer distribution and planting), which lead to reduced costs
and greater rewards and hence net individual (private) and societal (public) benefits
from the use of the services. When the additional benefits achieved from the use of
the services exceed the costs of their provision, net value is added and society is
better off.
One of the characteristic features of meteorological (and to a more limited extent,
hydrological) service provision is the need for a substantial underpinning
observational and data-processing infrastructure (the “Observations”, “Modelling”
and “Processing and data management” boxes in Figure B.1) as a prerequisite for the
production of scientifically sound information, forecast and advisory services. Thus,
substantial funds (C in Figure B.2) must be invested in infrastructure to achieve even a
minimal level of service, with additional funding enabling a higher level of service up
to some limit where essentially no further improvement is achievable, making the cost
curve for service production concave upwards as shown schematically by the “Total
costs” line in Figure B.2. On the other hand, the quality of the service has to reach
some threshold level (B) which will win the confidence of potential users before it
begins to deliver benefits – with the benefits then increasing as the level of service is
enhanced until no further value can be added by the service and the benefits curve
plateaus as shown by the “Total benefits” line in Figure B.2.
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Historically, the perceived importance of weather information, especially warnings of
imminent dangerous weather, to safety of life and property was so great that it was
seen as self-evident that all citizens should be provided with a basic level of
meteorological services. And, because essentially the same observational, data
management and modelling infrastructure and service provision arrangements
needed for warning purposes could also meet the needs of most other potential users,
the responsibility for service provision to all sectors of the community was historically
accepted by governments through establishment and operation of NMSs. In recent
times, as emphasis has increased on achieving the most economically efficient
provision of all categories of public services, governments and service-providing
organizations have focused on optimizing national arrangements for the provision of
essential public services and on minimizing and most appropriately allocating, their
costs (Alford and O’Flynn, 2012). This has raised challenging issues of funding and
charging, especially for services that go beyond governments’ basic public interest
responsibilities to their national communities.
B.2
METEOROLOGY, HYDROLOGY AND OCEANOGRAPHY
Meteorology is the science of the atmosphere, dealing in particular with its structure
and composition, interactions with the oceans and land, movements (including
weather-forming processes), weather forecasting, climate variability and climate
change (WMO, 1996). Meteorology includes, by definition, both weather and climate
(Met Office, 1972).
Hydrology is the science that deals with the waters above and below the land surfaces
of the Earth, their occurrence, circulation and distribution, both in time and in space,
their biological, chemical and physical properties, their reaction with their
environment, including the relation to living beings (WMO, 1992). Hydrology is often
subdivided into scientific and operational hydrology. Scientific hydrology is concerned
with understanding all stages of the hydrological cycle. Operational hydrology (WMO,
1996) comprises:
–Measurements of basic hydrological elements from networks of meteorological
and hydrological stations;
–Hydrological forecasting;
–Development and implementation of related methods, approaches and
techniques in those areas of activity.
Oceanography is the science of the ocean, including its composition, circulation and
behaviour and the observation, description and forecasting of characteristic ocean
phenomena on various time- and space scales. It is often subdivided into physical,
chemical and biological oceanography (Holland and Pugh, 2010).
Appendix B. Meteorological, hydrological and related services
151
In identifying an appropriate framework for maximizing the benefits of
meteorological, hydrological and oceanographic services, it is important to
understand the nature and impact of weather, climate, river, lake, ocean and related
environmental conditions on society, and the significance of the various links in the
end-to-end service production, delivery and application chain shown schematically in
the lower part of Figure B.1.
B.3
WEATHER, CLIMATE AND WATER
Weather is the state of the atmosphere at a particular time as defined by the various
meteorological elements (WMO, 1992). It is described in terms of the temperature
and other meteorological variables on timescales of minutes, hours, days and weeks
and the location and movement of weather-producing synoptic systems such as the
highs, lows, troughs and fronts that appear on the familiar television and newspaper
weather maps.
Climate is a synthesis of weather conditions in a given area, characterized by long-term
statistics (mean values, variances, probabilities of extreme values, and the like) of the
meteorological elements in that area (WMO, 1992). It is essentially a statistical
description of weather and its variability over longer time periods, usually months,
seasons, years, decades and centuries. It is described in terms of local values and
spatial patterns of the averages and extremes of the weather.
Water appears in various forms (liquid, solid, vapour). Atmospheric water is an
integral part of most weather and climate phenomena, while surface water interacts
with land surfaces and biospheres. The succession of stages through which water
passes from the atmosphere to the Earth and returns to the atmosphere –
evaporation from the land or sea or inland water, condensation to form clouds,
precipitation, interception, infiltration, percolation, runoff, accumulation in the soil or
in bodies of water, and re-evaporation – is known as the hydrological cycle (WMO
and UNESCO, 2012).
The weather- and climate-forming processes of the atmosphere and the ocean are
globally interconnected and closely coupled. Because of its greater density and heat
content, the ocean is characterized by phenomena on generally longer timescales
than those of the atmosphere. However, because they are both governed by the
same physical laws that enable certain aspects of their future state and behaviour to
be determined from their past and present states, their evolution over time can be
simulated numerically with powerful computers to produce forecasts or predictions
of future weather and climate. It is useful, in describing meteorological and related
services, including forecast services, to categorize the phenomena of weather and
climate according to their characteristic space and timescales, as shown
schematically in Figure B.3.
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Local scale
Climate change crojection
Decadal climate prediction
10 km
Seasonal to interannual
climate prediction
Nowcasting
Current weather
Mesoscale
Recent weather
100 km
Synoptic
scale
Recent climate
1 000 km
Continental/
regional
scale
“Normal” climate
10 000 km
Long-range weather forecasting
Global Scale
FUTURE CLIMATE
Medium-range weather forecasting
WEATHER
Short-range weather forecasting
PAST CLIMATE
1 km
Last Last
decade year
Last Last
month week Yesterday
Now
Tomorrow
Next
week
Next
month
Next
year
Next
Next
Next
decade century millennium
Figure B.3. Characteristic space scales of weather phenomena (left-hand scale)
and the approximate timescale terminology for weather
and climate description and prediction (lower scale)
B.4
WEATHER-, CLIMATE- AND WATER-SENSITIVE ACTIVITIES,
SECTORS AND COUNTRIES
Virtually every person and every country and almost all human activities are directly or
indirectly influenced by weather and climate. Also, many people are – from time to
time – seriously impacted by floods, ocean waves, storm surges and other hydrological
and oceanographic phenomena. The impacts extend over countries, regions,
economic sectors, social classes and age groups.
The sectors of society that are most sensitive to weather and climate include
agriculture, aviation, construction, emergency management, energy, health, natural
resource management, shipping and tourism (WMO, 1996).
Different types of weather and climate phenomena have varying impacts in different
parts of the world. Developing countries, in general, are more sensitive to weather and
climate than the economically stronger developed countries where infrastructure
planning and engineering have done much to reduce vulnerability albeit, often, with
more and far more costly assets at stake. Thus, developing countries reliant on rain-fed
agriculture are especially vulnerable to drought, while hurricanes remain an everpresent threat to safety of life and property in many tropical countries, especially those
with extensive coastal tourism infrastructure (WMO, 2007a).
Appendix B. Meteorological, hydrological and related services
B.5
153
IMPACTS OF WEATHER, CLIMATE AND WATER
Weather and climate have shaped the history of civilizations and nations through the
ages (Durschmied, 2000). Their extremes impact widely across society (Burroughs,
1997). There are many different metrics used for quantifying the impacts of weather,
climate and related environmental conditions and phenomena on the different sectors
of society and on national communities and economies as a whole. Two of the most
important are:
–
Numbers of people adversely affected and lives lost as a result of dangerous
meteorological and hydrological phenomena;
–
Economic costs of the damage from extreme weather, climate and hydrological
events and the economic benefits (for example, to farming or the tourism
industry) from spells of “good” weather.
There are also many different approaches to categorizing and aggregating these
impacts, both positive and negative, by phenomenon, impact sector, country and so
on. Even without specific factoring in of natural disasters, United States economic
activity (as GDP) varies by up to plus or minus 1.7% due to weather variability,
resulting in impacts as large as US$ 485 billion of the US$ 14.4 trillion 2008 GDP (Lazo,
2011). A 1990s study suggested that the strongest single indicator of the state of the
Australian economy, apart from the global economy, was the meteorological Southern
Oscillation Index (McTaggart and Hall, 1993).
Worldwide, it is estimated that, in 2011, about 206 million people were victims of
natural disasters with an economic cost of US$ 366 billion (Rogers and Tsirkonov, 2013)
with the largest part of this due to disasters of meteorological and hydrological origin.
B.6
ORIGIN OF MET/HYDRO SERVICES
Meteorological service provision (see also section C.2) has a very long history
stretching back, in one sense, for thousands of years (WMO, 1990; Halford, 2004). The
origin of scientifically based services dates from the second half of the nineteenth
century when, for example:
–
Maury (1855) provided climatological wind and current maps for the oceans from
ships’ logs as a service to marine navigation;
–
Fitzroy (see Gribbin and Gribbin, 2003) initiated storm warnings for ships at sea
and began issuing public weather forecasts for parts of England;
–
Abbe (see Cox, 2002) used the new real-time data collection powers of the
electric telegraph to prepare and distribute daily weather forecasts for several
cities across the United States.
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Soon, many countries began establishing NMSs to prepare weather bulletins and maps
for public information, with their data collection and exchange arrangements
coordinated internationally through the International Meteorological Organization
(IMO), established in 1873, via its regular “Conferences of Directors of Meteorological
Services” (Daniel, 1973).
Meteorological service provision expanded rapidly to almost every country during the
first half of the twentieth century, especially in support of agriculture and shipping and
to meet the burgeoning needs for both current and forecast information for the safety
and economy of civil aviation. Under the broad guidance of IMO, all major nations and
their colonies established observation networks, data collection arrangements (initially
by both telegraph and mail) and climatological and forecasting offices serving
shipping and aviation. In most countries, they also issued public weather forecasts
through newspapers and radio. The community demand for both current weather
information and forecasts became insatiable (see for example, Fleming, 1996;
Cox, 2002).
The concept of hydrological services has a shorter history than that of meteorological
services in most parts of the world, albeit that measurements and records of lake and
river levels also go back thousands of years, and streamflow and other hydrological
monitoring became an integral part of river management with the establishment of
the major river commissions in Europe in the nineteenth century. It was only following
the International Hydrological Decade of 1964–1974 and decision by governments to
vest international responsibility for operational hydrology in WMO in 1975 that the
concept of hydrological information as a service, analogous to a meteorological
service, became widely adopted in most of the rest of the world.
B.7
NATURE AND SCOPE OF MET/HYDRO SERVICES
Meteorological services range widely in nature and include almost every type of
information, advice or investigation on past, present and future weather and climate
and their impacts on society (Zillman, 1999). They often also include provision of
information on river, lake and ocean conditions and thus are sometimes regarded as
including both hydrological and oceanographic services. They are usually, though
somewhat artificially, subdivided into weather services and climate services (or met/
hydro services).
Weather services involve the provision of information and advice on recent, present
and expected weather conditions on timescales from a few hours (nowcasting) out to
a few weeks (medium-range weather forecasting). Weather forecasts or predictions
aim to describe the meteorological conditions at an individual location or over an area
or region at any point in time out to the limits of predictability of individual synoptic
weather systems. Weather warnings are aimed at alerting potentially affected
communities to severe or dangerous conditions and of the actions needed to reduce
their adverse impact.
Appendix B. Meteorological, hydrological and related services
155
Met/hydro services involve the provision of climate information in a way that assists
decisionmaking by individuals or organizations. A climate service requires
appropriate engagement along with an effective access mechanism, and must
respond to user needs. Met/hydro services include the provision of historical climate
data and information, analysis of current climate conditions and outlooks,
predictions, projections and scenarios of future climate on timescales from months to
millennia.
With the establishment of WMO in 1950 (Daniel, 1973), the initiation of WMO
WWW in 1963 (Rasmussen, 2003) and the major advances in atmospheric
predictability through the GARP in the 1970s and 1980s (WMO, 1990), the useful
application of weather and met/hydro services became widespread across the
community. In 1991, WMO initiated its Public Weather Services Programme (WMO,
2007b) to assist all countries to enhance the public availability and usefulness of daily
weather information, whether provided by NMSs or through private sector,
academic or media service providers. The establishment of the World Climate
Applications (and Services) Programme as part of the World Climate Programme
initiated in 1979 (Boldirev, 1991) greatly expanded the nature and scope of met/
hydro services in many countries. The concept of met/hydro services was greatly
broadened through the work of IPCC, established in 1988 (Bolin, 2007). The focus
on met/hydro services was further enhanced through the Climate Agenda (WMO,
1993), the World Climate Conference-3 in 2009 (WMO, 2009b) and establishment of
the GFCS (WMO, 2014a).
Hydrological services overlap significantly with meteorological services and cover
similar timescales but focus primarily on the surface component of the hydrological
cycle, especially streamflow and river height prediction. They include water resource
monitoring and assessment, and the important category of flash (short-term) and
riverine (long-term) flood warning. Warnings for flooding, especially flash-flood
warnings, are usually regarded as both meteorological and hydrological services.
B.8
ECONOMIC CHARACTERISTICS OF MET/HYDRO SERVICES
The policy, funding and charging arrangements for provision of met/hydro services
and the mechanisms through which they deliver benefits to society are significantly
influenced by the overall economic and policy framework within which they are
provided (WMO, 2002). This is especially so according to the extent of their economic
properties of rivalry and excludability (Freebairn and Zillman, 2002a).
Most meteorological services have historically been regarded as public goods
(Samuelson, 1954; Harris, 1995; Stiglitz, 2000; Gunasekera, 2004) characterized by the
twin properties of:
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–
Non-rivalry: One person’s consumption of the service does not reduce the
amount or value available to others;
–
Non-excludability: The service having been made available to one user, it is
impossible or very costly to exclude others from its use.
However, some economists regard the non-rivalrous criterion as the most important in
the characterization of public goods such as meteorological services.
Public goods have a number of other economic characteristics (Bailey, 1995) that
influence the way they are provided and consumed by society:
–
Because they are collectively owned and no property rights can be invested in
them, markets fail to exist for their provision;
–
The decision on whether they should be provided, and at what level, must be
taken by government;
–
The cost of their provision must be (primarily) met by taxation;
–
The beneficiaries are the whole of society and the total benefit to society is the
larger the more widely they are consumed.
Some public meteorological services, especially warning services, have the additional
characteristic of “merit goods” (Bailey, 1995), that is, goods with consumption that is
proactively fostered by governments in the public interest.
It should be noted, however, that there is also a substantial range of meteorological
and related services that are by nature of private (that is, rival, excludable) or mixed
goods (Gunasekera, 2004). Most user-specific special services are, at least to some
degree, rival and excludable and are most efficiently provided through market
processes. This can be achieved either through private sector service providers or
through commercial arms of NMSs. And, in some circumstances in some countries,
some of the revenue from commercial services may be used to offset the cost of
provision of the public service.
At the international level, many meteorological services may be further categorized as
“global public goods” (Kaul et al., 1999), that is, goods with consumption that benefits
many countries, a broad spectrum of the global population and future as well as
present generations. To some extent, the WMO system of international cooperation in
meteorology is itself a global public good (Gunasekera and Zillman, 2004).
While some hydrological services such as flood warnings and river and lake level regimes
possess essentially the same public-good character as public meteorological services,
others, such as real-time information on streamflow, dam level, soil moisture and water
quality have historically been more linked with water resource management and
commercial water supply, and have been regarded as more of the nature of private or
mixed goods. In some parts of Europe, river-flow data have been exchanged for a long
Appendix B. Meteorological, hydrological and related services
157
time but, at the global level, hydrology lacks the strong tradition of free and unrestricted
data exchange that underpins global meteorology, with many countries reluctant to
release river flow information beyond national borders. In this sense, hydrological
information has more of the rival and excludable properties of private goods.
B.9
PROVIDERS OF METEOROLOGICAL AND RELATED SERVICES
The provision of meteorological services in every country relies on the existence of
some form of end-to-end NMS system (lower part of Figure B.1) consisting of four
basic components:
–
A national observation network;
–
A research and development effort (although this may be very small or
non-existent in some developing countries);
–
Data management and modelling/forecasting/archival capabilities;
–
A service delivery system.
These components are supported by arrangements for international cooperation in
data collection and service provision (WMO, 2009a).
In the broadest sense, each of these must be regarded as essential links in an
integrated national service provision chain (for example, the observation network
provides an essential service to both research and modelling), but the main focus is
usually on the final step in the process through which historical and current data and
model outputs are transformed into information products suited to user needs,
including both the general public and the many specialized user communities.
The major participants in the NMS system (in recent United States terminology (National
Research Council, 2003) the “weather, water and climate enterprise”) are (Zillman, 2014):
–
The government agency, the NMS, usually publicly funded, responsible for the
operation of the national meteorological infrastructure and for provision of (at
least) the basic service to the community;
–
The academic (university) research community which usually plays a key role in
advancing the scientific basis for service provision and trains many of the
professional staff who move into service provision;
–
The mass media that, in most countries, work in close partnership with the NMS
in delivering essential services to the public;
–
Private sector and other providers, including commercial providers of value-adding
tailored services and special in-house service providers in many of the major user
sectors and organizations (for example, energy companies and airlines).
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Many NMSs also carry national responsibility for a range of hydrological,
oceanographic and other environmental services. Those that have formal national
responsibility for provision of hydrological as well as meteorological services are often
referred to as National Hydrometeorological Services, albeit with the same WMO
acronym (NMS) as those with responsibility only for meteorology. In other countries,
the major responsibility for hydrological service provision resides with separate NHSs,
often located in water supply ministries. Some countries also operate separate National
Oceanographic Services. Both NHSs and National Oceanographic Services operate on
a broadly similar end-to-end basis as NMSs, albeit without the strong public service
delivery mechanisms that characterize well-established NMSs.
B.10
USERS OF MET/HYDRO SERVICES
The users of met/hydro services embrace virtually every individual, organization and
community sector whose activities are sensitive to the impacts of weather, climate and
water. The user community is normally regarded as consisting of the general public, as
the users of basic services, and all the various economic and social sectors and
organizations as the users of what are often referred to as special services. In the case
of tailored (special) services provided on a commercial basis, it is now usual, in many
countries, to refer to the users of the services as clients or customers.
B.11
NATIONAL METEOROLOGICAL SERVICES
A country’s NMS is an essential component of its basic infrastructure (WMO, 1999a;
Zillman, 1999). Although their detailed responsibilities vary from country to country,
most NMSs are responsible for:
–
Operation of the national meteorological (and in some cases, also hydrological
and oceanographic) observation network, including both surface and upper air
observations needed for weather forecasting and for the climatological record;
–
Assembling and maintaining the national climate data archive, including
processing and quality control of all available observations, and their storage and
safeguarding in standard and appropriately accessible formats;
–
Advancing knowledge of their countries’ weather and climate through research
and investigation, in the overall national interest, as well as to improve their
weather and met/hydro services;
–
Providing a wide range of weather, climate and related (often including
hydrological, oceanographic, ionospheric and other environmental) services to
their national communities, both widely through the mass media and through
specialized delivery arrangements tailored for major user sectors or organizations;
Appendix B. Meteorological, hydrological and related services
–
159
Meeting their countries’ obligations for international data collection and
exchange under the Convention of the World Meteorological Organization,
including, usually, leadership of national involvement in the various constituent
bodies and programmes of WMO (and, in the case of those with oceanographic
service responsibilities, in the Intergovernmental Oceanographic Commission of
UNESCO).
The ultimate goals of NMSs also vary between countries, but in most they focus
particularly on (WMO, 2007a):
–
Protection of life and property;
–
Safeguarding the environment;
–
Contributing to sustainable development;
–
Promoting long-term observation and collection of meteorological, hydrological
and related environmental data;
–
Promotion of endogenous capacity-building;
–
Meeting international commitments;
–
Contributing to international cooperation.
Historically, most NMSs, whether in advanced or developing countries, were organized
fairly simply into observation, telecommunications, research, climate and forecasting
branches or departments. In recent decades, however, particularly since many NMSs
have adopted more business-oriented approaches to their missions, a wide range of
operating models has come into use (Rogers and Tsirkunov, 2013).
Zillman (1999) provides a general overview of the role and operation of NMSs and
Zillman (2003) summarizes the state of NMSs around the world in the early twenty-first
century. WMO (2013) provides a detailed listing of contemporary NMS functions and
services.
B.12
NATIONAL HYDROLOGICAL SERVICES
In many countries, the primary responsibility for river, lake and other hydrological
observation, data management, research, modelling and streamflow forecasting and
warning resides with organizationally separate NHSs, which are often located with
environmental, natural resource management, water supply or emergency services
ministries.
The basic functions of NHSs are essentially similar to those of NMSs but focused on the
surface phase of the hydrological cycle, including precipitation, runoff, river flow,
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storage (in soil and lakes) and loss to the atmosphere through evaporation and
evapotranspiration. The main NHS products and services include information on
historical and current rainfall and evaporation, river height and discharge and lake and
dam levels, as well as forecasts of river flow (including low flows) and warnings of flash
and riverine flooding. Many NHSs also have responsibility for monitoring of
underground water resources.
The role and operation of NHSs are discussed in a range of WMO and other publications
over recent decades with an excellent overview available (see WMO, 2001).
B.13
INTERNATIONAL COORDINATION OF MET/HYDRO SERVICES
The essential standardization and coordination of meteorological observation, data
collection and service provision were carried out from 1873 to 1950 by the
non-governmental IMO, especially through its regular international “Conferences of
Directors of Meteorological Services” and its subsidiary system of expert technical
commissions. Since 1950, the primary mechanism for international cooperation and
coordination in meteorology has been provided by the intergovernmental WMO. The
responsibility for international cooperation in hydrological data collection and
exchange, which had resided historically with the river basin commissions, was added
to the WMO Convention in 1975, with UNESCO assuming responsibility for
international cooperation in scientific hydrology.
The purposes of WMO under its convention now include (WMO, 2012):
–
To facilitate worldwide cooperation in the establishment of networks of stations
and to promote the establishment and maintenance of centres charged with the
provision of meteorological and related services;
–
To promote the establishment and maintenance of systems for the rapid
exchange of meteorological and related information;
–
To promote standardization of meteorological and related observations and to
ensure the uniform publication of observations and statistics;
–
To further the application of meteorology to aviation, shipping, water problems,
agriculture and other human activities;
–
To promote activities in operational hydrology and to further close cooperation
between meteorological and hydrological services.
Most of the international technical coordination of meteorological and hydrological
services is carried out through the specialized intergovernmental technical
commissions of WMO, in particular:
Appendix B. Meteorological, hydrological and related services
161
–
The Commission for Basic Systems that, in addition to its role in guiding the
operation of the common underpinning infrastructure, carries primary
international responsibility for the WMO Public Weather Services Programme;
–
The Commission for Agricultural Meteorology, which coordinates weather and
met/hydro services for agriculture;
–
The Commission for Aeronautical Meteorology, which works in conjunction with
ICAO to coordinate the provision of meteorological services for civil aviation;
–
The WMO–Intergovernmental Oceanographic Commission Joint Technical
Commission on Oceanography and Marine Meteorology, which provides
essential international coordination of meteorological and oceanographic
services for shipping and other offshore activities;
–
The Commission for Climatology, which coordinates the provision of met/hydro
services;
–
The Commission for Hydrology, which provides essential international
coordination of all aspects of operational hydrology including the provision of
hydrological services.
Within the WMO Secretariat, essential international coordination activities are
organized through a series of application and service programmes such as the Public
Weather Services Programme, the Agricultural Meteorology Programme and the
Aviation Meteorology Programme. Following World Climate Conference-3 in 2009,
WMO and its partner international organizations agreed to enhance the provision of
met/hydro services through the GFCS (WMO, 2009b; 2014a).
The viability of service provision within every country is heavily dependent on national
access to essential meteorological and related data and products from neighbouring
countries and from around the world. Following resolution of the major data exchange
controversies of the 1990s (Bautista Perez, 1996), the basic policy and practice
regarding international data exchange in support of various categories of service is set
down in Resolution 40 of the 1995 WMO Congress (for meteorology) and
Resolution 25 of the 1999 Congress (for hydrology).
B.14
LEVEL AND QUALITY OF SERVICE
Inevitably, the level and quality of meteorological and hydrological services vary
considerably from country to country depending, among other things, on:
–
Coverage and performance of the national observing networks and data
management systems;
–
Access to data (especially satellite data) and products from other countries;
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–
Sophistication and skill of prediction models and the effectiveness of the
cascading forecasting process through which the products of global and regional
centres are employed by NMSs in local forecasting operations;
–
Training and expertise of forecasting and other service staff;
–
Effectiveness of provider–user interaction and service delivery arrangements.
Most countries’ NMSs maintain extensive performance monitoring of the various links
in the service provision chain, including especially the accuracy and skill of their various
forecast products (Murphy, 1993, 1997). In its Guidelines on Performance Assessment of
Public Weather Services (WMO, 2000), WMO elaborates the important distinction
between forecast accuracy, precision, skill and reliability, and outlines an overall
framework for forecast verification and performance assessment from both provider
and user perspectives.
There is now an active research community and an extensive literature on forecast
verification (see, for example, Ebert et al., 2013) aimed at better quantifying various
key aspects of NMS performance and, in particular, at providing objective assessment
of the contribution of various stages of the service provision chain and various new
approaches and technologies, to forecast improvement. It has been shown, for
example, that, in the southern hemisphere, satellite data extend the time range of
skilful numerical weather prediction by a factor of four (Le Marshall et al., 2013).
Such performance measures, coupled with studies of forecast impact in the various
user communities, represent an essential foundation for national initiatives on
investment in NMS modernization.
B.15
SERVICE DELIVERY
In order to deliver value to their user communities, met/hydro services require efficient
and effective service delivery systems. In recent years, the WMO Public Weather
Services Programme has led the development of a comprehensive service delivery
strategy and implementation plan (WMO, 2014b) which is described in Chapter 2.
B.16
APPLICATION OF MET/HYDRO SERVICES IN DECISIONMAKING
The applications of meteorological services range widely across all weather- and
climate-sensitive sectors of society – from the simple, almost subconscious response of
individuals and households to the daily weather forecast, through the largely invisible
incorporation of detailed terminal and en-route winds and weather conditions in
aviation operations (affecting important safety, economic and regulatory decisions
such as the carriage of “holding” fuel), to sophisticated modelling of meteorological
Appendix B. Meteorological, hydrological and related services
163
influences on such long-term economic decisions as water-supply design or crop-yield
planning and forecasting. Useful summaries of the range of applications of traditional
weather services are included in the various programme documents of WMO,
including the report of the Madrid Conference (WMO, 2009a). The proceedings of the
first, second and third World Climate Conferences (WMO, 1979, 1991 and 2009b)
provide a good overview of the applications of met/hydro services and the GFCS
Implementation Plan (WMO, 2014a) outlines some of the new opportunities emerging
from improvements in climate prediction and IPCC assessments of human-induced
climate change.
The traditional users of hydrological services were located primarily in agricultural,
energy, navigation and water-supply sectors, with a long history of use of precipitation
and streamflow information in dam design, irrigation scheduling, and the like.
Increasingly in recent decades, the broader community applications of hydrological
services, in both qualitative and quantitative decision models, have advanced in line
with the underpinning technologies (especially satellite observation) and the
increasing challenges of reliable water supply for growing populations in both
developing and developed countries.
Many different factors influence the effectiveness of the application of met/hydro
services in decisionmaking and the ultimate benefits that flow to individual users and
society as a whole from their use. In addition to the inherent quality of the services and
effectiveness of their delivery, these include:
–
The strength of the weather/climate/water sensitivity of the socioeconomic
activities or sectors concerned;
–
The confidence of the users in the quality and usefulness of the services;
–
The sophistication of the decision models employed.
The confidence of users and potential users in the skill and reliability of forecast
information is especially important. Experience suggests that forecasts need to reach a
reasonably high threshold of skill and reliability (see Figure B.2) before users will
institutionalize them in economically significant decisionmaking (and be prepared to
forgive occasional forecast errors). Indicators of provider confidence in forecast
reliability in individual circumstances can be useful in building up user trust and
confidence to this end.
B.17
FUNDING, PRICING AND CHARGING FOR SERVICES
Historically, meteorological service provision, including provision of the essential
observational and data-processing infrastructure, was seen as a fundamental
responsibility of governments funded by taxpayers through government
appropriations in the interests of the community at large.
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The established meteorological concept of government-funded NMSs freely
exchanging their data internationally to help each other to deliver maximum benefits
to their national communities was firmly in place half a century before the economic
concept of public goods (Samuelson, 1954) became institutionalized in national
treasuries and budget processes. The IMO/WMO model of voluntary cooperation
emerged especially from the dependence of NMSs on observations from shipping, not
just to provide maritime forecasts and warnings for the safety of life at sea but also to
provide the best possible forecast services for their own national territories.
With the advent and rapid growth of civil aviation, however, the requirements for
meteorological services expanded so rapidly that the concept of funding at least the
aviation-specific services and, in some cases, the observational and forecasting
infrastructure needed to support them, through air navigation charges emerged. In
many former colonies and developing countries where only primitive NMSs had
existed in the pre-aviation era, various aviation industry-based funding arrangements
were put in place, with the capacity of the NMSs to provide public weather services
essentially subsidized from aviation user charges. Over time, a range of incremental
and other user charging models have been put in place through ICAO–WMO
mechanisms (for example, ICAO, 1997; WMO, 1999b).
Two major developments placed the traditional government and/or aviation industry
funding of NMSs under pressure in the 1980s and early 1990s. The first was the
substantially increased costs of the national and international meteorological
infrastructure (especially satellites) that resulted from the WWW and GARP initiatives
(WMO, 1990). The second was the move, in some parts of the world, to commercialize
or privatize many types of “public” services that had traditionally been provided by
government. This precipitated a period of considerable turmoil in WMO, with difficult
negotiations on issues of data exchange, commercialization and alternative service
delivery (Bautista Perez, 1996; WMO, 1999a). The relationship between NMSs and the
national and international private sector also came under stress, with different
approaches and policies adopted in different countries (WMO, 1996). Freebairn and
Zillman (2002b) and Gunasekera (2004) provide an analysis of some of the economic
and policy considerations involved in meteorological service funding, pricing and
charging. Rogers and Tsirkunov (2013) provide a useful survey of the funding and
operating models that have evolved over the past decade, including those where NMS
operations depend on a combination of government funding and user charging.
REFERENCES
Alford, J. and J. O’Flynn, 2012: Rethinking Public Service Delivery. New York, Palgrave Macmillan.
Bailey, S.J., 1995: Public Sector Economics. Houndsmills, MacMillan Press.
Bautista Perez, M., 1996: New WMO regulation on the international exchange of meteorological
data and products: Incorporating Resolution 40 (Cg.XII) – WMO policy and practice for the
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APPENDIX C. A SHORT HISTORY OF STUDIES
OF SOCIOECONOMIC BENEFITS OF METEOROLOGICAL
AND HYDROLOGICAL SERVICES
C.1
INTRODUCTION
There is an extensive literature on the social, economic and environmental benefits
from the application of meteorological services over the past 60 years (for example,
Bijvoet and Bleeker, 1951; Thompson and Brier, 1952; Gibbs, 1964; Maunder, 1970;
Taylor, 1972; Price-Budgen; 1990; Katz and Murphy, 1997; WMO, 2007a). Increasingly
during the past 50 years, the convergence of expertise from the separate, but in some
ways similar, disciplines of economics and meteorology, including through the work of
some who have excelled in both fields (see, for example, Arrow, 2008), has led to a
more quantitative approach to valuation and emergence of a significant field of
meteorological economics (WMO, 2002; Gunasekera, 2004; Katz and Lazo, 2011).
The World Meteorological Organization became substantially involved in studies of
the economic benefits of meteorology in conjunction with the increased financial
investment in observational infrastructure associated with the establishment of WWW
in the 1960s (WMO, 1966). This inspired a range of economic benefit studies at the
national level (WMO, 1968) and triggered academic interest in more refined
methodologies for establishing the economic value of meteorological information
(Freebairn, 1979). The World Meteorological Organization continued to foster
economic studies in conjunction with its work on more effective application of the
expanded range and increased quality of meteorological and hydrological services
through the 1980s and 1990s (WMO, 1990a, 1994) and, in particular, through the
2007 Madrid Conference and Action Plan (WMO, 2009a).
The World Bank has maintained a general interest in the role of met/hydro services in
natural disaster reduction and other development goals over the years, albeit mostly as
a minor component of much larger infrastructure projects in developing countries. It
was only with the initiation of a major World Bank project on modernizing the Russian
Hydrometeorological Service (Roshydromet) in the early 2000s (Tsirkunov et al., 2006)
that the Bank became substantially involved in specific projects focused on
strengthening the role and operation of NMHSs. This led to an extensive series of
projects aimed at demonstrating the benefits from improved met/hydro services in the
former Union of Soviet Socialist Republics (WMO, 2007b), with subsequent extension
to Africa and other developing regions and preparation of a comprehensive World
Bank guidance document (Rogers and Tsirkunov, 2013).
C.2
ORIGINAL MOTIVATION FOR PROVISION OF METEOROLOGICAL
SERVICES
Meteorology has, from the beginning, been an intensely applications-oriented field of
science, with investment in data collection infrastructure and research strongly
influenced by the need to deliver useful information for societal benefit. The origins of
international cooperation in meteorology (see also section B.6) in the mid-nineteenth
century resulted from the perceived benefits from using increased knowledge of
APPENDIX C. A SHORT HISTORY OF STUDIES OF SOCIOECONOMIC BENEFITS
OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
169
climatological wind and current patterns over the oceans to enhance the efficiency and
safety of marine navigation (Maury, 1855). The first systematic attempts at scientifically
based weather prediction were inspired by the need to provide forewarning of
dangerous storms to ships at sea (Cox, 2002). The initial establishment, in the late
1800s and early 1900s, of the predecessors of many of the present-day NMSs was
inspired by widespread belief in the benefits that would flow to society from better
information on the weather (for example, Day, 2007; Walker, 2012). Community faith
in the value of reliable meteorological services was well summarized in the
parliamentary debate on the establishment of the Australian Bureau of Meteorology as
a federal agency in 1906 (McColl, 1906):
In our present complex civilization … the discovery and formulation of laws governing
the weather are of first importance. To obtain an accurate meteorological service
throughout Australia, the government would be justified in incurring almost any
expenditure. To all sections of the community the matter is one of great importance –
to those interested in commerce, transportation, navigation, agriculture and trade of
all descriptions. In short, it concerns everybody whose living and comfort depend
upon the seasons and upon the weather.
With the birth of civil aviation and the extreme weather sensitivity of aircraft in the first
half of the twentieth century, the need for reliable meteorological information
increased rapidly and its benefits, in terms of the safety, efficiency and economy of air
operations, were widely seen as self-evident and very large (Cartwright and Sprinkle,
1996). Few governments or citizens queried the essentiality of expenditure on the
observational networks needed to provide reliable aviation weather services. The
global need for international cooperation in meteorological service provision and the
rationale for conversion of the non-governmental IMO, that had existed since 1873,
into the intergovernmental WMO were taken as given and widely supported by
governments (Daniel, 1973).
From time to time, however, the reliability, usefulness and value of meteorological
service provision was called into question, often from the scientific perspective when it
was argued that the level of scientific understanding was not yet sufficient to support
the level of services provided or demanded. Scientific peer pressure forced the
cessation of Admiral Fitzroy’s highly valued public forecasts and storm warnings in the
1860s (Walker, 2012). Sir Napier Shaw, in 1939 (Shaw, 1939), bemoaned that “The
stress of service has hampered the progress of science”, and Professor Joe Smagorinsky
resisted global climate models being pressed into “premature servitude” (Tucker,
1997). Most NMSs have found themselves severely criticized, from time to time, for
major forecast errors and for unreliable and “useless” services; but, throughout most of
the world over the past century, the importance of having an effectively operating
NMS and the benefits to the community from the services it provides have been widely
accepted by citizens in all walks of life and by national governments of both developed
and developing countries (WMO, 2003).
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C.3
EARLY WORK ON THE ECONOMICS OF METEOROLOGICAL
INFORMATION AND SERVICES
The first significant publications on the economic value of meteorological information
– originating from both the meteorological and economics communities – appeared in
the early 1950s (for example, Bijvoet and Bleeker, 1951; Thompson and Brier, 1952). The
interest in meteorological economics grew rapidly during the 1960s and 1970s on the
basis of both academic/research studies (for example, Thompson, 1962; Glahn, 1964;
McQuigg and Thompson, 1966; Maunder, 1970; Doll, 1971; Anderson, 1973; Murphy,
1977; Freebairn, 1979) and a number of service-, application-, industry- and countryfocused studies (for example, Borgman, 1960; Bollay Associates, 1962; Lave, 1963;
Gibbs, 1964; Mason, 1966).
C.4
ECONOMIC STUDIES IN SUPPORT OF WORLD WEATHER WATCH
In the late 1950s, the international meteorological community began to contemplate
the potential of earth-observing satellites, digital computers and advances in
understanding of atmospheric processes to bring dramatic improvements in the
quality and usefulness of meteorological services throughout the world (WMO,
1990b). In September 1961, United States President John F. Kennedy urged the United
Nations General Assembly to establish a cooperative global system of weather and
climate monitoring and prediction, which was soon to emerge, following the 1963
fourth World Meteorological Congress (WMO, 1963), as WMO WWW. The 1967
Congress approved an ambitious Plan and Implementation Programme for WWW that
over the following decades was to become widely accepted as the core programme of
WMO and the foundation for dramatically improved weather service provision in every
country (Rasmussen, 2003; Zillman, 2013).
Before the WWW era of satellites and powerful computers, the costs of meteorological
service provision were relatively modest and the perceived benefits so great that it was
not seen as especially important to undertake formal economic assessment of the
benefits and costs of the various components of the infrastructure needed for service
provision. However, with international planning proceeding for weather satellites,
large computer-equipped modelling centres and the various other costly observing
and information systems envisaged for WWW, it was judged appropriate, as an
integral part of WWW planning, to build on the limited sectoral and national studies
already undertaken to provide more rigorous economic assessment of the overall
benefits of WWW implementation and the benefits potentially available to individual
countries through participation in WWW. The World Meteorological Organization
issued three significant WWW planning reports on economic issues over the period
1966–1968 as follows:
–
No. 4 – A review of earlier economic studies of weather and climate information
and an overall assessment of the economic and other value of WWW
(WMO, 1966);
APPENDIX C. A SHORT HISTORY OF STUDIES OF SOCIOECONOMIC BENEFITS
OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
171
–
No. 17 – An 11-page set of guidelines produced by an ad-hoc group of economists
and meteorologists on methodologies for assessing the economic value of an
NMS (WMO, 1967);
–
No. 27 – A summary of economic benefit studies of NMSs of Australia, France,
Germany, the Russian Federation, the United Kingdom and the United States,
along with a general assessment of the applicability of BCA in meteorology and a
review of potential economic benefits from improved meteorological services in
developing countries (WMO, 1968).
The national assessments summarized in WWW Planning Report No. 27 were
presented to the 1968 session of the WMO Executive Committee with the European
Commission concluding, inter alia, that “Assessing what additional benefits will result
from improvements associated with the World Weather Watch … is a fascinating field
of study which can best be treated by a team of meteorologists and economists”
(Thompson and Ashford, 1968).
C.5
THE 1970s AND EARLY 1980s
Following the initial economic studies associated with the establishment of WWW, the
major focus of international meteorology through the 1970s and early 1980s turned to
the challenges of WWW implementation and conduct of the 1979 Global Weather
Experiment (Zillman, 1977) as a basis for more accurate and longer-range weather
prediction. While most NMSs and a substantial number of individual experts (for
example, Maunder, 1977) continued to work on economic aspects of service
development and application, the primary emphasis in the 1970s and early 1980s was
on the scientific and technological aspects of service improvement rather than on the
societal benefits of the improved services.
A few NMS staff, however, found themselves under increased pressure from
governments to provide economic justification for the public expenditure needed to
support their expanded services and, in collaboration with the relevant professional
societies and communities, initiated a series of conferences on the economic benefits of
meteorological services (for example, Australian Bureau of Meteorology, 1979;
Hickman, 1979). This entrained a new generation of economists into the issues of
meteorological service provision and fostered support in WMO for more systematic
long-term planning of national and international investment in the infrastructure for
service provision (WMO, 1982).
At the same time, the WMO assumption of responsibility for operational hydrology
within the United Nations system in 1975 began to strengthen the links, already in
place in some countries, between meteorological and hydrological service provision,
and opened up the scope for increased alignment between NMSs and NHSs at the
national level in those countries where they operated as separate organizations. While
this brought out some of the historically different approaches to funding and charging
for meteorological and hydrological services, it also provided the foundation for the
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more integrated approach to delivery of the benefits from weather, climate and
hydrological service provision that developed during the 1980s.
C.6
THE WORLD METEOROLOGICAL ORGANIZATION CONFERENCES
OF 1987, 1990 AND 1994
Three important developments of the early 1980s generated a heightened awareness
in WMO circles of the importance of better explaining and more rigorously
demonstrating the potential social and economic benefits from the investments in
NMHSs necessary to deliver the improved and expanded services (WMO, 1983):
–
Recognition of the major opportunities for improved service provision opened up
by the dramatic scientific and technological progress of the 1970s;
–
Greatly expanded capabilities for use of met/hydro products and services for
improved decisionmaking in weather- and climate-sensitive sectors;
–
The severe downward pressure developing on the budgets of NMHSs of both
developed and developing countries.
As an integral part of its long-term planning system introduced in the early 1980s,
aimed at delivering the benefits of the scientific progress of the previous decade and
bridging the gap between the NMHSs of the developing and developed countries
(Zillman, 1984), WMO organized three major international conferences focused on
SEBs of improved services:
–
Symposium on Education and Training with Emphasis on the Optimal Use of
Meteorological Information and Products by all Potential Users, at Shinfield
Park, United Kingdom, 13–18 July 1987. The symposium was attended by more
than 150 participants from 72 countries with some 42 papers focused particularly
on applications and benefits in the area of water resources, environment,
agricultural production and urban and regional development (Price-Budgen,
1990). The participants identified 10 key issues involved in enhancing the benefits
from improved services;
–
Technical Conference on Economic and Social Benefits of Meteorological and
Hydrological Services, in Geneva, 26–30 March 1990 (WMO, 1990a). The
conference was attended by 125 participants from 67 countries with some 61
papers presented under five major topics focused especially on evaluation
methodologies, user requirements and the role of NMHSs in economic and social
development. The outcome of the conference was directed particularly at
informing the 1991 World Meteorological Congress approval of the WMO Third
Long-term Plan, including the establishment of the proposed new WMO Public
Weather Services Programme (WMO, 2007c);
APPENDIX C. A SHORT HISTORY OF STUDIES OF SOCIOECONOMIC BENEFITS
OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
–
173
Conference on the Economic Benefits of Meteorological and Hydrological
Services, in Geneva, 19–23 September 1994 (WMO, 1994). The conference was
held in collaboration with several other United Nations system organizations and
was attended by more than 250 participants from 127 countries. Its objective was
to review methodologies and assess SEBs of NMHSs. The benefits were estimated
to be five to ten times the investments made by NMHSs. The conference
recommended that economic benefit analysis should be further developed and
refined to underpin continued and increased government funding of NMHSs,
and to stimulate revenue, as appropriate, from the private sector.
The outcome of the WMO conferences played a significant part in influencing WMO
policies and strategy through the 1990s, especially in shaping the international
handling of the difficult commercialization and data exchange debates of the period
(for example, Bautista Perez, 1996; Zillman, 1999).
C.7
CLIMATE INFORMATION AND SERVICES
Studies of the economic benefits of climatological services date from the 1970s (for
example, WMO, 1975a). However, the establishment of the World Climate Programme
in 1979, with one of its four main focuses on enhancing the application of climate
information and services, led to greatly increased awareness of the benefits potentially
available from informed use of climate information. A major effort commenced on the
demonstration and delivery of the benefits available from the effective use of climate
information, especially through provision of enhanced access to historical climate
records in developing countries through the highly successful CLICOM programme
(Boldirev, 1991; Bruce, 1991).
The 1990 Second World Climate Conference decision to establish the comprehensive
GCOS was based heavily on the recognition of the enormous potential benefits from
improved climate data in all countries that had emerged from the WMO “Economic
Benefits” conference earlier in that year, together with the findings of the 1990 First
Assessment Report of the IPCC. The GCOS Joint Scientific and Technical Committee
established an expert working group on SEBs, which provided initial estimates of the
likely benefits of providing an effective GCOS at between US$ 5 billion and
US$ 10 billion per annum (GCOS, 1995).
Work on the economic value of climate information and services continued under the
leadership of the WMO Commission for Climatology and the World Climate
Applications and Services Programme, with a major review of studies to that date
published in 1996 (WMO, 1996). The economic value of climate forecasts featured
strongly again at the 1997 International Conference on the World Climate Research
Programme (WMO, 1997) and in the successive sessions of the Interagency Committee
on the Climate Agenda, especially in the context of the growing international focus on
the economics of human-induced climate change (for example, Cline, 1992).
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C.8
WORLD METEOROLOGICAL ORGANIZATION ECONOMIC
FRAMEWORK
By the end of the 1990s, with WMO focused strongly on efforts to better define and
strengthen the role of NMSs at the national level (Zillman, 1999), attention turned to
establishment of a more comprehensive and rigorous overall economic framework for
the provision of meteorological services. Following a number of national studies and
consideration by a WMO Executive Council Advisory Group on the Role and Operation
of NMHSs over the period 1999–2001, WMO convened an Expert Meeting on the
Economic Framework for Meteorology in Geneva, 25–27 March 2002. The overall
framework document (WMO, 2002), subsequently endorsed by the WMO Executive
Council, elaborated a range of economic concepts bearing on meteorological service
provision and outlined the essential elements of such a framework under four broad
headings:
–
The mechanisms for evaluating the costs and benefits of meteorological services;
–
The economic characterization of meteorological service provision;
–
Competition policy issues that affect the provision of meteorological services;
–
Issues related to international exchange of meteorological information.
C.9
MADRID CONFERENCE AND ACTION PLAN
Following the adoption of the WMO Economic Framework, the 2003 fourteenth World
Meteorological Congress agreed on the need for a high-level conference on the
benefits of weather, climate and water services. The Government of Spain subsequently
agreed to host such a conference in Madrid in 2007.
Preparatory regional workshops focused especially on economic case studies were
held in Brazil, Croatia, Kenya, Kuwait, Mali, the Philippines and the United Republic of
Tanzania over the period November 2005 to February 2007, and the International
Conference on Secure and Sustainable Living: Social and Economic Benefits of
Weather, Climate and Water Services (the Madrid Conference) was held in Madrid on
19–22 March 2007 under the patronage of Her Majesty Queen Sofia of Spain. The
conference was attended by some 450 participants from 115 countries who reviewed
evaluation methodologies and case studies of the benefits of weather-, climate- and
water-related information and services in six major socioeconomic sectors including:
–
Agriculture, water resources and the natural environment;
–
Human health;
–
Tourism and human welfare;
APPENDIX C. A SHORT HISTORY OF STUDIES OF SOCIOECONOMIC BENEFITS
OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
–
Energy, transport and communications;
–
Urban settlement and sustainable development;
–
Economics and financial services.
175
The Madrid Conference was supported by a substantial publication (Elements for Life
(WMO, 2007a)) containing sectoral and other case studies (Rogers et al., 2007)
including several papers (for example, WMO, 2007d) on evaluation methodologies. In
its final session, the conference participants agreed on a Madrid Conference Statement
and Action Plan (WMO, 2007e, 2009a) that summarized the essential conclusions on
the current state of knowledge on the SEBs of met/hydro services and proposed a
five-year strategy for further enhancing and evaluating those benefits.
The overall objective of the agreed 15-point Action Plan, which was subsequently
endorsed by the 2007 World Meteorological Congress, was to achieve, within five
years, a major enhancement of the value to society of weather, climate and water
information and services in response to the critical challenges represented by rapid
urbanization, economic globalization, environmental degradation, natural hazards
and the threats from climate change. Action 11 focused specifically on valuation
methodologies in the following terms:
–
C.10
Encourage the NMHSs and the social science research community to develop
knowledge and methodologies for quantifying the benefits of the services
provided by NMHSs within the various socioeconomic sectors, in particular:
–
Develop new economic assessment techniques including especially
techniques of economic assessments for developing and least developed
countries;
–
Develop WMO guidelines on operational use of economic assessment
techniques;
–
Train national staff on the use and practical application of economic
assessment of the benefits of services provided by NMHSs;
–
Present results of economic assessments to governments and donors or
international financial institutions with the goal of modernizing the
infrastructure of NMHSs and strengthening their service delivery capacity.
WORLD METEOROLOGICAL ORGANIZATION TASK FORCE, FORUM
AND POST-MADRID ACTIVITIES
In the lead-up to, and follow-up from, the Madrid Conference, the main focus on
economic valuation in WMO resided with the Public Weather Services Programme and
its Task Force on Socioeconomic Applications of Public Weather Services, later
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broadened to Task Force on Socio-Applications of Meteorological and Hydrological
Services, and subsequently retitled WMO Forum: Social and Economic Applications
and Benefits of Weather, Climate and Water Services.
The WMO Task Force provided much of the initial input to planning for the Madrid
Conference and guidance to the WMO Secretariat on follow-up work on the Madrid
Action Plan as adopted by the 2007 congress. This included a significant emphasis on
economic benefit issues in post-Madrid public weather service workshops for
developing countries (for example, Zillman, 2007) and the initiation of a series of
economic valuation studies in individual WMO regions – especially in Europe under
the guidance of a Regional Association VI Task Team on Social-Economic Benefits
(Perrels et al., 2013).
In conjunction with the increased emphasis on economic valuation of meteorological
services in the lead up to the Madrid Conference, the WMO Hydrology and Water
Resources Programme initiated preparation of a comprehensive document Guidelines
on Valuation of Hydrological Services (WMO, 2007f), which included a comprehensive
bibliography on the economic value of hydrological services and a useful overview of
methodologies for use by NHSs.
Several other WMO programmes including, especially, the World Weather Research
Programme and the WMO–Intergovernmental Oceanographic Commission–
International Council for Science World Climate Research Programme are now also
placing considerable emphasis on assessment and demonstration of the societal
benefits of weather and climate research.
C.11
WORLD BANK STUDIES OF ECONOMIC BENEFITS
The World Bank was first faced with the need to develop a methodology for an express
assessment of economic efficiency of an NMS in 2003 while preparing the National
Hydrometeorological Modernization Project in the Russian Federation (WMO, 2008;
Hancock and Tsirkunov, 2013). In light of the Roshydromet experience, the World Bank
initially worked with a number of NMHSs in Eastern Europe and Asia on the
development and application of new and simplified approaches for assessing the
current economic benefits from existing NMHSs and, especially, for estimating the
additional economic benefits potentially available from their upgrading and
modernization (WMO, 2007b). The Bank approach relied heavily on bench-marking
with two stages: determining the benefits; and correcting them according to countryspecific characteristics.
Following the close collaboration between the World Bank and WMO in the
organization of the Madrid Conference and its immediate follow-up, and in the light of
further World Bank studies (for example, Hallegatte, 2012) and modernization projects
in the context of natural disaster reduction and climate change, most of the earlier
experience was brought together for internal World Bank guidance purposes in the
publication Weather and Climate Resilience – Effective Preparedness through National
APPENDIX C. A SHORT HISTORY OF STUDIES OF SOCIOECONOMIC BENEFITS
OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
177
Meteorological and Hydrological Services (Rogers and Tsirkunov, 2013). While this latter
publication goes well beyond the issues of benefit assessment to provide a
comprehensive view of the potential role of modernized NMHSs (cf. Appendix B), it
also provides a useful overview of the World Bank’s approach to economic aspects of
the organization and operation of NMHSs.
C.12
GLOBAL FRAMEWORK FOR CLIMATE SERVICES AND CLIMATE
SERVICES PARTNERSHIP ACTIVITIES
The 2009 World Climate Conference-3 decided to establish a new GFCS to strengthen
the production, availability, delivery and application of science-based climate
prediction and services (WMO, 2009b). The conference and the follow-up high-level
task force (WMO, 2011) placed special emphasis on enhancement of the sectoral and
national benefits from more effective application of met/hydro services in all of the
many climate-sensitive sectors of society. In addition to its emphasis on the various
other pillars of the framework, especially the need for an effectively operating GCOS
(Houghton et al., 2012), the GFCS Implementation Plan (WMO, 2014) approved by the
October 2012 Extraordinary World Meteorological Congress focused particularly on
issues of service delivery and application in enhancing the societal benefits from
climate information.
One particularly significant implementation mechanism for the GFCS is the CSP, which
originated from the (first) International Conference on Climate Services held in New
York in October 2011. The Climate Services Partnership established a Working Group
on Economic Valuation of Climate Services, with one of its first tasks being a
comprehensive assessment of recent published literature on the economic value of
met/hydro services (Clements et al., 2013).
C.13
RECENT STUDIES
Following the Madrid Conference and partly stimulated by it, a number of NMHSs and
individual researchers initiated a range of new economic benefit studies using
established methodologies. These include:
–
A comprehensive study of the economic benefits of weather and marine services
in India (National Council of Applied Economic Research, 2010);
–
A study of the economic benefit of meteorology in the Swiss road transport sector
(Frei et al., 2012);
–
A study of the value of historical climate knowledge and Southern Oscillation
Index-based seasonal climate forecasting on cropping in south-east Australia
(Wang et al., 2008).
178
C.14
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
VALUATION METHODOLOGIES
While determination and demonstration of the benefits of met/hydro services are, in
one sense, just a small subset of the wide range of approaches to determining the
economic value of information (Stiglitz et al., 2000), the meteorological economics
literature of the past 60 years summarized above includes a number of important
attempts to frame the various general valuation approaches in a form for specific
application to met/hydro services and especially to the operation of NMHSs.
Some of the more significant contributions have included the following:
–
World Weather Watch Planning Report No. 17 (1967) that provided simple
guidelines in a form for ready application by NMSs;
–
The WMO publication (WMO, 1975b) that sought to provide more explicit
guidance for use by NMS staff;
–
An analysis by Freebairn (1979) that addressed some of the methodological
challenges of valuation within a broader economic framework;
–
The WMO Conferences in 1990 and 1994, the proceedings of which include a
substantial number of papers outlining new and more refined approaches to
economic valuation of met/hydro services;
–
The report by Chapman (1992) that elaborated a methodology for assessing the
marginal benefits of modernization of the United States NWS;
–
The work of Anaman et al. (1995, 1998) that further developed the various
available methodologies and demonstrated their application to a range of
services provided by the Australian Bureau of Meteorology;
–
The publication edited by Katz and Murphy (1997) that provided the first
comprehensive treatise on methods for assessment of the economic value of
weather and climate forecasts;
–
Three papers (Zillman and Freebairn, 2001: Freebairn and Zillman, 2002a, 2002b)
that attempted to provide an overall economic framework for funding and
charging for meteorological services and a summary of available methodologies
for valuation of benefits;
–
A monograph by Gunasekera (2004) elaborating and demonstrating the
application of available methodologies via a series of case study summaries from
around the world;
–
The WMO guidelines document on valuation of hydrological services (WMO,
2007f);
APPENDIX C. A SHORT HISTORY OF STUDIES OF SOCIOECONOMIC BENEFITS
OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
–
179
The 2009 Primer on Economics for National Meteorological and Hydrological Services
(Lazo et al., 2009) aimed at providing a simple overview for non-economist staff
of NMHSs on the methodologies for BCA for met/hydro services.
While these and the many other publications on valuation theory and methodology
present a useful overview of progress over the past 60 years, they do not provide the
integrated conceptual approach and practical guidance, which is the primary objective
of this publication.
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APPENDIX D. COMPLEMENTARY ROLES FOR OTHER
SOCIAL SCIENCE APPLICATIONS IN SOCIOECONOMIC
BENEFIT STUDIES
D.1
INTRODUCTION: MORE THAN JUST ECONOMICS
For the purposes of this appendix, the focus is on those social sciences, not including
economics, that aim to describe, understand, or explain the human condition in
relation to its natural and social environment – it explicitly includes the social,
behavioural, and decision sciences. From an epistemological point of view, social
sciences are diverse, characterized by a wide breadth of disciplines, paradigms,
methodologies, national traditions and underlying political and social philosophies
(International Social Science Council, 2010). In other words, there isn’t one social
science – there are many – with great variation found even within individual disciplines
(for example, see the American Economic Association’s Journal of Economic Literature
classification system for a breakdown of subfields within economics).
Although much of this report is focused on the techniques and applications of
economics to benefit assessment, a number of other social science disciplines and
professions offer salient contributions to the overall evaluation of met/hydro services.
In some cases, for instance in developing robust survey designs, the practices are
already embodied within economic benefit assessment. In others, social scientific
approaches, methods, techniques and findings serve to complement the economic
studies and assist with contextualizing, extrapolating, qualifying and interpreting
results and their relevance for policy and decisionmaking. Thus, in these latter cases, a
better overall understanding of value results is achieved when other social sciences are
included in the overall SEB analysis.
The following social science fields are most commonly found to report applications
relevant for weather, climate and water: anthropology, applied health studies,
communication studies, economics, valuation research, human and hazards
geography, political science, psychology and sociology. Several recently published
example studies outside the field of economics are noted in Table D.1 for illustration.
Fundamentally, such research attempts to explain or evaluate critical assumptions
about the nature of human behaviour, in relation to weather, climate or water, and
decisionmaking, both generally and in the face of uncertainty. Researchers focused on
weather applications tend to draw from the instrumental (that is, problem-solving)
and, to a lesser extent, interpretive orientations in social science, rather than from the
critical perspective. As ethical issues continue to emerge, for instance regarding the
availability of potentially life-saving forecast information services to vulnerable
populations in developing nations, critical contributions from social science and
humanities fields such as philosophy and history may become more numerous and
important in the future.
Applications of social science methods, for instance in the form of satisfaction surveys
or focus groups with important users, have traditionally been used by NMHSs to
demonstrate their worth or influence and to provide evidence to justify budget
allocations and investments that are continually being challenged and tested for
alternative beneficial uses. Historically, social science input and applications have been
APPENDIX D. COMPLEMENTARY ROLES FOR OTHER SOCIAL SCIENCE APPLICATIONS
IN SOCIOECONOMIC BENEFIT STUDIES
185
Table D.1. Recent examples of peer-reviewed weather-related social science studies
Field/discipline
Title/reference
Contribution relevant to SEB analysis
Anthropology
Making use of hidden data:
Towards a database of weather
predictors (Pennesi, 2012)
Explores the challenge and benefits of
uncovering and documenting unique
local and cultural terms used to predict
weather
Applied health
studies
An evaluation of the progress in
reducing heat-related human
mortality in major U.S. cities
(Kalkstein et al., 2011)
Developed and applied a method to
indirectly assess the impact of early
warning systems and associated
services to cope with excessive heat
events in 40 large United States cities
Decision
sciences
Factors affecting the value of
environmental predictions to
the energy sector (Davison et al.,
2012)
Defined, explained and applied a series
of simple decision experiments based
on expert/stakeholder knowledge
to estimate the potential impact of
weather-related information
Hazards
geography
Social vulnerability and hurricane
impact modelling (Burton, 2010)
A social vulnerability index was
developed and combined with
physical hazard indicators to explore
the relationships between social
vulnerability and hurricane damage
Inter-disciplinary Exploring variations in people’s
sources, uses, and perceptions of
weather forecasts (Demuth et al.,
2011)
Applied factor and regression analysis
to data from a nationwide survey of
the United States public to understand
patterns in people’s sources,
uses and perceptions of everyday
weather forecasts and relationships
with personal characteristics and
experiences using forecasts
Psychology
Explored anchoring and correction
biases within the context of numeric
weather forecast information and
uncertainty
Reducing probabilistic weather
forecasts to the worst-case
scenario: Anchoring effects
(Joslyn et al., 2011)
sought rather irregularly, often in response to political or public pressure in the wake of
a major weather event. More often, however, this knowledge of value and impact is
now viewed as an intrinsic and continuous part of service planning and operations in
larger service agencies and as essential tools to develop new clientele in the private
meteorological sector. Encouraged by WMO and the World Bank, NMHSs seem to
generally accept that a better understanding of the use and value of providing
meteorological, hydrometeorological and climatological information could be
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fundamental input to measuring and improving services or making critical decisions
with respect to the application of new technologies and changes to existing
monitoring networks, observation strategies, communications, computer
infrastructure, human resource management and priorities for research and
development.
There remains, however, a need to produce and gain experience from more in-depth
and robust social science applications, especially in developing and non-Western
countries, and to analyse and develop better practices. Towards this end, Appendix D
will illustrate and recommend a few uses of social science methods in two critical yet
overlapping application areas pertinent to NMHSs and SEB evaluation: (a) identifying
and understanding user problems, needs and perceptions; (b) evaluating products
and services.
D.2
IDENTIFYING AND UNDERSTANDING USER PROBLEMS, NEEDS
AND PERCEPTIONS
D.2.1
An informed inventory of products, services and intraorganization perceptions
Understanding the audience (users, clientele, market, customers, stakeholders), its
problems, needs and perceptions, and use of existing products and services, is an
essential activity for modern NMHSs and one in which social science methods play an
important role. A seemingly mundane first step in this process, but one that is
important before commencing the evaluation of the products and services delivered, is
to identify what an NMHS or other producer provides and the rationale for doing so.
Such an exercise could be geared to support a whole-of-service assessment (that is, the
entire NMHS) or it might be confined to a sector, subset or package of services (for
example, surface transportation) depending on the nature of the larger SEB study.
With the possible exception of the few NMHSs that operate largely on a cost-recovery
or profit model, for example those of the United Kingdom or New Zealand, most
agencies cannot easily point to a comprehensive document that summarizes the
character and intent of their services and the clients, stakeholders and citizens who
utilize them.
This inward-looking exercise should go beyond a simple shopping list of variables or
elements (for example, temperature forecasts) and include reflective commentary on
the following aspects of particular products and services: information/message
content, attributes related to precision and quality, frequency, duration, format, means
of distribution/dissemination, production and dissemination process, support services
assisting with interpretation, competing/complementing products from other sources,
target audience, intended/expected use and historical evolution of the product/service.
Such an annotated inventory may assist the economic analysis of an SEB assessment,
for example in articulating and framing the weather information product in a CV
APPENDIX D. COMPLEMENTARY ROLES FOR OTHER SOCIAL SCIENCE APPLICATIONS
IN SOCIOECONOMIC BENEFIT STUDIES
187
survey instrument. The most important aspects though are the perceptions of the
developers/producers concerning their target audience, the intended or expected use
of the information and resulting outcomes. Differences in perceptions between those
developing a product/service and those of the intended user audience may point to
significant sources of untapped or poorly developed value (that is, disconnections
between services and needs). The final element of the inventory – historic evolution –
captures the development timeline for the product or service. Sorting through the
primary drivers of service changes (including cessation of a product/service), which
often are motivated by technological advances but also user demand, political,
institutional and financial factors, may assist in the value assessment, especially when
interpreting sensitivities to external factors (sensitivity scenarios) or clarifying recall
bias among survey respondents or interviewees.
Much of the basic information required to complete an inventory may be obtained by
canvassing general NMHS dissemination platforms (largely Internet based) and
through reviews of existing and historical NMHS operational, planning and annual
reporting documents. The information can be verified using qualitative interviews and
focus groups with participants selected (most likely in a non-random fashion) from
those engaged in the production and delivery of information and services.
Intraorganization perceptions and beliefs about the intended and expected uses of
information would also be solicited through this process. Interview questions could be
complemented with an individual or group exercise to define value chains (or influence
diagrams and logic models) specific to the targeted service. An online survey to obtain
the same information might be warranted if it was important to verify the
representativeness of the expressed opinions across an entire NMHS organization. All
elements would need to be scoped to the geographic, social and organizational
dimensions of the service and NMHS under examination.
D.2.2
Understanding actual use and information needs
A subsequent step involves moving from what was, and currently is, provided to how
such products and services are actually being used, by whom and for what purpose.
Bounded by the scope of the SEB assessment, an initial list of users can be compiled from
those identified by NMHS participants in the previous inventory exercise. To supplement
the initial user set, it may be possible to draw upon several other sources of information
within the domain of an NMHS (or neighbouring NHMSs, WMO, and the like). Such
sources could include: client databases; contract and service agreements; product/
service requests, inquiries, feedback forms and data/product download records;
completed internal needs/use surveys, assessments and stakeholder workshops.
Invariably, the list will be composed of entrants from the following categories:
–
Private enterprise, non-governmental organizations and public sector institutions
that provide, communicate and tailor weather and related risk or impact
information, advice and services to their clients/constituents/audiences in support
of decisionmaking;
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–
Businesses, organizations and government agencies with experience in, and
responsibility for, managing weather-related risks and opportunities;
–
Various segments of the general public engaging in weather-sensitive activities.
Needs are likely to extend to other weather- or climate-sensitive actors not yet currently
served by a particular NMHS. Identifying such users may require incorporation of
other information, as may be obtained through a content analysis of weather-related
media reports (to screen for those sectors, organizations, communities and
populations that are affected by an event) or a systematic review of the peer-reviewed
literature. For example, a state-level study by Lazo et al. (2011) revealed high degrees
of weather sensitivity in the real estate, insurance and finance sectors of the United
States economy relative to those sectors traditionally thought of as being significantly
affected by variable weather conditions (for example, agriculture and transport). The
broader weather and climate-related impact literature, for example in hazards and
applied meteorology, contains studies reporting on a wide range of additional
sensitivities that may also define or indicate potential underserved users and needs.
The final compilation of users serves as the sampling frame for exploration of decision
problems, preferences, perceptions and needs. Different types of social science
methods may be employed at this stage, but they generally break down into two
categories: (a) direct solicitation of the opinions and perceptions of representative
users or experts (stated preferences/intentions); (b) analysis of actual behaviour and
decisionmaking (revealed preferences/intentions). Budget, time and available
expertise permitting, it is best to use a mix of techniques from both categories to test
and corroborate findings.
Direct solicitation of opinion is typically conducted through self-administered,
telephone, or computer-aided survey questionnaires, or through face-to-face
interviews. Several example surveys and some general guidance are posted on the
WMO website. Closed (that is, the respondent chooses from the options provided) or
open (the respondent freely responds or “thinks aloud”) questioning can be used in
both questionnaire and interview formats. Closed questions are best used when one is
interested in testing hypotheses about relationships between variables and making
statistical inferences about the sampled populations (for example, do all emergency
managers making evacuation-order decisions have similar risk tolerances for particular
weather-related hazards?). Open-format questions and interviews are preferred for
exploratory research that aims to generate new ideas and often offer richer insight into
a topic (that is, through dialogue about real situations and examples). It often makes
sense to conduct a limited number of open format interviews and, through coding of
results, use the findings to develop a structured survey with closed questions.
While noting the need to tailor applications to specific NMHSs, and the inherent
difficulty in prescribing a ubiquitous instrument and approach, there are some general
elements that should be addressed. As in most surveys, collecting information about
sociodemographic characteristics, education levels, practical experience, risk-taking, or
other basic psychological profiles help to situate respondents relative to the larger
population. As noted by Weaver et al. (2014) for emergency managers there can be a
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189
rather large degree of variation across individuals for certain characteristics, which in
turn may significantly influence the generalizability of responses.
In terms of content, survey and interview questions should be designed and tested to
elicit input regarding the types of problems and opportunities confronting the unit of
analysis – be it a business, organization, community, household or individual – and the
various weather and non-weather factors that influence decisions and behaviours. The
instrument should reveal the temporal, social, organizational and spatial scales and
context of decisionmaking and extract formal decision thresholds (including attendant
certainty or confidence levels), informal rules (such as rules of thumb, instinct, cues,
and the like) and important information attributes from respondents. Furthermore,
there should be some appreciation of the extent to which respondents rely upon
cognitive/rationale or emotive/affective processes when making decisions. In addition
to decision processes, questions should be aimed at identifying outcomes of
importance to the user, noting that these might extend beyond the more obvious, and
measurable, things such as “injury avoidance” or “dollars of damage or profit”, to more
qualitative things embodied in feelings (for example, sense of accomplishment, safety,
assurance or flexibility). Finally, the survey or interview can include questions to solicit
input regarding the benefits of realizing outcomes as well as the costs and implications
of failing to achieve them – aspects that have been alluded to in Chapters 4–7.
The previous elements create a composite picture of the relative role and importance of
weather and weather information within the decisionmaking context of the
respondent – making it possible to derive needs either indirectly from the interview or
questionnaire responses or directly through a final set of questions focused on stated
information needs. The stated requirements may be combined with a series of focus
groups, meetings, workshops or symposia to develop a general set of needs or to
establish priorities at a higher order or scale. A very successful example of this type of
activity is documented in Weather Information for Surface Transportation: National Needs
Assessment Report, developed in the United States (Office of the Federal Coordinator for
Meteorological Services and Supporting Research, 2002).
Even the most carefully designed stated-preference survey cannot entirely avoid the
potential mismatch between what people say they do and what they actually do.
Fortunately, a range of techniques have been developed in social science to analyse
actual behaviour, some based upon original data collection and others based on
secondary or existing data. Field research and analysis of existing data are discussed
below, while other techniques, including experimentation, are introduced later on in
the appendix as part of the evaluation discussion.
Field research, pioneered in anthropology and sociology disciplines, aims to immerse
the researcher in the real-world environment of particular sets or classes of
decisionmakers, for example emergency managers, in order to observe, interact with
and learn from them. A qualitative approach, it enables researchers to gain a very
detailed and personal account of the actors’ decisionmaking processes, interactions
with others and how they make sense of the world. Observations in the form of notes,
audio or video recordings and maps or diagrams are typically collected over a period of
time that is much longer than the traditional interview (that is, days, weeks or months).
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Patterns, explanations and theory are developed inductively and iteratively through
the course of the research in contrast to the deductive, hypothesis-testing designs
adopted in many quantitative social science studies.
Not surprisingly, field research, as well as the interviewing methods already discussed,
place the researcher in a position to potentially influence what a respondent or
observant says or does. “Unobtrusive approaches” (also called “non-reactive”) are
available to address such concerns, though the trade-off is often a lack of complete
control over the collection and structure of the data. Content analysis is a technique
used to decipher meaning from various forms of communication, for example
newspaper articles. How often a term, phrase or reference to a behaviour, product,
issue, and the like, is used and with what intent (for example, associated with a
particular quality or meaning – such as good, bad, successful or failed) become the
data subject to analysis. Any form of communication could be used, including radio or
television weather reports, text-based weather forecasts or warnings, press releases
and reports from weather-sensitive organizations, and even electronic records such as
e-mail exchanges. One of the greatest potential sources of data for content analysis
research is publicly available records of social media exchanges. Because such sources
are not designed specifically for the intended research, it is crucial to ensure that the
terms and phrases chosen to indicate a particular important variable or meaning are
valid and applied consistently in the analysis.
Existing data originally collected for another purpose is sometimes available for use in
estimating the occurrence of certain behaviours of interest and assessing the validity or
extent of perceived impacts. The extent to which people say they are sensitive to, or
engage in actions given information about, a weather-related hazard or opportunity
can be examined and verified. For example, traffic and modal-share data can indicate
trip cancellation, route-altering and speed adjustment behaviour among motorists and
evacuation participation levels; Internet and telecommunications data can suggest risk
information-seeking patterns associated with storms; retail purchasing information can
point to behaviours associated with preparedness (for example, generators or plywood
in advance of a hurricane; dwelling location choice and style in consideration of
flooding potential); and hospitalization or other medical care data can be used to
estimate the impact of certain weather-related conditions on health and level of
response (that is, people seeking care). As this type of data are usually available only at
an aggregate level (a large region, population or long time period) the scalability of
inferences to individual behaviour is always subject to some assumptions.
Nevertheless, it makes a useful complement to stated-preference studies and is often
utilized to estimate or generalize exposure levels in economic studies.
D.3
EVALUATION OF MET/HYDRO PRODUCTS OR SERVICES
Another area of application where social scientific methods may assist NMHSs is in the
development and evaluation of existing or planned products and services. Evaluation
research has a long-standing tradition in social science and is the subject of several
academic journals (for example, the American Journal of Evaluation and Evaluation and
APPENDIX D. COMPLEMENTARY ROLES FOR OTHER SOCIAL SCIENCE APPLICATIONS
IN SOCIOECONOMIC BENEFIT STUDIES
191
Program Planning). The intent, of course, is to assess the merits of a particular
programme or activity and NMHSs have been quite active in recent years in collecting
and analysing such information to help them quantify, qualify and otherwise articulate
their worth to funders and users. As noted in Table D.2, a variety of performance
indicators have been used or cited in NMHS annual corporate reports and, above all,
internal studies.
Table D.2. A range of indicators and associated example measures and methods
used to evaluate meteorological warnings issued by NMHSs
NMHS performance
indicator
Warning is accurate
(location, timing,
severity)
Example measures
Example methods
– Traditional numerical verification
(for example, probability of
detection, false alarm ratio)
– Statistical analysis of
warning forecasts relative
to observations
– Survey to assess public or
– Likert rating scale
user-specific opinion
(for example, 1–5) or percentage
of time correct/accurate
Warning is disseminated
– Counts of warnings issued to
public/users over a period of
time
– Summation of warnings
by region, time period,
channel
– Descriptive or relative
statistics over longer
period of time (multi-year
trend in annual counts)
Warning reaches
intended audience
(that is, penetration)
– Percentage of population
receiving warnings
– Survey to assess public or
user-specific opinion
– Unique website “hits”
– Analysis of Internet
statistics
– Post-event interviews
Warning meaning is
understood as intended
(factual content)
– Percentage of correct
interpretations (that is, intended
by NMHS) by public/users
– Survey to assess public or
user-specific opinion
– Post-event interviews
Warning consequences
and suggested actions
are understood
– Percentage of correct
interpretations (that is, intended
by NMHS) by public/users
– Survey to assess public or
user-specific opinion
Behavioural intent
– Percentage of people intending
to take action in response to the
warning
– Survey to assess public or
user-specific opinion
Satisfaction with
warnings
– Likert rating scale
(for example, 1–5) of degree of
time satisfied
– Survey to assess public or
user-specific opinion
– Percentage of time satisfied
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The indicators, measures and methods in Table D.2 are limited in terms of assessing the
influence of a product or service on the actual use of weather information in
decisionmaking and associated outcomes. Experimental social research, whether
based on observations from “natural” experiments (for example, comparing those
affected or unaffected by a particular weather disaster) or simulated/laboratory
settings, offers an alternative structured approach to quantify such variables. Often the
biggest concern with the former is how best to control for factors that may offer
alternative explanations for the findings, while generalizability to the “real world” can
be problematic for the controlled, laboratory experiment (for example, raising
questions about external validity).
The classical experimental design involves conducting pre- and post-intervention tests
on randomly assigned control and treatment groups. Its intent is to isolate the effect of
the intervention, thus making the identification of causal relationships between
independent and dependent variables more likely – for instance between hurricane
warning advice and evacuation participation. Not surprisingly, it generally isn’t
possible, desirable or ethical to intentionally deny a population the best available
warning information or service in advance of a particular weather condition. Thus
quasi-experimental designs, where some aspects of the classical design are relaxed (for
example, no control group used but one group repeatedly measured several times
before and after the product/service is in place), are more likely to be utilized. For
example, Joslyn et al. (2011) assessed the relative merits of different approaches to
characterizing uncertainty in weather forecasts (probability of precipitation) using a
survey delivered to a convenience sample of undergraduate psychology students.
Implicit in many measures and experiments is a sense of what should be evaluated.
From an academic perspective, this is usually made explicit and involves formal testing
of a hypothesis or element of theory. For an NMHS, however, the use of experiments is
more pragmatic – did or will a particular service or product perform well? Thus, one
sees many contracted studies, internal reports, and the like, that focus on a particular
output or outcome measurement (for example, 65% of the public are very satisfied
with our 1–2-day forecasts) with minimal attention to the interpretation of the result,
important processes and the testing of alternative explanations that might yield
valuable information for designing and assessing services. In other words, there is a
need to expose and understand the theories of behavioural change implicit in the
evaluation.
Fortunately, the evaluation literature offers a holistic approach to make these theories
explicit and, in doing so, guide an evaluation. A “theory-driven evaluation” moves the
exercise from documenting evidence of impact, through causal description and
ultimately to causal explanation of why and how this particular intervention changes
outcomes given available resources and antecedent conditions. Also called “theorybased evaluation” and “programme theory”, the approach has been used extensively
and effectively in medical and health promotion applications over the past three
decades (Weiss 1997; Coryn et al., 2011). While weather-related applications seem to
be absent in the peer-reviewed literature, some in the weather community have noted
elements of the approach, typically in the form of “logic modelling”. A logic model is a
tool used to articulate the linkages among sets of components within a programme,
APPENDIX D. COMPLEMENTARY ROLES FOR OTHER SOCIAL SCIENCE APPLICATIONS
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193
including: inputs; activities; outputs; and short-term, intermediate and longer-term
outcomes (MacLaughlin and Jordan, 1999). A partial NMHS-related example, focused
exclusively upon activities and outcome sets, was developed by Gordon and
Shaykewich (WMO, 2000) and is provided in Figure D.1.
The theory of change in the example figure is not specified in much detail, as its
original use was chiefly illustrative. Nevertheless, one can infer a type of “knowledgeattitudes-action” model of change in the diagram. The various activities in the
operational outcomes somehow lead to a chain of intermediate outcomes whereby an
increase in the awareness of information (that is, a future weather condition/state and
its implications) among users affects their decisions and behaviours such that impacts
are reduced (ultimate outcomes). It is these processes and inter-linkages that become
the additional focuses of the evaluation – quantitative, qualitative or mixed methods
and supporting data would then be selected and collected to test the presence,
validity and strength of any supposed relationships. Ideally, the evaluation of a
particular change in services is conducted as part of the initial design (that is, screened
against the underlying theory to assess potential effectiveness) and then monitored
over time through its entire lifecycle. Underachievement may be a function of a failure
Balanced scorecard
performance logic model
tcomes
Operational ou
Government
policy and
financial
management
activities
Human
resource
activities:
- Competencies
- Capacity
- Recruitment
- Training
Service
delivery
activities:
- Direct to
citizens
- Through
partners
(media, etc)
Scientific
activities:
- Monitoring
- Prediction
- R+D
Direct control
tcomes
Intermediate ou
Increased
awareness
Modified
decisions
Modified
behaviours
es
Ultimate outcom
Reduced impact
on health,
safety and
economy
Increased
satisfaction
Etcetera!
Direct influence
Adaptation
to atmospheric,
hydrologic
and ice
conditions
Indirect influence
Balanced scoreca
rd
Figure D.1. Generic logic model of NMHS performance
Source: WMO (2000)
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VALUING WEATHER AND CLIMATE:
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in programme implementation, of the contextual or situational inappropriateness of
the theory, or a failure of the theory itself.
A more robust theory of change might draw upon aspects of behavioural models in
psychology and social psychology, for example social cognitive theory (Bandura, 1991)
and the theory of planned behaviour (Azjen, 1991). It might also be developed
inductively through empirical observation of cases, or through consultation and
interaction with users (Patton, 2008). Many of the social science contributions to
understanding suggested in previous sections will assist in the development of logic
models and explicit characterization of theories of change or action, and ultimately
through to effective applications and services that achieve outcomes.
D.4
FINDING EXPERTISE AND BUILDING CAPACITY TO CONDUCT
SOCIAL SCIENTIFIC RESEARCH AND APPLICATIONS
The previous two sections propose new or expanded kinds of activities and methods to
identify and explore user needs and to evaluate weather, water and climate services.
For an already fiscally lean or extended NMHS, this likely means reallocating resources,
finding extra efficiencies, or developing creative partnerships to sustain a social
scientific programme. Even if resources are made available, the task of finding and
retaining access to suitable expertise may be a challenge. Larger NMHSs or those
associated with or mandated to manage other government functions (for example,
pertaining to water, environment, natural resources, or transportation) might employ
or have access to social science and policy analysis expertise. Most organizations, and
certainly smaller services, must rely upon academic institutions or the private sector
consulting industry for support. In some cases it may be possible to examine existing
relationships with national universities where an NMHS already has an established
agreement or partnership, for example in training atmospheric scientists, hydrologists
or forecasters. Most large institutions will have programmes in psychology, sociology,
anthropology, geography, business/marketing/communications, economics and
health-related disciplines where expertise can be sought. Where endogenous capacity
and expertise are limited, it is hoped that WMO and its Members, the World Bank and
non-profit enterprises such as CSP will continue to help coordinate, if not conduct,
regional training sessions and establish demonstration projects to move from
classroom to applications and eventually to enhance internal capabilities.
REFERENCES
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Processes, 50(2):179–211.
Bandura, A., 1991: Social cognitive theory of self-regulation. Organizational Behavior and Human
Decision Processes, 50(2):248–281.
Burton, C.G., 2010: Social vulnerability and hurricane impact modelling. Natural Hazards Review,
11(2):58–68.
APPENDIX D. COMPLEMENTARY ROLES FOR OTHER SOCIAL SCIENCE APPLICATIONS
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Coryn, C.L.S., L.A. Noakes, C.D. Westine and D.C. Schröter, 2011: A systematic review of
theory-driven evaluation practice from 1990 to 2009. American Journal of Evaluation,
32(2):199–226.
Davison, M., A. Gurtuna, C. Masse and B. Mills, 2012: Factors affecting the value of
environmental predictions to the energy sector. Environmental Systems Research, 1:4,
DOI:10.1186/2193-2697-1-4.
Demuth, J.L., J.K. Lazo and R.E. Morss, 2011: Exploring variations in people’s sources, uses, and
perceptions of weather forecasts. Weather, Climate and Society, 3(3):177–192.
International Social Science Council, 2010: World Social Science Report 2010: Knowledge Divides.
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Joslyn, S., S. Savelli and L. Nadav-Greenberg, 2011: Reducing probabilistic weather forecasts to
the worst-case scenario: Anchoring effects. Journal of Experimental Psychology: Applied,
17(4):342–353.
Kalkstein, L.S., S. Greene, D.M. Mills and J. Samenow, 2011: An evaluation of the progress in
reducing heat-related human mortality in major U.S. cities. Natural Hazards, 56:113–129,
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Lazo, J.K., M. Lawson, P.H. Larsen and D.M. Waldman, 2011: U.S. economic sensitivity to
weather variability. Bulletin of the American Meteorological Society, 92(6):709–720.
McLaughlin, J.A. and G.B. Jordan, 1999: Logic models: A tool for telling your program’s
performance story. Evaluation and Program Planning, 11:54–61.
Office of the Federal Coordinator for Meteorological Services and Supporting Research , 2002:
Weather Information for Surface Transportation: National Needs Assessment Report (FCM-R182002). Silver Spring, Maryland, National Oceanic and Atmospheric Administration, United
States Department of Commerce.
Patton, M.Q., 2008: Utilization-focused Evaluation. Fourth edition. Thousand Oaks, California,
Sage Publications.
Pennesi, K., 2012: Making use of hidden data: Towards a database of weather predictors. Journal
of Ecological Anthropology, 15(1):81–87.
Weaver, J., L.C. Harkabus, J. Braun, S. Miller, R. Cox, J. Griffith and R.J. Mazur, 2014: An overview
of a demographic study of United States emergency managers. Bulletin of the American
Meteorological Society, 95(2):199–203.
Weiss, C.H., 1997: How can theory-based evaluation make greater headway? Evaluation Review,
21(4):501–524.
World Meteorological Organization, 2000: Guidelines on Performance Assessment of Public Weather
Services (N. Gordon and J. Shaykewich) (WMO/TD-No. 1023). Geneva.
APPENDIX E. CASE STUDIES
E.1
SUMMARY OF CASE STUDY ECONOMIC ASSESSMENTS
Part E.1 of this appendix provides an overview of the economic assessments that are
included as nine case study examples in this publication and that follow in Parts
E.2–E.10. In the following sections of E.1, background is provided on our rationale for
selecting these examples, together with a high-level summary of each assessment.
Additional information for each study appears in the detailed case study descriptions.
Background and overview
Our case study examples represent a diverse set of studies that the NMHSs and other
organizations have developed to assess the economic benefits of met/hydro services.
In selecting these examples, we have aimed to include sound economic studies that
have been conducted in various parts of the world, with an emphasis on developing
countries. We have also attempted to obtain diversity among key study parameters,
including:
–
Study objectives, for example, to obtain additional funding and justify existing
services;
–
Types of met/hydro services examined, for example, whole-of-service studies and
studies examining specialized services;
–
Types of benefits and costs analysed, for example, avoided asset losses, increased
profits and lives saved;
–
Valuation methods, for example, contingent valuation and decision models;
–
Level of aggregation, for example, sector analysis and household-level analysis.
Because relatively few NMHSs have conducted studies of the economic benefits of
met/hydro services, it was not always possible to meet our initial criteria for case study
selection. For example, several of the studies were conducted in developed countries,
and we have included one study that academic researchers initiated, rather than an
NMHS or other relevant organization (for example, international donor organizations
such as the World Bank). However, the nine studies described in Appendix E all contain
valuable information that can help NMHSs conduct or manage economic assessments
to examine the value of met/hydro services, based on their own objectives and
available resources.
The following sections provide short summaries of each case study example; more
detailed case study descriptions comprise the remainder of this appendix
(parts E.2–E.10). The detailed descriptions of each economic study provide background
on the reason that the study was conducted, describe the study methods and results,
discuss study limitations and offer suggestions for how the study could be tailored to
Appendix E. Case studies
197
individual NMHS circumstances. In developing most of the case study descriptions, we
were able to interview and receive input from a primary author of the study.
E.1.1
Case study 1: Evaluating the economic efficiency of NMHS
modernization in Europe and Central Asia using sector-specific
and benchmarking approaches
In 2003, the World Bank and Roshydromet, the NMHS of the Russian Federation,
developed a sector-specific approach, described below, to evaluate the benefits and
costs of modernizing Roshydromet’s services and products. The success of this project
encouraged the World Bank to launch similar economic studies in countries in Europe
and Central Asia, where many NMHSs are in decline because of underfunding.26 The
purpose of these studies was to identify the key economic benefits from large-scale
modernization of NMHS services in the region, and to enable national decisionmakers
to understand how to allocate resources to NMHSs to ensure functioning at a level
suited to national needs. The studies were commissioned in close cooperation with the
NMHSs under review, and were developed based primarily on inputs from NMHS and
sectoral experts. This case study summary discusses these European and Central Asian
World Bank studies in aggregate.
Methods
The Roshydromet study used a “sector-specific” approach to evaluate the economic
benefits of modernizing Roshydromet services for weather-dependent sectors of the
economy. This approach relies on in-country data and interviews with sectoral experts
to estimate the current direct weather-related losses (losses caused by direct
destruction, breakdown or damage to any types of property and tangible assets) for
each sector, and the potential reduction in these losses that large-scale modernization
would achieve. In nine of the subsequent Europe and Central Asia country
evaluations, 27 the World Bank applied the sector-specific approach to estimate the
benefits of improved met/hydro services. For these countries, the World Bank also
looked at the reduction in indirect weather-related losses (losses that a business entity
or economic sector suffers because of decreased revenues or additional expenditures
on production cycles) associated with modernization. The incremental reduction in
direct and indirect weather-related losses compared to the costs of modernization
represents the economic efficiency of met/hydro improvements, as defined by the
World Bank.
In all the European and Central Asian countries studied the World Bank also used a
simplified benchmarking approach as an alternative method for evaluating the
economic efficiency of investments in met/hydro services. The benchmarking
approach allows NMHSs to evaluate the economic benefits of their services in
26
Studies took place in Albania, Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Kyrgyzstan,
Serbia, Tajikistan, Turkmenistan and Ukraine.
27
Sufficient information was not available for Kazakhstan and Turkmenistan to use this method.
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Table E.1. Summary of case study examples of economic benefit assessments
Case study
Objectives
Sectors/beneficiaries analysed
1. Economic efficiency of
NMHS modernization in
Europe and Central Asia
(World Bank, 2008)
– Identify economic benefits of largescale NMHS modernization
– Enable national decisionmakers to
understand the necessary level of
funding for NMHS services
– Better understand the role of met/
hydro services in disaster risk reduction
– Demonstrate benefits and costs
of preventive versus reactive
humanitarian assistance
– Inform strategic-level investment
decisionmaking
Weather-dependent sectors
of the economy (not
specified)
2. Benefits of Ethiopia’s
LEAP drought early
warning and response
system (Law, 2012)
National-level assessment
of households affected by
drought
Providers of humanitarian
food assistance
(Government, humanitarian
agencies, donors)
Households/elderly residents
3. Success of the NWS
Heat Watch/Warning
System in Philadelphia
(Ebi et al., 2004)
– Demonstrate effectiveness of heat
warning systems
– Provide data for other locations
considering such systems
4. Benefits and costs
of improving met/
hydro services to
reduce disaster losses
in developing countries
(Hallegatte, 2012)
– Demonstrate the benefits of improving
early warning systems in developing
countries to developed country
standards
National-level benefits and
weather-sensitive sectors
5. Potential value of
general circulation
model (GCM)-based
seasonal rainfall forecasts
for crop management
(Hansen et al., 2009)
– Understand the potential value
of seasonal forecasts in a context
characterized by high-risk smallholder
agriculture and relatively high
predictability
– Understand the potential use and value
of seasonal forecasts downscaled from
a GCM
– Estimate benefits of TAFs for
Switzerland’s domestic airlines
– Evaluate how hydro/met services could
be improved to maximize social and
economic gains
Individual farmers
Determine the value of FMI existing met/
hydro services per euro of investment
Transportation, construction
and facilities management,
logistics, energy and
agriculture sectors
– Estimate costs and benefits of
improving met/hydro services for
households
– Help obtain funding for met/hydro
improvements that would reduce
damages from future extreme weather
event
– Evaluate stakeholder needs for
improved services
– Qualitatively assess benefits of
improved services for different
economic sectors
– Estimate costs and monetary benefits
(where feasible) of future met/hydro
services
Households
6. Value of met/
hydro information in
Switzerland for the
aviation transport sector
(von Grünigen et al.,
2014)
7. Avoided costs of FMI
met/hydro services
across economic sectors
(Leviäkangas and
Hautala, 2009)
8. Household WTP
for improved met/
hydro services (Lazo
and Croneborg,
forthcoming)
9. Socioeconomic
evaluation of improving
met/hydro services for
Bhutan (Pilli-Sihvola et
al., 2014)
a
Swiss domestic airlines
As defined by the World Bank, economic efficiency represents the benefit of improving met/hydro services
(in this case, the additional reduction in weather-related losses that would result from improvements) divided by the
cost of the improvements.
199
Appendix E. Case studies
Geographic
location
11 countries
in Europe and
Central Asia
Methods
Results
Sector-specific and
benchmarking approaches to
estimate avoided weather-related
losses
Economic efficiency of modernization could
range from 199% to 1 440% over 7 years,
a depending on method and country
Ethiopia
BCA to quantify avoided
livelihood losses for households
and decreased assistance costs
associated with LEAP
– Very early LEAP-activated early response:
US$ 2.8 million NPV benefits over 20 years,
compared to conventional humanitarian
emergency drought response
– Delayed LEAP-activated early response:
US$ 2.3 billion NPV benefits over 20 years,
compared to conventional response
Philadelphia,
Pennsylvania
Regression analysis to determine
lives saved by NWS system;
application of the EPA VSL
estimate
All developing
countries
Benefit-transfer approach to
quantify avoided asset losses,
lives saved and total value added
in weather sensitive sectors
Two semi-arid
regions in Kenya
Used crop modelling and
prescriptive decision model to
evaluate how changes in maize
crop management in response to
met/hydro information increase
gross margins
– Heat warning system saved 2.58 lives per
day when the NWS issued a formal heat
warning
– Value of the programme estimated to be
US$ 468 million over three-year period
– US$ 300 million to US$ 2 billion per year in
avoided asset losses
– 20 000 lives saved per year, valued
between US$ 700 million and
US$ 3.5 billion
– US$ 3 billion to US$ 30 billion per year in
additional economic benefits
– Annual BCR between 4 to 1 and 36 to 1
– Value of perfect information represented
24%–69% of gross margin
– Thus, farmers could potentially increase
their average income substantially with the
use of seasonal forecasts
Zurich and
Geneva airports
Applied simple decision model
to analyse how TAFs can reduce
fuel and flight deviation costs for
airlines
– Use of TAFs at Zurich airport generates
about SwF 14 million per year
– When Geneva airport is included, total
economic benefits amount to between
SwF 13 million and SwF 21 million per year
Finland
Applied decision framework
to quantify avoided costs and
productivity gains associated
with use of FMI services; used
impact models and expert
elicitation
Mozambique
CV, benefit transfer, expert
elicitation
– Annual benefits of FMI services for selected
sectors amount to between € 262 million
and € 285 million (2006)
– Annual BCR between 5 to 1 and 10 to 1
– Perfect information could increase benefits
by 65%–100%
– Average estimated WTP for improved
weather information is Mtn 2.9 per year
per individual (about US$ 0.09)
Bhutan
Cardinal rating method, benefit
transfer, expert elicitation
– Qualitative evaluation found significant
benefits for most sectors for services based
on historical climate data
– Forecasting services most significant for
agriculture
– NPV BCR of improved services in Bhutan is
about 3.1
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situations where there is inadequate or insufficient data for conducting sector-specific
assessments. This method relies on readily available data from other countries (in this
case from developed countries, the Russian Federation and China) on the level of
annual direct economic losses caused by unfavourable weather events (expressed as a
share of GDP), as well as the level of annual losses that could be prevented with
modernization. This information is adjusted for the study country using expert opinion
about three basic country characteristics: the weather dependence of the economy,
meteorological vulnerability and the current status of met/hydro service provision. The
simplified benchmarking approach only considers direct damages caused by weather
impacts.
Conclusions
The initial Roshydromet study found that improvements in forecasting and large-scale
modernization of met/hydro services would reduce weather-related economic losses
by 8.5%. In addition, total returns on investment in the modernization project were
estimated to range from 400% to 800% over seven years. As a result of this valuation,
support for the modernization effort reportedly increased from US$ 80 million to
approximately US$ 133 million.
The economic estimates for Europe and Central Asia also found that improvements in
forecasting could result in significant economic benefits. Depending on the method
and country, the World Bank estimated that the economic efficiency of met/hydro
service improvements could range from 199% to 1 440% over seven years.
The World Bank has concluded that both the sector-specific and benchmarking
approaches provide order-of-magnitude valuations of the likely benefits of NMHS
improvements. However, these approaches are both limited in that they rely heavily on
expert opinion. Thus, the results of the analysis are subject to potential biases and
knowledge limitations of the experts involved in the study. In addition, a limited
amount of data are available to support expert findings, and neither approach assesses
the value of met/hydro information for households. Benchmarking is further
constrained by the fact that it does not take into account indirect weather-related
losses, as well as by the limited amount of data used to establish its parameters.
E.1.2
Case study 2: Using benefit–cost analysis to evaluate the
socioeconomic benefits of Ethiopia’s national drought earlywarning and response system
In 2012, the World Food Programme (WFP), with the support of the United Kingdom
Department for International Development and the Netherlands Directorate-General
for International Cooperation, conducted a study to evaluate the benefits and costs of
Ethiopia’s LEAP system. Livelihoods, Early Assessment and Protection is an integrated
drought early warning action system developed in 2008 by the Government of
Ethiopia, with the support of WFP and the World Bank. It was designed to scale up
Ethiopia’s existing national food and cash safety net in case of drought by triggering an
Appendix E. Case studies
201
established contingent fund. This type of integrated system, which combines early
warning with contingent financing and social safety nets, allows the Government of
Ethiopia and its humanitarian partners to respond much faster to a drought. It enables
the provision of food assistance before households have been negatively affected by
drought – which is often not the case with the conventional humanitarian relief system.
Early response has the potential to reduce humanitarian relief costs and prevent
households from engaging in destructive drought risk-coping strategies. The study,
conducted by Anna Law with the support of WFP, was intended to quantify the
economic benefits of early drought response in Ethiopia, and specifically evaluate the
cost-effectiveness of the LEAP system.
Methods
Law used a forward-looking BCA to evaluate costs and benefits of the LEAP system
over the next 20-years. Law compared three scenarios to draw her conclusions about
the costs and benefits associated with the LEAP system: a conventional emergency
response (that is, a baseline scenario without LEAP, in which response is triggered eight
months after the first early warning of an impending drought), an ideal LEAP-activated
early response (two months after the early warning), and a delayed LEAP-activated
response (five months after the early warning). The benefits of a LEAP-triggered early
response were calculated in terms of avoided livelihood losses for households,
including losses related to stunting, reduced adult food and non-food consumption,
and the “distress sale” of productive assets. Law also examined benefits in terms of
decreased assistance costs for those who provide food aid: the Government,
humanitarian agencies, and donors. For the two LEAP scenarios, Law included the cost
of setting up and maintaining the LEAP system.
In the absence of quantitative data on how beneficiary numbers increase over time
from early to late response, Law assumed that beneficiary numbers would remain
constant in all three scenarios. In reality, it is likely that the number of people in need of
assistance increases with time as a crisis escalates – probably in a non-linear fashion.
However, Law assumed that the benefits of acting early do not result from lower
beneficiary numbers, but rather from (a) lower cost of assistance per beneficiary, and
(b) lower livelihood losses per beneficiary. Several additional assumptions are
described in the complete case study. The study did not quantify and monetize certain
benefits, such as number of lives saved, avoided livestock losses and other indirect
benefits.
Conclusions
This study concluded that both LEAP scenarios provided economic benefits that greatly
outweighed the costs. Law estimated that the ideal LEAP-activated response and the
delayed LEAP-activated response would generate US$ 2.8 billion and US$ 2.3 billion,
respectively, in NPV benefits (compared to the conventional response scenario), over a
20-year period. Most of these benefits are because of avoided livelihood losses,
although there were also benefits associated with lower assistance costs. Benefits
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could be higher if the number of people requiring assistance is reduced by early
response, and if drought frequency and/or magnitude increase under climate change.
E.1.3
Case study 3: Quantifying the success of the United States
National Weather Service’s heat watch/warning system in
Philadelphia in terms of lives saved
This study, conducted by Ebi et al. (2004), quantified the potential benefits of NWS
extreme heat warning notices for the Philadelphia, Pennsylvania area in terms of the
number of lives saved. The research reflects both a desire to demonstrate the
usefulness of such systems, and to provide specific evidence concerning Philadelphia’s
approach as a potential benchmark for other locations considering such systems. The
Electric Power Research Institute and NOAA funded the study.
Methods
The authors used regression analysis to evaluate the relationship between weather
conditions, heatwave warning announcements and daily summertime mortalities for
people aged 65 and older, who are particularly vulnerable to heat mortality, for the
years 1995 to 1998. The study looked at two types of “heatwave days”: (a) days when
NWS issued a formal heat warning, and (b) days when NWS did not issue a heat
warning but Philadelphia’s Hot Weather-Health Watch/Warning System (PWWS)
indicated that weather conditions posed a risk to human health. For each of these
heatwave days, the authors compared daily mortality data for the warning day and the
following three days. Including these subsequent days, the total number of days
evaluated was 45 with NWS formal heat warnings and 210 with PWWS-indicated risks.
The authors used the regression analysis to determine the number of additional deaths
that would have occurred on the 45 days that NWS issued a warning if the warning
had not been called, such as on the 210 days with PWWS-indicated risks.
To monetize the estimated number of lives saved by the NWS-issued warning, as
determined by the regression analysis, the authors used the EPA VSL estimate,
approximately US$ 6 million at that time, as a starting point. Based on a limited review
of studies of the sensitivity of the VSL to age, the authors concluded that a value of
US$ 4 million was appropriate because of the study population’s tendency to be elderly.
However, making “age-based adjustments” to the VSL is not generally appropriate.
Attempts to monetize potential future or observed changes in mortality risk or outcomes
need to be carefully considered and guided by local conditions and available data.
Conclusions
Ebi et al. concluded that there were approximately 2.58 fewer excess deaths per day
on each of the 45 days when the NWS issued a formal heat warning. 28 Multiplying
28
However, the regression analysis was not statistically significant at the commonly used 5% level,
and therefore the authors could not rule out the possibility that the warnings do not save lives.
Appendix E. Case studies
203
the extrapolated number of lives saved by the author’s adjusted VSL of US$ 4 million
provided an estimate of the programme’s value as US$ 468 million over the threeyear study period.
The study drew notable attention because of the magnitude of the estimated benefits.
However, the study evaluated a period when the city and its residents may have been
especially responsive to heat warnings. Specifically, the 1995 to 1998 study period
evaluated actions following the 1991 and 1993 heatwaves in Philadelphia, as well as
the extreme heat mortality and nationwide coverage of the 1995 heatwaves in
Chicago. However, some researchers, for example Sheridan (2007), have found that
heat warnings do not cause at-risk individuals to modify their behaviour and more
frequent warnings might desensitize the public to risks.
E.1.4
Case study 4: Applying benefit transfer to evaluate the benefits
and costs of improving met/hydro services to reduce disaster
losses in developing countries
World Bank economist Stephane Hallegatte conducted this study in 2012 as part of a
larger effort to demonstrate the national-level benefits of improving met/hydro
information and early warning systems in developing countries. This research serves as
an example of how existing data, estimates from the literature and expert knowledge
can be applied to estimate the value of met/hydro services in other contexts.
Methods
Hallegatte (2012) employed a benefit-transfer approach to develop estimates of the
benefits and costs of improving met/hydro information and early warning systems in
developing countries to meet developed-country standards. Benefit-transfer
approaches use existing data from other studies and attempt to apply their findings to
a study case with limited or no available data. For this study, the author used readily
available data and existing studies to first estimate the benefits from early warning
systems in Europe in terms of avoided asset losses, number of lives saved and economic
gains for weather-sensitive sectors of the economy. Hallegatte applied the findings of
this evaluation to estimate the potential benefits of providing these services in
developing countries.
To transfer avoided asset loss data to the developing world, Hallegatte used existing
data to estimate that early warning systems in developed countries result in avoided
asset losses that amount to between 0.003% and 0.17% of GDP. He applied this
information to developing countries by grouping them into four categories, ranging
from those with no basic met/hydro services to those with met/hydro services and
early warning systems comparable to those in Europe. The author assumed that
countries with the least amount of services would benefit the most from
improvements, while countries with the greatest amount of services would not require
improvements.
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Hallegatte also made assumptions about the number of people’s lives that improved
early warning systems could save, based on rates of weather-related deaths in Europe,
and reductions in weather-related deaths associated with an early warning system in
Bangladesh. He applied a dollar value to the number of lives saved based on guidelines
from the Copenhagen Consensus.
In addition to the benefits of early warning systems, Hallegatte estimated the
economic benefits that improved met/hydro services could provide to developing
countries in the form of useful services for industries, businesses, households and
individuals when no weather-related emergencies occur. For example, weather
forecasts are used to plan in the agricultural sector, anticipate electricity demand,
optimize air traffic and ship routes, plan road salting and achieve many other purposes
in various sectors. To estimate additional economic gains (that is, value added)
associated with improved met/hydro services, Hallegatte first determined that in
Europe, weather forecasts have led to value-added gains of between 0.1% and 1.0% in
weather-sensitive sectors, amounting to between 0.025% and 0.25% of GDP.
Hallegatte applied these estimates to developing countries, again taking into account
the existing level of met/hydro services based on the four categories of developing
countries described above.
Conclusions
The study estimated that the potential benefits from upgrading the met/hydro
information production and early warning capacity in all developing countries to
developed-country standards would include:
–
US$ 300 million to US$ 2 billion per year of avoided asset losses caused by natural
disasters;
–
An average of 20 000 people’s lives saved per year, valued at between US$ 700 million
and US$ 3.5 billion per year using the Copenhagen Consensus guidelines;
–
US$ 3 billion to US$ 30 billion per year of additional economic benefits.
Based on this analysis, the total benefits to developing countries would be between
US$ 4 billion and US$ 36 billion per year. This can be compared to costs of around
US$ 1 billion per year, for a BCR of between 4 and 36, with the majority of these
benefits attributed to economic gains resulting from the availability and use of
improved met/hydro information.
Hallegatte conducted this analysis at a global scale, using simple assumptions that
provide orders of magnitude rather than project-level estimates. This study also did not
account for the increase in people’s lives saved or the avoided asset losses that would
likely occur with population and economic growth. However, this research provides
rough estimates of the value of met/hydro services – estimates that could be used to
help developing countries make an initial case for increasing investment in early
warning systems and other met/hydro services.
Appendix E. Case studies
E.1.5
205
Case study 5: Using crop models and decision analysis to assess
the potential value of general circulation model-based seasonal
rainfall forecasts for crop management in Kenya
This study used crop growth and decision models to assess the potential value of
seasonal rainfall forecasts, based on downscaled GCM data, for maize farmers located
in two areas of semi-arid Kenya. A team of academic experts led by the International
Research Institute for Climate and Society at Columbia University conducted this
research to gain a better understanding of (a) the potential value of feasible seasonal
forecasts in a context characterized by high-risk smallholder agriculture and relatively
high predictability, and (b) the potential use and value of seasonal forecasts
downscaled from a GCM (Hansen et al, 2009).
Methods
The researchers compared the expected outcome of optimal decisions made in
response to seasonal rainfall forecasts to optimal decisions made based on historical
climate information, which assumes average conditions. They assumed that the value
of the forecast was a function of (a) management variables that maximize expected
gross revenues, (b) the cost of production associated with the management strategies,
and (c) climate and environmental variables.
The authors evaluated two management variables (that is, decisions) that farmers in the
study region could alter to maximize gross margins in response to seasonal forecasts:
stand density and nitrogen fertilizer application rate. First, they used a crop model to
determine the combination of stand density and fertilizer application rate that would
result in the highest average gross margin under different climate conditions. They
determined gross margins using agricultural enterprise budgets, which they developed
based on local cost data for production inputs and market price data for maize.
Next, the authors developed seasonal hindcasts, simulating what the seasonal forecast
would have been in each year of a 34-year simulation period (1968–2002). The authors
developed these hindcasts for two different GCM-based forecast types. To assess the
value of the forecasts, the authors used the crop model to determine the gross margins
realized each year of the simulation period, based on (a) the optimal management
strategies selected for the forecast, and (b) the actual observed weather. The authors
compared the gross margins for the different forecast scenarios to those that would
have been realized using a climatological approach. The authors also estimated gross
margins for a scenario in which the farmer had perfect knowledge of daily weather
conditions. For each scenario, they evaluated optimal management strategies and
gross margins with and without labour costs as a factor of production.
Conclusions
The results indicated that farmers could increase their average income from maize
substantially if they could perfectly anticipate weather for the upcoming growing
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season. The estimated value of perfect information represented 24%–69% of gross
margin, depending on location and whether or not labour costs were considered.
These results suggested that farmers would increase their average income from maize
substantially if they could perfectly anticipate weather for the upcoming growing
season. As expected, the estimated value of seasonal predictions from the observed
GCM-based forecasts was lower than the value of perfect information. However, the
results indicated that the more skilful forecast has the potential to increase average
gross margins by 10% to 24% (when labour costs are included), depending on
location.
Although these types of studies can be resource intensive and require outside
expertise, they can serve as important tools in helping NMHSs and in-country partners
(for example, agricultural extension agencies and food security organizations) to
identify management strategies that could result in the greatest benefits for farmers
under different forecast scenarios. The results of the studies could also be used by
NMHSs to encourage farmers to use seasonal forecasts and adopt alternative strategies
when warranted.
This study is limited in that it focuses on the effect of only two management strategies,
thereby ignoring many other determinants of forecast value. A more realistic and
robust picture of the potential value of seasonal forecasts to farmers could be obtained
from a farm-level analysis that includes additional management options, and
represents the difference in farm types in the study region.
E.1.6
Case study 6: Using decision models to assess the value
of met/hydro information in Switzerland for the aviation
transport sector
In 2009, MeteoSwiss commissioned a pilot study to develop rough valuations of the
economic benefits of met/hydro services for Swiss households and the agriculture and
energy sectors. The pilot study found that benefits from met/hydro services were in the
order of hundreds of millions of Swiss francs, with a probable BCR of 5 to 1. Based on
the findings of this analysis, MeteoSwiss agreed that more detailed, sector-level
analyses would be necessary to gain a better understanding of the value of met/hydro
services within the Swiss context and to evaluate how met/hydro services could be
improved to maximize social and economic gains. Towards that end, MeteoSwiss
commissioned two additional studies, focusing on the economic value of met/hydro
services for the road and aviation transport sectors. The present case study focuses on
the aviation study, which looked at the benefits to domestic airlines of using TAFs to
determine weather conditions at their destination airport.
Methods
The authors of this study developed a decision model to analyse how the use of TAFs
can reduce fuel and flight deviation costs for airlines. If adverse weather conditions are
expected at the destination airport, the airlines can carry additional fuel reserve to be
Appendix E. Case studies
207
able to extend the flight time. If an airline decides to carry extra fuel and the actual
conditions at the destination are not adverse for landing, the airline will have incurred
unnecessary additional costs. However, if aeroplanes do not have enough fuel to
extend a flight until it is safe to land, the flight crew must land at a different airport and
face additional costs such as passenger compensation, transfer costs, landing fees, fuel
and reputation costs, among others. The authors compared the costs that airlines incur
with and without the use of TAFs by determining the frequency with which forecast
conditions accurately predicted the actual weather conditions, and the frequency with
which the airlines decide to correctly or unnecessarily carry extra fuel. The analysis
relied on TAF verification data from April 2008 through March 2010.
Conclusions
The study found that the use of TAFs at Zurich Airport generates significant economic
benefits for domestic airlines, amounting to between SwF 11 million and SwF 17 million
per year. When extrapolated to Geneva Airport, the study suggests that the total
economic benefits for Switzerland’s domestic airlines amount to between SwF 13 million
and SwF 21 million (US$ 14 million–US$ 22 million) per year. However, this estimate
does not account for the different economic and aeronautical conditions at Geneva
Airport, and the estimates depend greatly on the price of fuel. Additionally, the authors
did not report the costs associated with installing and using the TAFs. However, the
costs of TAFs are expected to be relatively minimal.
The decision model employed for this study is relatively simple, and could potentially
be completed in-house with the adequate expertise and resources. In the authors’
view, one main lesson from their work can be useful for similar studies: companies
know quite well where and why they use meteorological information; however, they
often cannot easily quantify the benefits related to that use. Thus, NMHSs should not
rely on surveys or interviews to learn about the monetary benefits of meteorological
information. Instead, they should conduct explorative interviews to understand the
decisionmaking process within the companies. Then, based on that knowledge, the
agencies should build, validate and use a decisionmaking model to evaluate the
monetary benefits.
E.1.7
Case study 7: Evaluating the avoided costs of the Finnish
Meteorological Institute’s met/hydro services across
economic sectors
In 2007, the Technical Research Centre of Finland (VTT) conducted a valuation of the
benefits of FMI met/hydro services. This study focused on the benefits of met/hydro
services for various sectors and user groups to determine the value that FMI met/hydro
services generate per euro of investment. Specifically, the study developed initial,
order-of-magnitude estimates of the benefits of FMI met/hydro services for
transportation, construction and facilities management, logistics, energy and
agricultural sectors. Although many other sectors are also likely to benefit from the use
of met/hydro services, the authors excluded them from their analysis because of
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limitations of available data or difficulties in expressing benefits in monetary terms. The
Finnish Meteorological Institute has continued to develop more in-depth assessments
since the completion of this initial study.
Methods
For each sector, the authors identified decisions or behaviour that can be altered in
response to met/hydro information. Next, they identified and quantified the effects of
these changes and, where feasible, attached unit prices to estimate economic benefits
in terms of avoided costs and productivity gains. For example, in the transportation
sector, information on adverse weather and poor road conditions might cause drivers
to stay home or avoid affected areas. This would reduce the number and severity of
accidents, and the associated costs of personal injuries and material damages.
Likewise, seasonal forecasts for agriculture can increase value added through increased
crop production.
The authors applied this framework to compare the benefits of the then-current level
of FMI services and services that delivered “perfect information”. The authors
introduced the concept of perfect information so that FMI would have a reference
point for the maximum benefits that could be achieved through the dissemination of
met/hydro information.
The authors used data and interviews to determine the current level of use of met/
hydro services, how individuals and organizations change their decisions in response
to this information, and how this benefits the decisionmaker, or others. When possible,
the authors used available data, statistics and models to quantify the effects associated
with using the met/hydro services in each sector. They relied on literature, interviews,
market price data and other available information to assign monetary values to the
quantified effects.
Conclusions
The study estimated that the annual benefits of FMI services for the selected sectors
amounted to between € 262 million and € 285 million (price level and exchange rate of
2006 euros). Using the annual FMI budget as the “cost” of providing met/hydro
information, the annual BCR for these services is between 5 to 1 and 10 to 1. If FMI
were able to provide perfect information, the benefits could increase by 65% to 100%.
A somewhat surprising result of the study was that warnings about slipperiness for
pedestrians and cyclists appeared to be the single most beneficial service. According
to the VTT study, the reduction in medical costs, lost working hours, avoided lifelong
injuries and even lives saved amounted to an estimated € 113 million per year at the
level of services provided at the time. Even though the warning service is in all
likelihood quite beneficial, the estimate is really uncertain and quite – if not
surprisingly – high.
Appendix E. Case studies
209
The valuation framework that the authors used for this study provides a
straightforward process that NMHSs can use to assess the benefits of met/hydro
services within the context of the met/hydro services value chain. However, to
complete the study, the authors had to make a number of assumptions regarding the
use and effects of met/hydro services across sectors. The reliability of estimates such as
these depends largely on the availability of impact models and relevant data, as well as
the knowledge and understanding of the use and value of met/hydro services by the
experts who contributed to the study.
Despite these limitations, NMHSs can use this type of analysis to justify their budgets
and to explore the value chain for met/hydro services in different sectors. Such an
effort could lead to more detailed valuations of specific services, serving as an
important feedback tool in the development process.
E.1.8
Case study 8: Estimating household willingness to pay for
improved met/hydro services in Mozambique
Mozambique has experienced major flooding in recent years, resulting in numerous
deaths, displacement of populations and destruction of infrastructure. The World Bank
and other organizations are supporting enhancements of the water sector to reduce
damages from future extreme weather events, including improvements to met/hydro
data services.
This project (Lazo and Croneborg, forthcoming) evaluated the costs and benefits of
improving met/hydro services for households in Mozambique. It used a combination
of three approaches: (a) a benefit-transfer approach, (b) an expert elicitation related to
specific economic sectors, and (c) a stated-preference survey of the general public. The
present case study primarily focuses on the stated-preference survey.
Methods
The stated-preference public benefits assessment consisted of a multipart survey using
a CV method (also known as “stated value”). The authors used an in-person survey of
more than 500 individuals to understand how much people in a relevant (that is,
non-random) population would be willing to pay for improved met/hydro services.
The authors used two versions of the CV method survey question; each respondent
was randomly assigned only one version. One version described a programme of
intermediate improvements in services and another described a programme of
maximal improvements. The respondents were asked about the maximum amount
they would be willing to pay for the improved programme, ranging from nothing to
Mtn 9 000. The survey also asked questions about the respondents’ socioeconomic
status, their knowledge about and sources of weather information and their
motivations for their value statement.
A significant concern in undertaking non-market valuation studies in developing
countries is that many individuals have no monetary income and thus asking WTP in
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monetary terms may not yield meaningful results. The authors constrained the results
by asking questions about the incomes of respondents. Respondents may also reject a
scenario if they do not understand or believe some aspect of the scenario. The authors
attempted to address this concern by asking questions about individuals’ motivations
for their value statement.
Conclusions
The CV-method study indicated a mean annual WTP of about US$ 0.09 per individual
for improved weather forecast information. Analysis of responses indicated reasonable
factors influencing WTP. For example, the authors found that urban, more highly
educated and higher income respondents were willing to pay more for improved
forecast information than rural, less educated and lower income respondents. They
also found that individuals revealing some form of scenario rejection stated a lower
WTP that would cause a downward bias in benefit estimates if not accounted for.
Finally, individuals who wanted to make sure future generations had improved
weather information (that is, had a bequest motivation) stated a higher WTP.
Implementation of this study faced many challenges, including difficulty in sampling a
representative cross section of the public, potential language barriers and income
limitations to WTP.
Aggregation of results across the Mozambican population using a 3% rate of discount
over a 50-year benefit lifespan would suggest a total present value of benefits of over
US$ 50 million – significantly more than the project fixed costs of about US$ 21 million.
This indicates that improved met/hydro services in Mozambique could provide
significant societal benefits, dependent in part on ongoing support of operations and
maintenance following any initial largely fixed cost investment.
In addition to the economic information, the survey provided a range of essential
information on respondents’ experience with weather, water and climate, as well as
their sources, uses, preferences and values for met/hydro information. Little or no
information existed on public use of met/hydro products and services prior to this
survey. Results of the study will therefore serve as a baseline for responsible agencies in
assessing the usefulness of and needs for met/hydro information, as they work to
improve their capabilities.
E.1.9
Case study 9: Evaluating the benefits and costs of improved
weather and climate services in Bhutan
Bhutan is subject to significant weather variability and extreme weather and
hydrological events, the frequency and severity of which are expected to increase
under climate change. In light of these factors, the Bhutanese Department of HydroMet Services (DHMS) and FMI initiated a study to investigate how DHMS can
strengthen weather, climate, and hydrological services in Bhutan. As part of this
Appendix E. Case studies
211
investigation, FMI completed an SEB study to (a) evaluate stakeholder needs for
improved met/hydro services, (b) qualitatively assess the potential benefits of improved
services for different economic sectors, and (c) estimate the costs and monetary
benefits (where feasible), of future met/hydro services (Pilli-Sihvola et al, 2014).
Methods
The authors evaluated the benefits and costs of climate services, weather forecast
services, and early warning systems for 15 economic sectors. The scope of the study
was to evaluate the benefits of an overall upgrade of met/hydro services in Bhutan at a
broad level, rather than to assess any particular investment in great detail.
For each sector, the authors evaluated how potential services could affect operations
and investments, avoid or reduce weather- and climate-related damages, and/or be
used to better exploit opportunities (for example, through optimal sizing and location
of hydro, wind and solar power units, or optimized crop choice). Information sources
used included existing climatic and economic data (where available), estimates from
the literature, interviews, and two workshops.
Where feasible, the authors quantified potential benefits by applying changes in
damage probability or estimating increased productivity associated with the use of
met/hydro information and services. The benefit valutations were largely determined
using benefit transfer and information from in-person interviews. For each service and
sector, benefits were also evaluated qualitatively through the filtering steps of the
weather service chain approach (Nurmi et al., 2013).
In addition to benefits, the authors evaluated the costs associated with improving met/
hydro services to the envisaged level. The study assumed a gradual build-up of
services, with space for learning and stepwise upgrading to more sophisticated
systems. Maintenance and staffing requirements were also taken into account.
Conclusions
Given the varied quality of available information, the authors qualitatively assessed
potential benefits based on a cardinal rating method, indicating one to five plus (+)
signs, depending on the estimated significance of the benefit. This assessment shows
significant benefits associated with basic climate services (based on historical climate
data) in most sectors, while forecast services (for example, seasonal forecasts) are the
most significant for agriculture.
The report also presents an overall evaluation of the (quantifiable) benefits and costs
for the period 2015–2030. Overall, the authors estimate that the NPV BCR of providing
improved services in Bhutan is about 3.1. This includes the relatively high capital costs
of DHMS modernization.
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Data and budget limitations consideration
The authors were not able to conduct a full quantitative BCA due to data and budget
limitations for this study. A more in-depth analysis would have required substantial
data from the different economic sectors, as well as sectorial and macroeconomic
modelling capabilities. However, the “quick scan” of costs and benefits of improved
services has provided a good starting point for future service improvements.
Specifically, the authors report that the SEB study effectively demonstrated the need
for service development and related investments in up-to-date observation, dataprocessing and forecasting capacity. It has also helped to set priorities within DHMS
and raise awareness among potential end users.
E.1.10 Summary and conclusions
The case studies highlighted in this publication clearly demonstrate that met/hydro
services can provide significant benefits for individual users, industries and national
and global economies. These studies help to make the case for increased investments
in met/hydro services, including specialized services (for example, TAFs for aviation,
seasonal forecasts for agriculture), large-scale early warning systems, weather forecasts
and entire NMHS information systems. Because the studies were conducted with
different assumptions and evaluated different types of services, it is not possible to
directly compare study results or to draw conclusions regarding a general return on
investment associated with met/hydro services.
Several of the case study examples rely largely on expert opinion and/or existing data
from other countries to assess the benefits of met/hydro services across economic
sectors. Examples include the World Bank’s sector-specific and benchmarking studies,
the VTT study of the benefits of existing FMI services, and Hallegatte’s evaluation of
the benefits of improving early warning systems and met/hydro information in
developing countries to meet developed country standards. The advantage of these
studies is that they do not require a large amount of data or modelling expertise, and
they are relatively inexpensive to conduct. With a basic understanding of the relevant
economic concepts, most NMHS agencies can conduct these types of studies in-house.
However, it is important to recognize that these studies can generally only provide
order-of-magnitude evaluations of the benefits of met/hydro services, which limits
their usefulness for specific applications. For example, these studies should not be used
to assess the trade-offs between different types of met/hydro services for budget
prioritization purposes, or to determine how to improve met/hydro services to
maximize their value. However, they can serve as a useful tool to help NMHS agencies
justify their funding, obtain additional funding or assess which services they may want
to evaluate in greater detail.
In contrast, many of the case study examples employ robust economic methods,
including decision models, CV and regression analysis to evaluate specific services.
Such studies include Law’s analysis of Ethiopia’s LEAP drought response system, the
MeteoSwiss valuation of the benefits of TAFs for Swiss domestic airlines, the Ebi et al.
study of the benefits of the NWS heat watch/warning system for Philadelphia, the use
Appendix E. Case studies
213
by Hansen et al. of crop models to estimate the benefits of GCM-based seasonal rainfall
forecasts for farmers in Kenya, and the study by Lazo and Croneborg of household
WTP for specific met/hydro services in Mozambique. The complexity and data
requirements of these studies vary considerably, and in most cases these types of
analyses will require NMHS agencies to retain an outside expert. However, the
methods can substantially reduce the uncertainty of study estimates, and can be used
to better evaluate the benefits of met/hydro services in relation to the met/hydro
services value chain.
As pointed out by von Grünigen et al. (2014), NMHSs should not rely solely on one
method to evaluate the benefits of meteorological information. Ideally, they should
conduct explorative interviews and review existing data to understand the met/hydro
decisionmaking process. Based on that knowledge, NMHSs can use decisionmaking
models or other methods to evaluate monetary benefits. The level and type of analysis
conducted will ultimately depend on the objectives of the NMHS, as well as the
resources available for the study.
To date, there have not been many studies initiated by NMHSs or similar organizations
to evaluate the benefits of met/hydro services. However, many academic researchers
have addressed this topic, particularly in relation to agriculture. Many of these studies
are referenced throughout the main guidance document. They are also described in
more detail in a literature review completed for USAID in 2012 (http://www.climateservices.org/sites/default/files/CCRD-Climate-Services-Value-Report_FINAL.pdf).
Similar to the case study examples, NMHSs can review these studies to identify options
for conducting their own SEB valuations.
REFERENCES
Ebi, K.L., T.J. Teisberg, L.S. Kalkstein, L. Robinson and R.F. Weiher, 2004: Heat watch/warning
systems save lives: Estimated costs and benefits for Philadelphia 1995–98. Bulletin of the
American Meteorological Society, 85(8):1067–1073.
Hallegatte, S., 2012: A Cost Effective Solution to Reduce Disaster Losses in Developing Countries:
Hydro-Meteorological Services, Early Warning, and Evacuation. Policy research working paper
6058. Washington, D.C., World Bank.
Hansen, J.W., A. Mishra, K.P.C. Rao, M. Indeje and R.K. Ngugi, 2009: Potential value of
GCM-based seasonal rainfall forecasts for maize management in semi-arid Kenya.
Agricultural Systems, 101(1–2):80–90.
Law, A., 2012: Evaluating the cost-effectiveness of drought early warning early response systems
for food security: A cost-benefit analysis of Ethiopia’s Livelihoods, Early Assessment, and
Protection (LEAP) system. Submitted in partial fulfilment of the requirements for the degree
of Master of Science in Environmental Change and Management. Environmental Change
Institute, University of Oxford.
Lazo, J.K. and L. Croneborg, forthcoming: Survey of Mozambique Public on Weather, Water, and
Climate Information. Final report to the World Bank, to be available at https://opensky.library.
ucar.edu/.
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Leviäkangas, P. and R. Hautala, 2009: Benefits and value of meteorological information services
– the case of the Finnish Meteorological Institute. Meteorological Applications, 16:369–379.
Nurmi, P., A. Perrels and V. Nurmi, 2013: Expected impacts and value of improvements in
weather forecasting on the road transport sector. Meteorological Applications, 20:217–223,
DOI: 10.1002/met.1399.
Pilli-Sihvola, K., P. Namgyal and C. Dorji, 2014: Socio-Economic Study on Improved HydroMeteorological Services in the Kingdom of Bhutan. Report prepared for the Strengthening
Hydro-Meteorological Services for Bhutan (SHSB) project. Bhutan, Finnish Meteorological
Institute and Department of Hydro-Met Services.
Sheridan, S., 2007: A survey of public perception and response to heat warnings across four
North American cities: An evaluation of municipal effectiveness. International Journal of
Biometeorology, 52:3–15.
von Grünigen, S., S. Willemse and T. Frei, 2014: Economic value of meteorological services to
Switzerland’s airlines: The case of TAF at Zurich airport. Weather, Climate and Society,
6:264–272.
World Bank, 2008: Weather and Climate Services in Europe and Central Asia: A Regional Review.
World Bank working paper No. 151. Washington, D.C.
APPENDIX E. CASE STUDIES
E.2
CASE STUDY 1: EVALUATING THE ECONOMIC EFFICIENCY OF
NATIONAL METEOROLOGICAL AND HYDROLOGICAL SERVICES
MODERNIZATION IN EUROPE AND CENTRAL ASIA
E.2.1
Background
215
While preparing for the Russian Federation’s National Hydrometeorological
Modernization Project in 2003, the World Bank and Roshydromet recognized the need
to evaluate the economic benefits of improving national met/hydro services to help
make the case for large-scale NMHS modernization. With limited time and resources,
the agencies used a sector-specific approach (described below) to evaluate the
economic efficiency of improving Roshydromet’s services and products. A joint World
Bank–Roshydromet working group developed this approach, in coordination with
NOAA economists and experts from WMO. The study found that improvements in
forecasting would reduce weather-related economic losses by 8.5%. In addition, total
returns on investment in the modernization project were estimated to range from
400% to 800% over seven years. The Russian Government and WMO noted that
support for the project increased from US$ 80 million to approximately US$ 133 million
as a result of the valuation.
The success of this project encouraged the World Bank to launch similar economic
studies in Europe and Central Asia, where many NMHSs are in decline because of
underfunding. Accordingly, the World Bank, jointly with a number of NMHSs in the
Europe and Central Asia region, is developing and piloting methods to evaluate the
benefits associated with existing weather and climate services, as well as the benefits
that modernization might achieve. The purpose of these studies is to identify the key
economic benefits from enhanced services of the NMHSs of Europe and Central Asia
and to enable national decisionmakers to understand how to scale appropriately the
allocation of resources to NMHSs to ensure functioning at a level suited to national
needs. The studies have been commissioned in close cooperation with the NMHSs
under review and developed based primarily on inputs from NMHSs and sectoral
experts (World Bank, 2008).
E.2.2
Methods
To date, the World Bank has conducted economic studies in 11 European and Central
Asian countries (see Table E.2). As described below, these studies applied three
economic methods to evaluate the economic benefits of met/hydro services:
–
Sector-specific assessments, based on the Russian case study, to estimate
weather-related losses for weather-dependent industries and sectors of the
economy, with and without improved met/hydro services. The World Bank
implemented sector-specific assessments in all of the participating countries in
Europe and Central Asia;
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–
Simplified benchmarking approach (described below) where data were
inadequate or insufficient to carry out sector-specific assessments. The World
Bank conducted benchmarking studies in nine of the European and Central Asian
countries;
–
Contingent valuation studies to assess economic benefits for households based
on stated WTP. The World Bank conducted CV valuation studies in two of the
countries.
Case study 1 focuses on the sector-specific and benchmarking approaches because
case study 8 (Mozambique) describes CV in detail. Although there are limitations to
the use of sector-specific and benchmarking methods (for example, the World Bank
has acknowledged deficiencies in the use of benchmarking for detailed assessment,
see Tsirkunov et al., 2007), the World Bank finds this method useful for providing
order-of-magnitude valuations that help NMHSs justify increasing public funds to
support their services.
Sector-specific method
The sector-specific method evaluates the economic benefits that would accrue in
weather-dependent sectors from the modernization of an NMHS. In the European and
Central Asian countries the World Bank used available country data and surveyed
national experts from NMHSs and weather-dependent sectors to evaluate current
sectoral losses from weather events, and determine the potential reduction in losses
that modernization would achieve. The World Bank also used the surveys to determine
the costs associated with actions taken by organizations and entities to prevent
weather-related losses, both with and without modernization. The results of the
studies compare the benefits of modernization, expressed as the additional prevented
losses from hazardous events and unfavourable weather, with the costs associated
with modernizing the NMHS and implementing preventive measures. This comparison
(that is, the incremental reduction in weather-related losses compared to the costs of
modernization) represents the economic efficiency of met/hydro improvements, as
defined by the World Bank.
For the Europe and Central Asia studies, the World Bank expanded upon the
methodology it employed in the Roshydromet study by evaluating both the direct and
indirect economic losses that would occur as a result of unfavourable weather events,
with and without modernization. In the context of this study, the World Bank defined
direct economic losses as those that are caused by direct destruction, breakdown or
damage to any types of property and tangible assets. Indirect economic losses include
those that a business entity or economic sector suffers because of decreased revenues
or additional expenditures on production cycles.
Box E.1 shows the basic steps that the World Bank employed in evaluating the
preventable losses associated with NMHS modernization.
APPENDIX E. CASE STUDIES
217
Box E.1. Evaluating the benefits of NMHS modernization in Europe and Central
Asia using the sector-specific approach (Smetanina et al., 2006a, 2006b)
First, the World Bank used existing data and surveys of NMHSs and sectoral experts to
determine:
(a)
(b)
(c)
(d)
(e)
(f)
Sectors of the economy that suffer significant economic losses from hazardous events
and unfavourable weather (i);
The share of potentially preventable losses at the current quality of met/hydro services
(Ri). Determined using expert assessments for the most weather-dependent sectors of
the economy;
The share of potentially preventable losses that could be avoided with modernization
(Si); estimated for the selected sectors of the economy, and possibly varying from 0%
(that is, the modernization will not reduce potentially preventable losses) to 100%
(the modernization will allow for the avoidance of all potentially preventable losses);
Mean level of losses from hazards and unfavourable weather at the current forecast
quality level (V); evaluated on the basis of official data and independent assessments
of direct losses available at the time of the study and on the basis of expert
assessments of indirect losses;
Mean annual expenditures (C); required to take preventive and protective actions
against met/hydro hazards and unfavourable weather events;
The largest possible changes (relative changes) in the level of expenditures on actions
required to prevent the effect of met/hydro hazards and unfavourable weather events
that would result from the improved accuracy and lead time of met/hydro
information (Δi); determined using expert assessments for the selected sectors of the
economy.
Using the above basic components, the World Bank derived the following formula for
evaluating the economic efficiency (viability) (E) of the expected modernization:
Е = {(V·ΣRiSi – СiΣΣΔ1i)/n}/PC
Where PC equals the estimated costs (expenditures) required for the modernization of an
NMHS; and n represents the number of economic sectors surveyed.
The World Bank noted that special attention should be given to estimating Si because it
relates directly to the expected modernization and the improvement of forecast quality and
lead time. Therefore, the expert survey should contain a clear, quantitative definition of the
improvements expected after the modernization effort.
Benchmarking method
Similar to the sector-specific approach, benchmarking assesses the losses caused by
earlier events and estimates the reduction in losses that could be achieved with
improved services. However, the benchmarking method provides a way to address
limited sector-level data and expertise on weather-related losses in the European
and Central Asian countries. This method relies on expert opinion and readily
available data to assess the vulnerability of the country’s overall economy to
weather-related events and obtain results about direct damages caused by weather
impacts (that is, unlike the sector-specific approach, benchmarking does not take
into account indirect losses).
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Benchmarking is carried out in two stages:
(a) Determining benchmarks – Using data and estimates from other countries and
expert judgment, the authors define and adjust the following two benchmarks
for each country:
(i)
The level of annual direct economic losses caused by met/hydro hazards
and unfavourable weather events, expressed as a share of GDP;
(ii)
The level of annual prevented losses, with and without modernization,
expressed as a percentage of the total level of losses;
(b) Correcting benchmarks – In this stage, data are adjusted to benchmarks
according to country-specific estimates of weather and climate conditions,
structure of the economy and other factors.
For the European and Central Asian countries, the authors determined the level of
annual direct losses and annual prevented losses based on findings from studies
conducted in several countries.29 These studies showed that the mean annual level of
direct losses from met/hydro hazards and unfavourable events varies between 0.1%
and 1.1% of GDP.30 The studies also showed that the share of prevented losses may vary
from 20% to 60% of total weather and climate-related losses.
To evaluate these basic parameters for a specific country, the authors made
adjustments to the average values based on three basic country characteristics: the
weather dependence of the economy, meteorological vulnerability and the current
status of met/hydro service provision. The authors evaluated these factors, and the
extent to which they influence the benchmarks, based on quantitative data and expert
assessments.
In the second stage of the benchmarking process, the authors further adjusted the
benchmarks based on rapid assessments of national climate, agency capacity, national
economic structure and other factors. The adjusted benchmarks are used to assess the
marginal efficiency of met/hydro services, with and without modernization. Results are
reported as the absolute value of the expected reduction in total losses resulting from
modernization divided by the cost of the NMHS modernization improvements.
E.2.3
Results
All assessments indicate that improving met/hydro services and information can result
in significant economic benefits. The World Bank applied the benchmarking method in
all countries. In countries with sufficient information, the Bank also applied the
29
The values used are based on studies that assessed the economic efficiency of met/hydro
information in developed countries and in China and the Russian Federation.
30
These figures represent the mean annual level of losses for a fairly long period of observations.
Losses for some specific year in some specific country may be well beyond the range given.
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APPENDIX E. CASE STUDIES
sector‑specific approach. Table E.2 presents the economic efficiency estimates
determined using the benchmarking and the sector-specific approaches.
Economic efficiency compares the estimates of prevented losses to the NMHS funding
level. For example, economic efficiency in Kyrgyzstan ranges from 244% to 318%,
meaning that every dollar spent on the NMHS could yield US$ 2.4 to US$ 3.2 in
revenues as a result of avoided damages. Information and data were too limited to
apply the sector-specific method in Kazakhstan and Turkmenistan.
E.2.4
Communication of results and outcomes
From these assessments, many further projects and efforts followed, which
attempted to achieve the same benefits that were highlighted in these studies. Some
countries used the results of the studies to independently finance the investment,
instead of using World Bank funding. In addition, the heads of the respective NMHSs
have emphasized the importance of these studies in enhancing dialogue with
national planners.
Table E.2. Comparative results of the Europe and Central Asia economic
assessments, economic efficiency estimates for the benchmarking and sectorspecific approaches (percentage efficiency over seven years)
Economic efficiency
estimate –
benchmarking
Economic efficiency
estimate –
sector-specific assessment
Albania
210
320–680
Armenia
440
1 070
Azerbaijan
430
1 440
Belarus
530
480–550
Georgia
260
1 050
Kazakhstan
540
N/A
Kyrgyzstan
244
318
Serbia
880
690
Tajikistan
199
357
Turkmenistan
413
N/A
Ukraine
310
410–1 080
Country
Note: The World Bank did not conduct sector-specific assessments in Kazakhstan or Turkmenistan because
sufficient data were not available in these countries.
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These studies were also communicated within the sector unit of the World Bank that
has an interest in weather and with the Europe and Central Asia region. World Bank
representatives have presented the results of the studies at a WMO conference on
economic benefits.
E.2.5
Challenges and limitations
Sector-specific assessments
The World Bank developed the sector-specific approach to help NMHSs provide
understandable results to decisionmakers with limited time and resources. Another
stated benefit of this approach is that input from economic experts can contribute to
the design of a modernization project and establish connections between providers
and users of weather information, which can lay the groundwork for private–public
partnerships.
However, the sector-specific method is severely limited in that it relies primarily on
expert opinion to determine the current level of weather-related losses for a given
sector, the additional reduction in weather-related losses that modernization would
achieve and the costs associated with mitigation options. Thus, the results of the
analysis are subject to the potential biases and knowledge limitations of the experts
involved in the study. In addition, there is a limited amount of data available to support
expert findings and the inability of this method to estimate economic benefits to
households.
Another challenge relates to the fact that the agricultural sector is a significant
beneficiary of improved climate services and weather forecasting. However, farmers are
dispersed, which makes it difficult to obtain information about met/hydro services, such
as those services they need, those they already use and the quality of these services.
Benchmarking
Benchmarking is less expensive than most other methods because it does not require
any detailed analytical studies or surveys. However, similar to the sector-specific
method, the accuracy of benchmarking estimates is subject to expert opinions and
potential biases. Additional restrictions result from the fact that this method is
intended to evaluate direct economic losses and does not take into account indirect
losses associated with loss of life and lost profit of economic entities.
Benchmarking is further constrained by the limited amount of data used to establish its
parameters. For example, a single value to characterize the country’s meteorological
vulnerability will not capture all of the complexities of the real situation. Similar to the
sector-specific approach, the benchmarking method does not assess the value of
meteorological information for households.
APPENDIX E. CASE STUDIES
221
Despite these limitations, the World Bank maintains that this approach is useful in
developing order-of-magnitude estimates of the likely benefits of NMHS
improvements, based on global averages.
REFERENCES
Smetanina, M., V. Tsirkunov, S. Ulatov and A. Korshunov, 2006a: Assessment of Economic Benefits
of Hydrometeorological Services in Albania. Moscow, World Bank.
Smetanina, M., A. Korshunov, V. Tsirkunov and S. Ulatov, 2006b: Assessment of Economic Efficiency
of Hydrometeorological Services in the Countries of the Caucasus Region. Moscow, World Bank.
Tsirkunov, V., M. Smetanina, A. Korshunov and S. Ulatov, 2007: Kazakhstan Hydrometeorological
Service Development Program: Economic efficiency assessment. Background paper.
Unpublished.
World Bank, 2008: Weather and Climate Services in Europe and Central Asia: A Regional Review.
World Bank working paper No. 151. Washington, D.C.
FURTHER READING
Korshunov, A., M. Smetanina, V. Tsirkunov and S. Ulatov, 2006: Economic benefits of RHMS of
Serbia. Background paper. Unpublished.
Tsirkunov, V., M. Smetanina, A. Korshunov and S. Ulatov, 2004: The Russian Federation Assessment
of Economic Efficiency of the National Hydrometeorological System Modernization Project.
Moscow, World Bank.
Tsirkunov, V., M. Smetanina, A. Korshunov and S. Ulatov, 2008: Economic assessment of the
benefits of NMHS modernization – Sector specific methodology and benchmarking
methodology. Background paper. Unpublished.
Ulatov, S., A. Korshunov, M. Smetan and V. Tsirkunov, 2007: Belarus Hydrometeorological
Service Development Program: Economic efficiency assessment. Background paper.
Unpublished.
World Bank, 2009: Improving Weather, Climate and Hydrological Services Delivery in Central
Asia (Kyrgyz Republic, Republic of Tajikistan and Turkmenistan). Washington, D.C., Russia
Country Office, World Bank.
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E.3
CASE STUDY 2: USING BENEFIT–COST ANALYSIS TO EVALUATE
THE EFFECTIVENESS OF A DROUGHT EARLY WARNING AND
RESPONSE SYSTEM IN ETHIOPIA
E.3.1
Background/introduction
Ethiopia’s LEAP system is an integrated drought early-warning/early-action system that
predicts crop yield reductions. The LEAP system has three primary components,
including early warning, contingency planning and contingency financing. The World
Bank administers a US$ 160 million relief fund, and the LEAP system’s drought index
triggers the disbursement of these funds once a drought reaches a certain level. This is
opposed to traditional drought relief, which is implemented after drought losses have
occurred. The three components of LEAP support the scale-up of a social safety net,
which LEAP uses to assist people in times of drought.
Evidence suggests that early response leads to lower relief costs for governments and
donor agencies, and can result in avoided livelihood losses for households (Law, 2012).
For governments and donor agencies, the cost of providing early assistance is lower
than during the emergency phase, when expensive food packages and support to
rebuild lost assets are needed. In addition, by the time response arrives under the
traditional drought relief framework, households have usually resorted to destructive
risk-coping strategies that can have significant long-term detrimental health and
economic impacts. Early provision of food or cash can prevent households from having
to engage in such coping strategies, by allowing them to maintain consumption levels
without having to sell productive assets (Law, 2012).
Despite the widely acknowledged benefits of early response, governments and donor
agencies continue to rely on traditional drought relief strategies. One key explanation
for the continued dominance of reactive aid is the lack of quantitative evidence on the
cost-effectiveness of early response (Owens et al, 2003; Choo, 2009; International
Federation of Red Cross and Red Crescent Societies , 2009; and as cited in Law, 2012).
In 2012, the United Kingdom Department for International Development and the
Netherlands Directorate-General for International Cooperation funded a study to
evaluate the benefits and costs of LEAP. The primary motivations for this research
included: (a) to gain a better understanding of the role of climate services in disaster
risk reduction, (b) to “inform strategic-level investment decisionmaking within
governments and donor/humanitarian agencies” (Law, 2012, p. 21), and (c) to
demonstrate whether quantitative evidence on the cost-effectiveness of early response
justifies preventive humanitarian aid rather than reactive humanitarian aid. The specific
objectives were to:
–
Quantify the economic benefits of early drought response to humanitarian
agencies, governments and beneficiaries – the total population in need of
assistance – in Ethiopia;
–
Evaluate the cost-effectiveness of the LEAP integrated early-response model;
APPENDIX E. CASE STUDIES
–
223
Create a model for evaluating the costs and benefits of early-response systems
used for drought-induced food crises.
This study is important because it represents, in part, an attempt to quantify the
downstream effects associated with severe drought, including long-term livelihood
losses. Anna Law, a doctoral candidate from the University of Oxford, conducted this
research.31
E.3.2
Methods used
The author used a BCA approach to provide a more holistic valuation of Ethiopia’s LEAP
system by monetizing its associated costs and benefits at a national scale over a
20-year period.32 It had originally been planned to conduct the BCA at a regional scale,
but Law was unable to do so because of a shortage of regional econometric studies on
livelihood losses associated with drought. Law used Microsoft Excel to conduct all of
the analyses presented in her dissertation.
Law used three scenarios to draw her conclusions about the costs and benefits
associated with the LEAP system: a conventional emergency response (baseline
scenario without LEAP), an ideal LEAP-activated early response, and a delayed LEAPactivated response. The benefits of LEAP were calculated in terms of avoided livelihood
losses for households and decreased assistance costs relative to the baseline scenario.
The two benefit categories were quantified separately because each provided a benefit
to a different group of people: avoided livelihood losses benefits beneficiaries, while
lower assistance costs benefits governments, humanitarian agencies and donors.
To calculate costs for each scenario, Law quantified (a) the average per-capita cost of
emergency assistance, which includes the cost of food and non-food assistance, and
(b) the cost of long-term livelihood losses, which includes losses related to stunting, to
reduced adult food and non-food consumption, and to the “distress sale” of
productive assets. For the two LEAP scenarios, the costs of installing and maintaining
the LEAP system were also included. Table E.3 summarizes the key assumptions and
calculations that were used to calculate the costs of the different scenarios, including
key assumptions.
To calculate the total aid costs and livelihood losses over time, the author conducted
a hazard analysis to determine the frequency of severe droughts and an exposure
analysis to determine the number of beneficiaries affected by a severe drought event.
Defining what constitutes a medium, severe or catastrophic drought is extremely
subjective, and depends in part on whether drought is defined in terms of an
31
Law’s dissertation does not represent the views of the United Nations WFP, the Government of
Ethiopia or any other entity associated with LEAP.
32
Law used the BCA to (a) provide an input to decisionmaking and not as a decision rule, and
(b) place a relative value rather than an absolute one on projects.
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Table E.3. Cost calculations for the conventional and the Livelihoods, Early
Assessment and Protection scenarios (in 2012 US$)
Type of costs
Assumptions
Conventional emergency response
Cost of
Calculated based on the
assistance
average per-capita cost of
emergency assistance in terms
of (a) costs of food assistance;
and (b) non-food assistance,
such as water and sanitation,
agriculture, health and
nutrition
Conducted vulnerability
Cost of
assessment to determine
long-term
(a) lifetime earnings lost by
livelihood
stunted children, and (b)
losses
lower household income
growth in years following a
drought
Calculated for low-income,
agrarian Ethiopian households
Calculation
Cost of food assistance: Used
US$ 77, which is the WFP percapita cost of food aid delivery
in Ethiopia
Limitation: not enough data
on the timing of when people
switch to different droughtcoping strategies
US$ 100 per
beneficiary
Cost of non-food assistance:
Added 30% to the cost of food
assistance
Lifetime earnings lost by
stunted children: Calculated
the expected present value
of lifetime earnings without
a drought and applied a 14%
reduction (based on approach
by Alderman et al. (2006))
to estimate earnings with
drought
Lower household income
growth: Calculated the
expected present value of
household income over
the next 20 years without a
drought and applied a 16%
reduction (based on approach
by Clarke and Vargas Hill
(2012)) to estimate household
income with drought
LEAP early-response and delayed-response scenarios
Calculated based on personal
The cost of installation and
Cost of
communications (A. Kumar,
maintenance over the next
the LEAP
WFP/DRMFSS;a N. Balzer and
20 years
system
R. Choularton, WFP, 2012)
Cost of
Calculated based on the
assistance
average national cost of cash
and food assistance
Calculated relative to the
For lifetime earnings by
Cost of
baseline emergency response
stunted children: the average
long-term
scenario in terms of livelihood
household will start reducing
livelihood
losses avoided under each
consumption three months
losses
early-response scenario
after harvest
For household income growth:
the average household will
reduce consumption of and
sell livestock three months
and five to eight months after
harvest (for ideal and delayed
LEAP scenarios, respectively)
Monetized cost
Adapted estimates from
Clarke and Vargas Hill (2012)
regarding the timing of
drought coping strategies
Lifetime earnings
lost by stunted
children:
US$ 10 per
capita
Lower household
income growth:
US$ 216 per
capita
Total:
US$ 226 per
capita
US$ 567 790
US$ 34 per
beneficiary
Lower lifetime
earnings by
stunted children:
Ideal LEAP –
10%
Delayed LEAP –
30%
Lower household
income growth:
Ideal LEAP –
10%
Delayed LEAP –
30%
Notes:
All United States dollar values reported in 2012 values.
a Disaster Risk Management and Food Security Sector of the Ministry of Agriculture and Rural Development.
APPENDIX E. CASE STUDIES
225
agrometeorological anomaly or in terms of human impact. Because this study focuses
on the effects of drought on people, Law defined a severe drought as one that leads to
important livelihood losses, even if it is not considered very severe or unusual by
agrometeorological standards. Severe drought was defined as a drought on a similar
scale to those that occurred in Ethiopia in 2008, 2009 and 2011; the author assumed
that such a drought occurs every five years, based on estimates from the literature
(Hess et al., 2006; World Bank, 2006; Cabot Venton et al., 2012).
Law calculated the number of beneficiaries for all three scenarios using the
Humanitarian Requirements Documents for the recent severe droughts in Ethiopia,
based on the average number of emergency food beneficiaries identified in the
documents for the three droughts: 4.6 million beneficiaries in 2008, 6.2 million in 2009
and 4.6 million in 2011 (Ethiopia, 2008, 2009, 2011) – an average of 5.1 million
beneficiaries per drought.
In the absence of quantitative data, it was assumed the number of beneficiaries
remained constant in all three scenarios. In reality, the number of people in need of
assistance increases with time as a crisis escalates, and this increase is likely non-linear,
with numbers increasing exponentially once people cross a certain survival threshold.
However, this analysis assumed that the benefits of acting early do not result from
lower beneficiary numbers, but rather from (a) lower cost of assistance per beneficiary,
and (b) lower livelihood losses per beneficiary. When calculating the cost of response
over 20 years, beneficiary numbers were assumed to increase by 1% per year, to
account for population growth and an increase in population vulnerability.
Data requirements/collection efforts
The author conducted three literature reviews to understand (a) the nature of
humanitarian response to drought-induced emergencies; (b) how the LEAP system
works and its associated costs and benefits; (c) the economic impacts of drought on
households. The author used existing data rather than conducting a primary study
because of time and budget constraints.
Uncertainty
Law dealt with uncertainty in the data and her assumptions by conducting sensitivity
analyses on key inputs, including: drought frequency, discount rate, initial number of
beneficiaries, annual changes in population exposure, livelihood losses avoided under
early response, and per-capita cost of assistance under the emergency scenario.
E.3.3
Resources required, including cost and expertise
The entire study – data collection, elaboration of methodology, analysis and write up
– took three months. The author received a grant from the United Kingdom
Department for International Development and the Netherlands Directorate-General
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for International Cooperation, through the Climate and Development Knowledge
Network, as well as an internship stipend from WFP. The grant and internship stipend
covered the author’s living expenses during the period of the study, and in total
amounted to approximately US$ 2 500. The only other cost was a two-day trip for two
people to Ethiopia to present the findings, which cost in the range of US$ 3 000.
The author received help from WFP staff in Rome and Ethiopia to conduct interviews
and discuss the analysis methodology and also received feedback from personnel in
the Ethiopian Government’s Ministry of Agriculture.
E.3.4
Findings/results
Table E.4 provides a summary of the results for the three scenarios included in the study.
The author came to three main conclusions:
–
The economic benefits of early response are high: Even in the delayed LEAPactivated scenario, relative to the conventional emergency response, the benefits
outweigh the costs. This is true even when sensitivity analyses were used to test
different input assumptions that would lead to a more conservative estimate of
benefits. Most of these benefits are due to avoided livelihood losses, although the
benefits of lower assistance costs are also significant;
–
Drought early warning systems are among the most cost-effective disaster risk
reduction investments for food security: The author finds that this is mostly due
to the fact that the benefits come primarily from avoided livelihood losses rather
than avoided crop losses;
Table E.4. Summary of costs and benefits under baseline assumptions,
over 20 years (US$ billions)
Emergency
Ideal LEAP
Delayed LEAP
Assistance costs
1.039
0.353
0.353
Livelihood losses
2.350
0.235
0.705
–
0.001
0.001
3.389
0.589
1.059
Net assistance benefits
(once cost of LEAP is subtracted)
–
0.686
0.686
Net livelihood benefits
–
2.115
1.645
Total net benefits
(NPV)
–
2.800
2.330
Cost of LEAP
Total costs
Note: Totals may not sum due to rounding.
APPENDIX E. CASE STUDIES
–
227
Benefits over time will be larger than portrayed in the study if drought frequency
and/or magnitude increase under climate change. However, there is still great
uncertainty regarding how climate change will affect drought in Ethiopia (World
Bank, 2010, as cited in Law, 2012; IPCC, 2012). According to the sensitivity
analyses, drought frequency has the second largest impact on the results;
discount rate has the largest impact.
E.3.5
Communication of results and outcome of the analysis
The results of the BCA were not published, but the preliminary findings were presented
to the Ethiopian Government in Addis Ababa. The author received a lot of positive
feedback and many questions about what she did not quantify, such as avoided
livestock losses and other indirect benefits. Indirect benefits that were not used in the
analysis due to data limitations include “improved national meteorological
infrastructure, enhanced inter-ministerial collaboration, potential for use of
agrometeorological information and LEAP indices for other services (such as
community or household-level index insurance schemes), and capacity-building
(training of government staff in data analysis and use of the LEAP software)”. These
discussions helped highlight potential improvements for the LEAP system and
commonly overlooked benefits.
E.3.6
Lessons learned/challenges
The key lessons learned and challenges associated with this project are listed below:
–
Evaluating non-monetary benefits for disaster risk reduction: Law did not
quantify and monetize the number of avoided lives lost under each scenario
because of the limited availability of mortality data associated with droughts. In
addition, she stated that monetizing the number of avoided lives lost raised
ethical questions about placing a value on human lives (however, as described in
the main guidance and in other case studies, economists often apply VSL
estimates in BCAs);
–
Selecting an appropriate discount rate: The results of the BCA are highly sensitive
to discount rate. Law used a sensitivity analysis to look at a high (15%), medium
(10%) and low (0%) discount rate, and a 10% discount rate for the main analysis;
–
Predicting future risk patterns with limited meteorological records and
uncertainty about the effects of climate change on drought frequency and
magnitude in Ethiopia: To overcome this inherent uncertainty, the author used a
sensitivity analysis assuming a higher and lower drought frequency. She found
that drought frequency had the second largest impact on study results; the
selected discount rate had the largest impact;
–
Gaining access to and obtaining the right data: In many instances the author was
unable to perform the analysis she wanted to due to lack of available data;
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Predicting changes in population exposure: Law used sensitivity analysis
assuming various increases in population exposure.
Despite these challenges, the author maintains that the BCA framework is a useful
strategic decisionmaking tool that can help governments and donor agencies choose
between alternative investment scenarios for disaster risk reduction. Thus, the analysis
compares differences in the reliability of returns between projects. Sensitivity analysis
was used to highlight investments that consistently generate positive returns, while
flagging those where returns are vulnerable to critical analysis assumptions, such as
the discount rate or drought hazard frequency.
REFERENCES
Alderman, H., J. Hoddinott and B. Kinsey, 2006: Long term consequences of early childhood
malnutrition. Oxford Economic Papers, 58(3):450–474.
Cabot Venton, C., C. Fitzgibbon, T. Shitarek, L. Coulter and O. Dooley, 2012: The Economics of
Resilience: Lessons from Kenya and Ethiopia. London, United Kingdom Department for
International Development.
Choo, C., 2009: Information use and early warning effectiveness: Perspectives and prospects.
Journal of the American Society for Information Science and Technology, 60(5):1071–1082.
Clarke, D. and R. Vargas Hill, 2012: Cost-Benefit Analysis of the African Risk Capacity Facility. Report
for the United Nations World Food Programme and the African Union. Washington, D.C.,
International Food Policy Research Institute.
Ethiopia, Disaster Risk Management and Food Security Sector of the Ministry of Agriculture and
Rural Development, 2008: Humanitarian Requirements Document 2008. Joint Government and
humanitarian partners document. Addis Ababa.
———, 2009: Humanitarian Requirements Document 2009. Joint Government and humanitarian
partners document. Addis Ababa.
———, 2011: Humanitarian Requirements Document 2011. Joint Government and humanitarian
partners document. Addis Ababa.
Hess, U., W. Wiseman and T. Robertson, 2006: Ethiopia: Integrated Risk Financing to Protect
Livelihoods and Foster Development. Discussion paper. Washington, D.C., World Bank.
Intergovernmental Panel on Climate Change, 2012: Managing the Risks of Extreme Events and
Disasters to Advance Climate Change Adaptation. Special Report of the Intergovernmental Panel on
Climate Change. Cambridge, Cambridge University Press.
International Federation of Red Cross and Red Crescent Societies, 2009: World Disasters Report
2009: Focus on Early Warning-Early Action. Geneva.
Law, A., 2012: Evaluating the cost-effectiveness of drought early warning-early response systems
for food security: A cost-benefit analysis of Ethiopia’s Livelihoods, Early Assessment, and
Protection (LEAP) system. Submitted in partial fulfilment of the requirements for the degree
of Master of Science in Environmental Change and Management. Environmental Change
Institute, University of Oxford.
Owens, T., J. Hoddinott and B. Kinsey, 2003: Ex-ante actions and ex-post public responses to
drought shocks: Evidence and simulations from Zimbabwe. World Development,
37(7):1239–1255.
APPENDIX E. CASE STUDIES
229
World Bank, 2006: Ethiopia: Managing water resources to maximize sustainable growth. Washington,
D.C., World Bank.
———, 2010: Economics of Adaptation to Climate Change, Ethiopia Country Case Study. Washington,
D.C., World Bank.
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E.4
CASE STUDY 3: QUANTIFYING THE SUCCESS OF THE NATIONAL
WEATHER SERVICE’S LIFE-SAVING HEAT WATCH/WARNING
SYSTEM IN PHILADELPHIA
E.4.1
Background and introduction
Although cities around the world continue to develop and implement extreme heat
watch/warning systems, only an extremely limited number of peer-reviewed studies
attempt to quantify the effectiveness of these systems. One frequently referenced
example of such a study is the Ebi et al. (2004) review of potential avoided deaths
attributable to the extreme heat warning notices that NWS issues for the Philadelphia,
Pennsylvania, area.
Ebi et al. were motivated to examine whether the benefits of PWWS could be
quantified in terms of the number of lives saved by the system’s warnings and
associated community response actions. The research reflects both a desire to
demonstrate the usefulness of such systems and to provide specific evidence
concerning Philadelphia’s approach as a potential benchmark for other locations
considering such systems. Funding for the authors’ research came from the Electric
Power Research Institute and NOAA.
The following sections outline the methods the authors used for their analysis and its
key findings. Following this, the study results are considered more generally in terms of
their relevance for NMHSs.
E.4.2
Methods used
To determine whether the warnings resulted in fewer mortalities associated with
extreme heat events, Ebi et al. used regression analysis to evaluate the relationship
between daily summertime mortalities for people aged 65 and older, weather
conditions and heatwave warning announcements for Philadelphia for the years 1995
to 1998. A brief summary of the critical study elements and conclusions follows.
Study days
The study design relied on a relatively unique circumstance to define two types of
“heatwave days” that occurred in Philadelphia during the study period: days on which
NWS actually issued a heat warning, and days on which PWWS (see section E.1.3.1)
indicated that weather conditions posed a risk to human health.
Philadelphia developed PWWS following a series of devastating heatwaves in the early
1990s, including one from 6 to 14 July 1993, when the medical examiner’s office
determined that 118 deaths were attributable to heat. At that time, formal findings of
such a large mortality impact attributable to extreme heat were unheard of. In
response, the city funded development of PWWS to identify and provide warning of
APPENDIX E. CASE STUDIES
231
conditions likely to elevate mortality. During the study period, staff in the local NWS
office were responsible for issuing heatwave warnings. To guide their decisions, staff
used NWS forecast information, as well as information that PWWS produced.
Philadelphia’s Hot Weather-Health Watch/Warning System evaluates NWS forecasts to
identify conditions (that is, air masses) that had previously produced elevated daily
mortalities compared to seasonal averages. For the period under study, when
forecasters identified such conditions, PWWS then recommended issuing a heat
warning. However, NWS forecasters did not completely rely on PWWS
recommendations and were often conservative in issuing advisories and warnings.
Thus, the first set of days in the study consisted of those summertime days when
PWWS recommended issuing a warning. This produced a pool of 210 potential
heatwave days, including the recommended warning day and the three days following
the recommended warning day. The authors included the three days following the
recommended warning day because heat-induced health effects can last for several
days, and conditions often remain critical in the days following an extreme heat event,
even if they do not warrant a heat watch/warning.
The second set of study days included days when the NWS staff issued a heatwave
warning based on actual and forecast heat index values, which reflect the combined
effect of heat and humidity. Heat warnings were issued by NWS for 21 days during the
study period. Thus, the second set of heatwave days included 45 total days, when the
three days following the actual warning day were included.
Mortality data
The mortality outcome that the authors considered was the estimate of excess daily
mortality among people aged 65 and older during the summer season. Excess
mortality is the measure of how the reported deaths in a population, here people aged
65 and older, vary from a longer-term average for the time period. Ebi et al. created a
time series database of daily excess mortality among people aged 65 and older in
Philadelphia for both sets of heatwave days.
The authors obtained the daily mortality data for the Philadelphia metropolitan
statistical area from the National Center for Health Statistics. They chose to limit the
analysis to people aged 65 and older because older people are more vulnerable to
excessive heat; therefore, they reasoned that the statistical evidence regarding the
effectiveness of the warning system would be strongest for this age group.
Regression analysis
In their regression analysis, the authors used daily excess mortality values for people
aged 65 and older as the dependent variable, so the coefficients on the explanatory
variables reflect the effects of each variable on this daily mortality measure. After
considering a number of potential explanatory variables, the authors reported values
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for a regression with variables that were significantly associated with excess mortality.
The resulting regression included a constant and the following explanatory variables:
time of season, for which values reflected a sequential count of the days in the
summer season; a warning indicator variable, which reflected whether the data
represented a day (or one of the three days following) on which the NWS warning
was actually issued.
The authors completed their analysis with the multiple linear regression function in
Microsoft Excel.
Value of a statistical life
To monetize the estimated number of lives saved by the NWS-issued warning (as
determined by the regression analysis), the authors used the EPA VSL estimate,
approximately US$ 6 million at that time, as a starting point. Based on a limited review
of studies of the sensitivity of the VSL estimate to age, the authors concluded that a
value of US$ 4 million was appropriate because of the older study population. We
discuss some issues with this approach in greater detail in section E.4.7.
E.4.3
Results
The results of the regression analysis indicated there was a reduction of 2.58 excess
deaths in the 65-and-older population each day that NWS issued a heat warning, or
within the three following days. Extrapolating over the 45 days in the study period
when an NWS-issued warning occurred, the authors suggest the warnings may have
saved a total of 117 people in this age group over the three-year study period (that is,
45 warning days or successive days x 2.58 people saved per day).
However, as the authors noted in their paper, these quantitative results came with a
caveat that the warning coefficient has a t-test statistic value of 1.43 and a p value of
0.08 (significant at the 92% level) and the regression equation explained only 4% of
the observed variation in the data (that is, an R-squared value of 0.04). This result
means that at the commonly used 5% level of statistical significance used to evaluate
the effect of a variable, the authors could not reject the hypothesis that the warnings
do not save lives. The authors considered the low p-value for the warning days
coefficient and discussed a second interpretation – a 92% chance that the system
operation contributed to saving at least one person’s life. This created a frame of
reference for the programme’s benefits, resulting in a large range from one person
saved to 117 people saved.
Multiplication of the extrapolated number of lives saved by the author’s adjusted VSL
of US$ 4 million provided an estimate of the programme’s value over the three-year
study period as US$ 468 million.
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E.4.4
233
Communication of results and outcomes
As mentioned above, reviews of the potential effectiveness of heat health watch/
warning systems in other peer-reviewed articles and agency documents widely cite the
Ebi et al. paper. The authors’ results appear in presentations in a wide range of
professional conferences, such as the annual American Meteorological Society
meetings. However, whether or how the results of the study assisted in adjusting
subsequent heat advisories or components of PWWS is unclear.
E.4.5
Challenges and lessons learned
The Ebi et al. study revealed a subtle challenge with respect to identifying extreme
heat days. Specifically, the difference in the number of days PWWS recommended
issuing heat warnings compared to the number of days where NWS actually issued a
warning reveals how alternative criteria can produce vastly different determinations of
health risk associated with specific meteorological conditions. While this discrepancy
was crucial for producing the data the authors evaluated, it raises additional questions.
For example, would the potential benefits have increased if the public clearly
understood that the recommendations were linked to a past association with elevated
mortality? Or would the potential benefits have diminished if residents began to
interpret more frequent warnings as reflecting “typical,” rather than “extreme”
conditions?
E.4.6
Resources and expertise required
As reported in Lazo et al. (2009), completing the analysis to produce the study took Ebi
et al. approximately 340 hours and approximately US$ 45 000. The analysis also
required the services of, in this case, an economist with the expertise to complete the
regression analysis.
However, the crucial element for this study was having access to the underlying daily
mortality, weather and heat warning data. As Lazo et al. noted in their review, this data
had already been assembled because one of the Ebi et al. co-authors, Kalkstein, was a
principal developer of PWWS. In particular, the effort and resources associated with
categorizing days in terms of their corresponding air mass category for PWWS was not
reflected in the reported financial resources required to generate this research. In sum,
such studies entail a labour-intensive process that requires access to, and the ability to
evaluate, a wide range of meteorological data.
E.4.7
Recommendations for tailoring methods to NMHS circumstances
The Ebi et al. study draws notable attention because of the aforementioned
quantitative results. Considering how others could or should replicate the study is
important, as is whether other conclusions from the study are worth noting. This
section addresses these considerations.
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Replicating the Ebi et al. study
Replicating the Ebi et al. study exactly would be difficult. The main difficulty is that the
study evaluated the relatively unique situation where two different systems were in
place for the issuing of heat warnings. In most cases, an area would develop and
operate a single system.
Determining the resources that others would need to complete a similar study is also
complicated because the authors had obtained a much larger funding commitment to
support the work of developing the excess mortality and air-mass relationships that
underlie PWWS and that presumably informed the NWS criteria.
Looking to NMHSs elsewhere, others could execute the work to develop heat-warning
criteria with varying ranges of complexity and cost. In general, such work would
require participation of health officials with access to daily mortality data for a targeted
area and weather officials with access to historical meteorological data. A less resourceintensive effort could consider evidence that mortality increases when specific
meteorological criteria, consistent with extreme heat, occur. A more resource-intensive
effort would be to conduct a full mapping of historical days into air mass categories
and then evaluate the relationship for elevated mortality based on the air-mass-specific
results mirroring the general process used to develop PWWS.
Considering the Ebi et al. results for NMHSs
One issue of particular note is the authors’ use of the US$ 4 million value per estimated
life saved, which the authors applied to produce a monetized estimate of the benefits
of the programme. They chose the value to reflect the age of the study population and
potential mortality displacement. The article correctly noted that the literature
available at the time reported mixed results with respect to the support for age-based
adjustments to the VSL estimate; however, the selected value of US$ 4 million was
nonetheless a choice the authors made, instead of an empirically supported
adjustment. Finally, we note that attempts to monetize potential future or observed
changes in mortality risk or outcomes need to be carefully considered and guided by
local conditions and available data. In future studies, authors would need to carefully
evaluate using the current VSL estimates available from EPA; using the US$ 4 million
value per estimated life saved that Ebi et al. used would be problematic given the lack
of empirical support for the value.
An interesting consideration for this study is that although it quantifies the effects of
the heat warning announcement, this announcement in turn triggers a series of actions
that the city implements in response to anticipated conditions. In short, attributing the
estimated benefits to the announcement would be short-sighted and we would lose
sight of the city’s efforts to identify and evaluate at-risk individuals and provide
protective services and actions that contribute to saving people’s lives. Other research,
for example that by Sheridan (2007), found that when individuals in an at-risk group
were aware of heat warnings, they did not modify their behaviour to reduce their risks.
APPENDIX E. CASE STUDIES
235
In addition, the Ebi et al. study evaluated a period when the city and its residents may
have been especially responsive to heat warnings. Specifically, the 1995 to 1998 study
period evaluated actions following the 1991 and 1993 heatwaves in Philadelphia, as
well as the extreme heat mortality and nationwide coverage of the 1995 heatwaves in
Chicago. On the other hand, some posit that the public could show a reduced
response to heat warnings, over time, if members of the public begin to lose sensitivity
to the real risk. We have noted the discrepancy reported in the study between the
number of days that PWWS recommended warnings compared with the days where
the NWS actually issued warnings. Had warnings been issued on all of the days that
PWWS recommended, the public might have questioned whether a truly significant
event was occurring; the level of public response may have then trailed off over time.
REFERENCES
Ebi, K.L., T.J. Teisberg, L.S. Kalkstein, L. Robinson and R.F. Weiher, 2004: Heat watch/warning
systems save lives: Estimated costs and benefits for Philadelphia 1995–98. Bulletin of the
American Meteorological Society, 85(8):1067–1073.
Lazo, J.K., R.S. Raucher, T.J. Teisberg, C.J. Wagner and R.F. Weiher, 2009: Primer on Economics for
National Meteorological and Hydrological Services. Boulder, University Corporation for
Atmospheric Research.
Sheridan, S., 2007: A survey of public perception and response to heat warnings across four
North American cities: An evaluation of municipal effectiveness. International Journal of
Biometeorology, 52:3–15.
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E.5
CASE STUDY 4: APPLYING BENEFIT TRANSFER TO EVALUATE THE
BENEFITS AND COSTS OF IMPROVING MET/HYDRO SERVICES TO
REDUCE DISASTER LOSSES IN DEVELOPING COUNTRIES
E.5.1
Introduction and background
Many developing countries lack the resources or relevant expertise to conduct
quantitative assessments of the value of the met/hydro services they provide. The
World Bank’s 2012 study, A Cost Effective Solution to Reduce Disaster Losses in Developing
Countries: Hydro-Meteorological Services, Early Warning, and Evacuation (Hallegatte, 2012)
addresses this issue by applying a low-cost benefit-transfer methodology to estimate
the benefits and costs of improving met/hydro information and early warning systems
in developing countries.
Case study 4 provides an overview of the methods and results of this study, which was
funded by the Office of the Chief Economist at the World Bank. Led by World Bank
economist Stephane Hallegatte, this research is part of a larger effort by the World
Bank to demonstrate the national-level benefits of improved met/hydro services and to
contribute to development policy discussions around the world.
This case study has been included because it serves as an example of how existing
data, estimates from the literature and expert knowledge can be applied to estimate
the value of met/hydro services in other contexts. However, as we discuss below, the
study provides large ranges for the potential benefits of early warning systems and
other met/hydro services. Because the study did not rely on a direct analysis of benefits
in developing countries, these results should be interpreted as initial, order-ofmagnitude estimates that help indicate the potential value of met/hydro service
improvements. Local and context-specific analyses will need to be incorporated by
NMHSs wishing to apply this approach before real investments are made.
E.5.2
Methods used
Hallegatte employed a benefit-transfer approach to develop estimates of the benefits
and costs of improving met/hydro information and early warning systems in
developing countries to meet developed-country standards. Specifically, the author:
–
Estimated the benefits from early warning systems in Europe in terms of avoided
asset losses and people’s lives saved, based on existing literature and data for
Europe;
–
Applied the findings of this valuation to estimate the potential benefits of
providing similar services in developing countries;
–
Estimated other economic benefits that could accrue from using the met/hydro
information required for early warning systems in weather-sensitive sectors,
including agriculture, energy, construction, transportation, health, tourism,
237
APPENDIX E. CASE STUDIES
among others. The author derived these benefits for Europe and applied them to
developing countries;
–
Estimated the costs associated with improving met/hydro information and early
warning capacity in developing countries to developed country standards;
–
Developed a range of BCRs for met/hydro services and early warning systems in
developing countries.
Benefits from early warning and preparation measures in Europe
As a first step to this analysis, Hallegatte relied on existing data to estimate the benefits
of early warning systems in Europe in terms of avoided asset losses and the number of
people’s lives saved.
Avoided asset losses
Hallegatte evaluated avoided asset losses associated with early warnings based on a
review of literature related to emergency preparedness and response to floods and
storms in Europe, as well as his own knowledge and experience. Based on this
approach, Hallegatte estimates that the use of early warning systems in Europe avoids
between € 460 million and € 2.7 billion in lost assets per year. This represents between
0.003% and 0.017% of European GDP. Table E.5 shows the assumptions and sources
that the author used to calculate these estimates.
Table E.5. Calculations and assumptions used to estimate avoided asset losses
provided by early warning systems in Europe
Floods
Storms
Average annual cost to
Europe (€)
€ 4.0 billion
(Barredo, 2009)
€ 2.6 billion per year
(Swiss Re, 2006)
% of events forecasted
50% to 75%
(author’s estimate)
100% (author’s
estimate)
% reduction in losses
because of early
warnings
10% (author’s estimate) to
50% (Carsell et al., 2004)
10% to 50% per year
(assumed to be the
same as floods)
Total annual loss
reduction
€ 200 million to
€ 1.5 billion
€ 260 million to
€ 1.2 billion
Total benefit
€ 460 million to € 2.7 billion per year
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Lives saved
Weather-related threats to human safety in Europe include floods, heatwaves, winter
storms, cold spells and avalanches. Hallegatte reviewed existing data and literature
to determine the average number of people who have died in Europe as a result of
each of these events and the frequency with which these events occur. He then made
an assumption about the number of people who would have died if no early
warnings had been in place. The author does not report the exact method used to
determine this estimate, but notes that he took into account the effectiveness, use
and response to early warnings for different sectors of the economy (for example,
maritime and air transport, outdoor activities, and government emergency
preparations).
Based on this assessment, Hallegatte estimates that early warning systems in Europe
save at least 200 people’s lives per year. The author maintains that this is an extremely
conservative estimate, based on lower-bound estimates from the literature, and that
met/hydro services more likely save upwards of 800 lives per year.
Application of benefit estimates for Europe to the potential benefits of providing
similar services in developing countries
Some of the potential benefits from early warning systems already occur in the
developing world. Thus, to transfer findings on the benefits for Europe to developing
countries, the author determined (a) how much of these benefits are already captured,
and (b) how much it would cost to capture the full benefit potential. To answer these
questions, Hallegatte identified four groups of developing countries based on the
following assumptions:
–
Group 1 (low-income countries) includes countries with no basic met/hydro
services, where benefits are likely to be close to zero. Hallegatte assumed that
10% of the benefits achieved in Europe are already realized in these countries
because of existing regional or global services;
–
Group 2 (lower middle-income countries) includes countries where basic met/
hydro services exist but are not fully operational. Hallegatte assumed these
countries realize 20% of the benefits achieved in Europe;
–
Group 3 (upper middle-income countries) includes countries with wellfunctioning met/hydro services but with gaps in the chain from data production
to early warning systems. Hallegatte assumed that 50% of the European benefits
are achieved in these countries;
–
Group 4 (high-income countries) includes countries where met/hydro services
and early warning systems are comparable to European ones. Hallegatte assumed
100% of the European benefits are achieved in these countries.
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APPENDIX E. CASE STUDIES
Avoided asset losses
To estimate asset losses avoided as a result of improved early warning systems in
developing countries, Hallegatte assumed that the magnitude of potential avoided
losses depends on the level of existing services for each country group, as defined
above. For example, for developing countries in group 1 (low income), where
Hallegatte assumed that the countries currently achieve only 10% of the benefits
achieved in Europe, he calculated the lower-bound estimates for avoided asset losses
from improved services as follows:
–
Potential total benefits of the European level of services = GDP (US$ 413 000
million) x 0.003% (lower-bound estimate for avoided asset losses as a percentage
of GDP) = US$ 12 million;
–
Estimated benefits from existing level of services = US$ 12 million x 10% =
US$ 1 million;
–
Additional potential benefits from improved services = low estimate of potential
benefits (US$ 12 million) – low estimate of benefits provide by current services
(US$ 1 million) = US$ 11 million.
Table E.6 summarizes this analysis by country group. Hallegatte’s results show that
developed countries could avoid losses of about US$ 300 million to US$ 2 billion per
year as a result of implementing early warning systems.
Table E.6. Estimated benefits from avoided asset losses
because of implementation of early warning systems (US$ millions)
Developing country
income group
Potential benefits
from improved
Assumed Existing benefits
services
ratio of
Upper
Lower
current
bound
bound
vs.
(0.003% (0.017% potential Lower Upper Lower
Upper
of GDP) of GDP benefits bound bound bound bound
Potential total
(European-like)
benefits
GDP
Group 1:
Low income
413 000
12
69
10%
1
7
11
62
Group 2:
Lower-middle income
4 300 000
122
714
20%
24
143
97
572
Group 3:
Upper-middle income
15 300 000
433
2 542
50%
217
1 271
217
1 271
Group 4:
High income
43 000 000
1 217
7 145
100%
1 217
7 145
–
–
Total
63 013 000
1 748
10 470
1 459
8 565
324
1 904
Note: Totals may not sum because of rounding.
Source: Hallegatte (2012)
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Lives saved
To estimate the number of lives that would be saved with improved early warning
systems, Hallegatte first investigated the number of weather-related deaths that occur
annually in Europe and developing countries. Based on data from the International
Disaster Database developed by the Centre for Research on the Epidemiology of
Disasters, weather-related extreme events killed an average of 43 000 people per year
in developing countries between 1970 and 2011. The total population in developing
countries in 2011 was approximately 5.7 billion; thus, the annual death probability
associated with weather-related events was approximately 7.5 per million inhabitants.
In developed countries, the death toll was 2 500 persons per year. With a total
population in developed countries of approximately 1.1 billion, the annual death
probability was approximately 2.2 per million inhabitants.
Hallegatte acknowledges that differences in housing and infrastructure quality,
disaster protection and climate contribute to the much higher death probability rate in
developing countries. However, he attributes much of the difference in death
probability rates to the availability and effective use of early warning systems in
Europe. We are unable to independently confirm whether access to early warning
information explains the difference in risk or whether other factors also contribute.
Citing the reduction in deaths resulting from the use of an early warning system in
Bangladesh during Hurricane Sidr (as compared to previous hurricanes in the region,
when no such system was in place), Hallegatte assumed that improving early warning
and evacuation systems in developing countries to a level available in Europe would
make the death probability decrease from 7.5 per million to 4 per million – a 46%
reduction. This means that early warning systems would reduce human deaths
associated with extreme events from 43 000 to 23 000 per year – saving 20 000 lives
per year.
To assign a value to these estimates, Hallegatte applied the Copenhagen Consensus
guidelines on the value of a human life (ranging from US$ 1 000 to US$ 5 000 per
“disability-adjusted life year”).33 He assumed that each death from weather-related
events was equivalent to 30 lost years to estimate that the annual value of avoided
deaths would be US$ 600 million (assuming US$ 1 000 per life) to US$ 3 billion
(assuming US$ 5 000 per life).
Note that this represents a lower-bound estimate, as most researchers have applied
much higher estimates for the value of human life. For example, a report on the
transportation sector in France estimated € 1 million per life (République Francaise,
2005). Viscusi and Aldy conducted a comprehensive review and evaluation of studies
conducted throughout the world on the estimated VSL. They found VSL estimates for
United States labour market studies to be in the range US$ 4 million to US$ 9 million. In
developing countries, VSL estimates ranged from US$ 750 000 in the Republic of Korea
to US$ 4.1 million in India (Viscusi and Aldy, 2003). For more information on VSL
estimates, see Chapter 7 (benefits).
33
The disability-adjusted life year measures one lost year of a “healthy” life.
241
APPENDIX E. CASE STUDIES
Economic benefits from met/hydro information (excluding benefits from early
warning systems)
Improving met/hydro services will not only allow for better early warning systems;
these services can also produce economic benefits in the form of useful services for
industries, businesses, households and individuals when no weather-related
emergencies occur. For example, weather forecasts are used to plan in the agricultural
sector (for example, to decide when to plant or apply fertilizer), anticipate electricity
demand, optimize air traffic and ship routes, plan road salting and achieve many other
purposes in various sectors.
Based on existing literature, Hallegatte estimated that weather forecasts led to valueadded gains of between 0.1% and 1.0% in weather-sensitive sectors, amounting to
between 0.025% and 0.25% of GDP. Hallegatte considered this to be a lower-bound
estimate because evidence from the literature suggests much higher values are
possible. For example, a World Bank study of met/hydro services in south-eastern
Europe found the economic benefits from met/hydro services ranged from 0.09% in
Croatia to 0.35% in the Republic of Moldova. In addition, Hallegatte’s estimate did not
include values for households.
Based on the 0.025%–0.25% estimate, the value of weather forecast information in
Europe was between € 3.4 billion and € 34 billion per year. Table E.7 shows how
Hallegatte generalized these estimates to developing countries. As shown in the table,
he estimated that the economic benefits associated with met/hydro information used
during normal conditions could vary from US$ 3 billion to US$ 30 billion per year.
Table E.7. Potential economic benefits from improved met/hydro services,
excluding benefits from early warning systems (US$ millions)
Developing country
income group
Potential benefits
(European-like)
GDP
Lower
Upper
bound
bound
(0.025% (0.25%
of GDP) of GDP)
Estimate of
benefits from
Estimate of existing
Assumed
improved services
benefits
ratio of
current
vs.
potential Lower
Upper
Lower Upper
benefits bound
bound bound bound
Group 1:
Low income
413 000
103
1 033
10%
10
103
93
929
Group 2:
Lower-middle income
4 300 000
1 075
10 750
20%
215
2 150
860
8 600
Group 3:
Upper-middle income
15 300 000
3 825
38 250
50%
1 913
19 125
1 913
19 125
Group 4:
High income
43 000 000
10 750
107 500
100%
10 750
107 500
–
–
Total
63 013 000
15 753
157 533
12 888
128 878
2 865
28 654
Note: Totals may not sum because of rounding.
Source: Hallegatte (2012)
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Estimated costs of upgrading met/hydro information production and
early warning capacity
Improving met/hydro services and early warning systems in developing countries
would entail costs associated with developing local observation systems; increasing
local forecast capacity, capacity to interpret forecasts and capacity to translate them
into warnings; developing communication tools to distribute and disseminate
information, data and warnings; increasing institutional capacity; and ensuring that
users make decisions based on the information available.
Hallegatte points out that it will not be necessary for developing countries to develop
the most expensive components of early warning systems and met/hydro information
(for example, Earth observation satellites and global weather forecasts) because the
international met/hydro community has already built these systems.
Based on information available for several developed countries, Hallegatte estimated
the cost, including maintenance and operational costs, of providing appropriate early
warning systems in developing countries to be approximately US$ 50 million per
country over a five-year period.34 This would be equal to about US$ 2 billion over five
years for all developing countries, for an annual cost of US$ 800 million per year for all
developing countries. He further estimated that the cost to invest in NMHS capacitybuilding and development of skills would be about US$ 200 million per year. Thus, the
total cost of providing services across all developing countries would be approximately
US$ 1 billion per year.
E.5.3
Findings/results
The study estimated that in Europe met/hydro information and early warning systems
save several hundred people’s lives per year, avoid between € 460 million and
€ 2.7 billion of disaster asset losses per year and produce between € 3.4 billion and
€ 34 billion in additional benefits per year through the optimization of economic
production in weather-sensitive sectors. The potential benefits from upgrading the
met/hydro information production and early warning capacity in all developing
countries to developed-country standards would include:
–
US$ 300 million to US$ 2 billion per year of avoided asset losses caused by natural
disasters;
–
An average of 20 000 people’s lives saved per year, valued at between
US$ 700 million and US$ 3.5 billion per year using the Copenhagen Consensus
guidelines;
–
US$ 3 billion to US$ 30 billion per year of additional economic benefits.
34 The
author acknowledges that costs will vary considerably by country depending on local
scientific capacity, including the existence of university and research programmes, local
infrastructure and transportation capacity, the size of the country, how information is
communicated, people’s level of trust in the local forecast producers, and other factors.
APPENDIX E. CASE STUDIES
243
Based on this analysis, the total benefits to developing countries would be between
US$ 4 billion and US$ 36 billion per year. This can be compared to costs of around
US$ 1 billion per year, giving a BCR of between 4 and 36.
E.5.4
Outcomes and recommendations for tailoring methods to NMHS
circumstances
Hallegatte’s analysis identified a large potential for investments by developing
countries in met/hydro services and early warning and evacuation systems to reduce
human and economic losses from natural disasters. The research also estimated the
value of other SEBs that could accrue from met/hydro services during times when the
weather is not severe.
When reviewing this study, we noted some considerations for reflection:
–
The author’s assumptions were not always based on existing data or analyses. For
example, the author applied a 46% reduction in lives lost during weather-related
events to estimate the number of lives that would be saved by improving early
warning systems in developing countries. This number seems arbitrary, but does
provide a benchmark with which to evaluate potential benefits. This number
could be higher or lower, depending on the frequency and type of events that
developing countries experience;
–
Some of the methods the author employed were inconsistent. For example, the
author used country groups to assess avoided asset losses; however, he does not
apply this approach to estimate the costs associated with met/hydro
improvements;
–
The study methodology did not seem to consider the difference between the
type, frequency and severity of extreme events in Europe and developing
countries. However, the author did acknowledge the importance of these factors;
–
As the author noted, this study did not account for the increase in people’s lives
saved or the avoided asset losses that would likely occur with population and
economic growth.
Despite these concerns, this research provides rough valuations of met/hydro
services – valuations that could be used to help developing countries make an initial
case for increasing investment in early warning systems and other met/hydro services.
Hallegatte conducted this analysis at a global scale, using simple assumptions that
provide orders of magnitude rather than project-scale valuations. Because of these
simplified assumptions, we would suggest that NMHSs interested in applying this
approach first incorporate local and context-specific analyses before making real
investments. For example, the World Bank used Hallegatte’s findings in a loan
appraisal for a met/hydro project in Nepal. World Bank personnel employed a benefittransfer approach to evaluate the benefits of avoided asset losses plus economic
benefits by applying Hallegatte’s methodology, making adjustments for observed
244
VALUING WEATHER AND CLIMATE:
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weather-related mortality and sector sizes in the country. They then compared these
benefits to project costs. The World Bank’s analysis required approximately two days to
complete. The World Bank has also applied Hallegatte’s methodology in BCA studies in
Ethiopia, Nigeria and Yemen.
REFERENCES
Barredo, J.I., 2009: Normalised flood losses in Europe: 1970–2006. Natural Hazards and Earth
System Science, 9(1):97–104.
Carsell, K.M., N.D. Pingel and D.T. Ford, 2004: Quantifying the benefit of a flood warning
system. Natural Hazards Review, 5(3):131–140.
Hallegatte, S., 2012: A Cost Effective Solution to Reduce Disaster Losses in Developing Countries:
Hydro-Meteorological Services, Early Warning, and Evacuation. Policy research working paper
6058. Washington, D.C., World Bank.
République Francaise, 2005: Instruction-cadre relative aux méthods d’évaluation économique des
grands projets d’infrastructures de transport. May 27.
Swiss Re, 2006: The effect of climate change: Storm damage in Europe on the rise. Zurich, Swiss
Reinsurance Company, http://www.preventionweb.net/files/20629_
publ06klimaveraenderungen1.pdf.
Viscusi, W.K. and J. Aldy, 2003: The value of a statistical life: A critical review of market estimates
throughout the world. The Journal of Risk and Uncertainty, 27(1):5–76.
APPENDIX E. CASE STUDIES
245
E.6
CASE STUDY 5: USING CROP MODELS AND DECISION ANALYSIS
TO ASSESS THE POTENTIAL VALUE OF GLOBAL CIRCULATION
MODEL-BASED SEASONAL RAINFALL FORECASTS FOR CROP
MANAGEMENT IN KENYA
E.6.1
Introduction and background
Many studies have paired crop growth models with economic decision models to
assess the value of forecast information at the farm level. These studies have generally
shown that advance information in the form of seasonal climate forecasts has the
potential to improve on-farm management, leading to at least modest and sometimes
substantial increases in expected farm profits.
This case study describes academic research that used crop growth and decision
models to assess the potential value of downscaled GCM-based seasonal rainfall
forecasts for farmers located in two areas of semi-arid Kenya. Specifically, the authors
evaluated how maize planting and fertilizer management decisions made in response
to seasonal forecasts can result in increased farm revenues compared to a no-forecast
scenario in which farmers rely on historical climate information.
The study considered two locations in Kenya’s semi-arid Eastern Province: the National
Dryland Farming Research Centre at Katumani, in the Machakos District; and Makindu,
in the Makuene District. Maize production in this region strongly depends on rainfall
that occurs during the October through December “short rains” season. Maize
production is risky in this semi-arid environment partly because of its sensitivity to
year-to-year variability in the amount and timing of rainfall (Hansen et al., 2009). Thus,
farmers could potentially realize substantial gains with the use of improved forecast
information.
A team led by the International Research Institute for Climate and Society at Columbia
University conducted this research to gain a better understanding of (a) the potential
value of feasible seasonal forecasts in a context characterized by high-risk smallholder
agriculture and relatively high predictability, and (b) the potential use and value of
seasonal forecasts downscaled from a GCM.35
E.6.2
Methods used
This section provides an overview of the basic methodology the authors used. The
study itself contains a much more comprehensive description of these different
methodology components, as well as the methods used to develop the GCM forecast
scenarios.
35
Hansen et al. (2009) includes detailed information on the downscaled GCM data.
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VALUING WEATHER AND CLIMATE:
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Decision framework
To derive benefit estimates, the authors compared the expected outcome of optimal
decisions made in response to seasonal rainfall forecasts to the expected outcome of
optimal decisions made based on previous climate information (the climatological
distribution, in this case), such that the value of the rainfall forecast system, Vf, is
equal to:
n
n
n-1 ∑ ( PT y ( x*| Fi ; θi , eT ) − Cx*|Fi ) − n-1 ∑ ( PT y ( x*| Θ ; θi , eT ) − Cx*|Θ )
i =1
i =1
Expected outcome with
use of seasonal forecasts
Expected outcome based on
historical climate information
Where:
P =
crop price
y =
crop yield
x* = vector of crop management strategies that maximize expected return
Cx* = cost of production associated with management strategies x*
Fi = the seasonal rainfall forecast in year i
Θ = the climatological distribution
θi = observed weather in year i
T = the current year
n = the number of historic years sampled
eT =the current value of other environmental variables, limited in this case to
initial soil moisture and nitrogen conditions (representative of soil fertility)
Thus, the value of the forecast is a function of (a) management variables that maximize
expected gross revenues, (b) the cost of production associated with the management
strategies, and (c) climate and environmental variables. For each year of weather data,
crop yield was determined as a function of observed weather and management
optimized for either the forecast or the climatological distribution. Within this
framework, farmers derive value because forecasts are closer to the weather that
actually occurs (when averaged among all years) than the climatological distribution.
Thus, forecast-based management strategies are more optimal for actual weather.
Crop simulation and profit-maximizing management strategies
As a first step, the authors used the APSIMv4.2 crop model to simulate maize yield
response to weather inputs and management strategies, including varying levels of
stand density and nitrogen fertilizer application rate.36 The model required the
following inputs:
36
Yield predictions from this model have been verified through several field experiments conducted
in Kenya and other countries of sub-Saharan Africa.
APPENDIX E. CASE STUDIES
–
Daily weather data (minimum and maximum temperatures, precipitation and
solar irradiance);
–
Dates of planting;
–
Local soil properties;
–
Soil water content at the beginning of the season;
–
Cultivar characteristics;
–
Stand/plant density;
–
Nitrogen fertilizer inputs.
247
The authors used observed daily weather data over 34 years (1968 to 2002) from
stations located within the Katumani and Makindu study areas. They determined
planting dates for each year of the simulation based on the first time that at least 25
millimetres of rain fell on two consecutive days within the fall planting window
(October 15 to November 15). If this did not occur, the authors assumed planting took
place on November 15. Local soil properties, initial soil water content and cultivar
characteristics were held constant across the simulation years.
To identify optimal management, the authors considered four different stand densities
and 11 fertilizer application rates. They then selected the combination of stand density
and fertilizer application that resulted in the highest average gross margin under
different climate conditions. The authors determined gross margins using agricultural
enterprise budgets, which they developed based on local cost data for production
inputs and market price data for maize.
Forecast scenarios
Next, the authors developed seasonal hindcasts, simulating what the forecast would
have been for each year of the 34-year simulation period. The authors developed
hindcasts for two different GCM-based forecast types that incorporated a common set
of global sea-surface temperature (SST) boundary conditions:
–
Observed SST seasonal forecast – a 24-member ensemble of GCM simulations
driven by “observed” monthly global SSTs. This is not a true forecast prediction
because it incorporates information that would not have been available until after
the forecast date. The authors developed this hindcast to simulate the skill level of
forecasts that are available today;
–
Persisted SST seasonal forecast – a 12-member ensemble of GCM “predictions”
derived by adding SST anomalies observed in August to long-term average global
SSTs during the October through February forecast period.
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VALUING WEATHER AND CLIMATE:
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The persisted SST forecast was used to represent the simplest possible SST forecast
system and served as a lower limit in terms of GCM forecast skill for the study region.
The observed SST forecast was used to represent the upper limit of operational
predictability from a given GCM-based seasonal forecast system.
To assess the value of these forecasts, the authors used APSIM and crop enterprise
budgets to determine the gross margins realized each year of the simulation period,
based on (a) the optimal management strategies selected for the forecast, and (b) the
actual observed weather. The authors compared the gross margins for the different
forecast scenarios to those that would have been realized using a climatological
approach. The authors also evaluated gross margins for a scenario in which the farmer
had perfect knowledge of daily weather conditions. For each scenario, they evaluated
optimal management strategies and gross margins with and without labour costs as a
factor of production. Labour costs were estimated based on a 1989–1997 field experiment
conducted at a local research station. The authors assumed that labour required for
sowing is proportional to stand density associated with the different forecasts.
E.6.3
Results and key findings
The results of the APSIM analysis indicated that optimal fertilizer rate and stand density
varied considerably in response to rainfall variability. In wet years, gross margins were
best at a higher fertilizer rate and higher stand densities; in dry years, the authors
found that the optimal fertilizer rate and stand density were much lower. This positive
interaction between rainfall and optimum input levels suggests that farmers should
adjust fertilizer and stand density jointly to exploit the greatest value from seasonal
rainfall forecast information.
Table E.8 summarizes the estimated value of three forecast information scenarios:
perfect knowledge of daily weather, GCM simulations run with observed SSTs, and
Table E.8. Predicted value of seasonal rainfall forecasts
Value (K Sh per hectare per year)
% of gross margin
Katumani
Makindu
Katumani
Makindu
Perfect information
9 333
6 851
68.7
43.6
GCM, observed SSTs
3 277
1 383
24.1
8.8
GCM, persisted SSTs
-794
-1 289
-5.8
-8.2
Perfect information
11 657
7 268
44.2
23.6
GCM, observed SSTs
4 295
734
16.3
2.4
GCM, persisted SSTs
31
-1 066
0.1
-3.5
Including labour cost
No labour cost
Note: At the time of this study, K Sh 1 was equivalent to US$ 0.01319 and € 0.00997.
APPENDIX E. CASE STUDIES
249
GCM forecasts run with persisted SSTs. As shown, the estimated value of perfect
information represented 24%–69% of gross margin, depending on location and
whether or not labour costs were considered. These results suggest that farmers would
increase their average income from maize substantially if they could perfectly
anticipate weather for the upcoming growing season.
As expected, the estimated value of seasonal predictions from the observed SST
forecast was lower than the value of perfect information. However, the use of this
forecast increased average gross margins by 24% at Katumani and by close to 10% at
Makindu. At both sites, omitting the labour expenditure from the enterprise budget
increased the average optimum planting density and fertilizer application in response
to the observed SST forecast. This increased the yield enough to offset the increased
cost of seed and fertilizer, and therefore increased the forecast value on an absolute
basis at Katumani, but not at Makindu. The authors reported that forecasts based on
the persisted SST forecast showed negative or near-zero value largely because they did
not show significant positive prediction skill. However, the authors maintain that the
persisted SST forecast likely under-represents the skill of seasonal rainfall forecasts
currently available for the study region (see Hansen et al., 2009).
E.6.4
Outcomes and recommendations for tailoring methods to NMHS
circumstances
As noted above, several studies have examined the potential value of seasonal forecasts
for on-farm management using crop growth models and profit maximization
principles. These studies range in complexity, but generally require significant
expertise related to local agricultural production, crop growth and economic
optimization models. Many NMHSs do not have this expertise in-house and may need
to hire an outside consultant to perform this type of analysis.
Although these types of studies can be time and resource intensive, they can serve as
important tools in helping NMHSs and in-country partners (for example, agricultural
extension agencies and food security organizations) to identify management strategies
that could result in the greatest benefits for farmers under different forecast scenarios.
The results of such studies could be used by NMHSs to encourage farmers to use
seasonal forecasts and adopt alternative strategies when warranted.
As Hansen et al. noted, a primary limitation of their study is that it focuses on the effect
of only two management strategies, thereby ignoring many other determinants of
forecast value. For example, the authors report that farmers who participated in
two-day training workshops at each of the project locations in 2004 collectively
identified a wide range of potential management responses related to: timing and
method of land preparation, crop and cultivar selection, planting strategy, weeding,
soil fertility management, pest management, area cultivated, terrace maintenance,
labour procurement and allocation, fencing and cover for livestock, forage
management, and grain and fodder storage. However, the available options differ
substantially among farms, and particularly between commercial farms and
smallholder farms; the latter tend to be more diversified and much more resource
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constrained. A more realistic and robust picture of the potential value of seasonal
forecasts to farmers could be obtained from a farm-level analysis that represents the
heterogeneity of farm types and includes additional management options.
As detailed in the main guidance chapters of this publication, studies that use decision
analysis to assess the value of met/hydro services for an individual decisionmaker do
not take into account the potential price effects associated with the widespread use of
seasonal forecasts. For example, a single agricultural decisionmaker who begins using
seasonal forecasts would have little impact on supply or demand within the local
region. However, widespread adoption of seasonal forecasts may cause changes in
total supply, which would have an impact on price in a competitive market. Price
changes would impact both consumers and producers as the market settles at a new
equilibrium.
REFERENCE
Hansen, J.W., A. Mishra, K.P.C. Rao, M. Indeje and R.K. Ngugi, 2009: Potential value of
GCM-based seasonal rainfall forecasts for maize management in semi-arid Kenya.
Agricultural Systems, 101(1–2):80–90.
APPENDIX E. CASE STUDIES
E.7
CASE STUDY 6: ASSESSING THE VALUE OF MET/HYDRO
INFORMATION IN SWITZERLAND FOR THE AVIATION
TRANSPORT SECTOR
E.7.1
Background
251
In 2009, MeteoSwiss commissioned a pilot study to evaluate the benefits of met/hydro
services in Switzerland for different sectors of the economy. This study (Frei, 2010) was
part of a larger goal to understand how weather-sensitive sectors use met/hydro
services to make decisions, and to identify improvements in these services that would
result in additional social and economic benefits. The objective of the pilot study was
to provide initial, order-of-magnitude benefit valuations because at the time it was
undertaken, very little was known about the value of met/hydro services in
Switzerland.
The author of the 2010 study used a benefit-transfer approach to develop rough
valuations of the economic benefits of met/hydro services for Swiss households and the
agriculture and energy sectors. Results indicated that the benefits from met/hydro
services (excluding long-term climate services) in Switzerland amount to hundreds of
millions of Swiss francs, with a probable BCR of 5 to 1. This estimate does not include
benefits for key economic sectors that were not evaluated as part of the study, such as
insurance, telecommunications, tourism, transport and logistics.
Based on the findings of this analysis, MeteoSwiss agreed that more detailed, sectorlevel analyses were necessary to gain a better understanding of the value of met/hydro
services within the Swiss context and to indicate how met/hydro services could be
improved to maximize social and economic gains. Towards that end, Frei and
colleagues Stefan von Grünigen and Saskia Willemse conducted two additional
studies, focusing on the economic value of met/hydro services for the road and
aviation transport sectors (Frei et al., 2014, and von Grünigen et al., 2014, respectively).
Case study 6 focuses on the aviation transport study (von Grünigen et al., 2014), which
applies a simple decision model to analyse the economic benefits of using TAFs for
Switzerland’s domestic airlines at Zurich airport.
E.7.2
Methods used
Von Grünigen et al. used a decision model to evaluate the benefits of TAFs in terms of
avoided costs for Switzerland’s domestic airlines at Zurich airport. The following
describes the decision model and data that the authors used to quantify this benefit.
Decision framework
In weather-sensitive sectors, met/hydro information serves as an important input into
decisionmaking and production processes. Thus, the use of met/hydro forecasts results
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in better-informed decisions relative to a scenario in which decisionmakers do not use
forecast information or rely only on climate data. This generally leads to increased
economic gains through lower production costs and/or improvements in the quality or
quantity of output. We can therefore evaluate the economic benefits of met/hydro
services by comparing the outcomes that occur when decisionmakers use met/hydro
services to the outcomes that occur when they do not.
Applying this theory to the aviation sector in Switzerland, von Grünigen et al.
developed a decisionmaking model to analyse how the use of TAFs can reduce fuel and
flight deviation costs for airlines. The model assumes that an airline’s decision to carry
additional fuel on a particular flight is based on forecast weather conditions. If adverse
weather conditions are expected at the destination airport, pilots and flight dispatchers
carry an additional fuel reserve to better deal with weather-related flight time
extensions. Without this additional fuel reserve, there is an increased risk that a flight
will have to deviate and land at an alternative airport. Flight deviations lead to
additional passenger compensation, transfer, landing fee, fuel and reputation costs,
among others. Thus, additional fuel serves as insurance against the risk of costs from
avoidable deviations. The price of this insurance is equal to the price of the fuel burned
to carry the additional fuel. In other words, airlines face a trade-off between the
insurance fee (that is, the cost of carrying additional fuel) and the downside risk (that
is, the cost of deviation).
Decision model
Whether or not an aeroplane can land at its destination airport depends on (a) actual
weather conditions at the destination, and (b) the decision to carry extra fuel.
For this study, the authors considered two different weather conditions: “good” and
“adverse”. The decision model assumes that if the weather is good, landing is always
possible. During adverse weather conditions, landing is possible with probability p if
extra fuel was carried and with probability q without the extra fuel. Hence, a deviation
to another airport occurs with probability 1 − p if extra fuel was carried and with
probability 1 − q without extra fuel. Figure E.1 provides an illustration of this decision
process.
The authors modelled the decision process under two scenarios: one in which airlines
use TAFs to make decisions and one in which they do not. They then compared the
expected costs associated with each scenario, as described below, to obtain the
economic benefits of TAFs.
For the airlines, cost components include the cost of deviation (D) if the flight cannot
land and the cost of insurance (I) if the airline carries additional fuel. To obtain
expected costs associated with the use of TAFs, the authors defined a specific cost
variable for each combination of forecast and actual weather, as shown in Table E.9.
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APPENDIX E. CASE STUDIES
yes
no
Adverse-weather
fuel reserve
Additional fuel
carried
Adverse weather
conditions at the
destination
p
Landing
Additional fuel
not carried
Good weather
conditions at the
destination
Adverse weather
conditions at the
destination
1-p
Deviation
q
Landing
Landing
Good weather
conditions at the
destination
1-q
Deviation
Landing
Figure E.1. Decision paths implemented in the model
Source: Von Grünigen et al. (2014)
For example, C2 represents the costs that airlines incur when adverse weather
conditions are forecast but the actual weather is good; C2 is equal to insurance costs I
since in this case the airline would have decided to carry additional fuel based on the
adverse forecast and it would not incur deviation costs. Costs C1 and L are calculated
based on insurance costs I, deviation costs D, and probabilities p and q (see Figure E.2),
as follows:
C1 = C2 + [(1 – p) × D]
Thus, the costs that airlines incur when adverse conditions are forecast and adverse
conditions actually occur (C1) are equal to the cost of carrying additional fuel (C2),
plus the probability of deviation when additional fuel is carried (1 – p) multiplied by
the cost of deviation (D).
Table E.9. Costs incurred for different combinations of forecast and actual weather
Forecast weather conditions
Adverse
Good
Actual weather
conditions
Source: Von Grünigen et al. (2014)
Adverse
C1
L
Good
C2
0
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Table E.10. Relative frequency of forecast and actual weather conditions
Forecast weather conditions
Adverse
Good
Actual weather
conditions
No forecast
Adverse
F11
F21
F01
Good
F12
F22
F02
The costs that airlines incur when good conditions are forecast but adverse conditions
actually occur (L) are equal to the probability of deviation when additional fuel is not
carried (1 – q) multiplied by the cost of deviation (D):
L = [(1 – q) × D]
To calculate costs that airlines incur with the use of TAFs, the authors had to determine
the frequency with which forecast conditions accurately predicted the actual weather
conditions. For the no-forecast scenario, the authors had to determine the percentage
of time that the actual weather was considered “adverse” and the percentage of time
that it was considered “good”. These frequencies are represented in Table E.10.
The expected costs associated with the use of TAF forecasts (ECT) are then calculated
by the cross-multiplication of Tables E.9 and E.10, as follows:
ECT = F11C1 + F12C2 + F21L
In most cases, airlines have to carry enough fuel to reach one alternative destination
airport (for example, Basel or Geneva when flying to Zurich) in case of an emergency.
When TAFs are not used, regulations require airlines to carry enough additional fuel to
reach two alternative airports instead of one. This additional cost (A) is considered in
the calculation of the expected costs associated with not using TAFs (ECNT), as follows:
ECNT = F01C1 + F02C2 + A
Based on these calculations, the authors were able to calculate the economic value
(EV) of the TAFs, as follows:
EV = ECNT – ECT
Data
To estimate EV, the authors input economic, aeronautical and meteorological data into
the model described above. They obtained economic and aeronautical data from two
different domestic airlines, a network carrier and a point-to-point carrier, and Zurich
airport. Meteorological data were provided by MeteoSwiss.
APPENDIX E. CASE STUDIES
255
The airlines provided estimates of aeroplane-based cost components, fuel prices and
the probabilities p and q, while Zurich airport provided detailed information about
flight plans and landing frequencies. Based on this information, the authors classified
flights into categories by flight duration. For each category, the authors defined a
typical aeroplane and assigned costs accordingly.
The authors used TAF verification data for the period April 2008 to March 2010. This
verification is based on the comparison of the forecast and the actual meteorological
parameters of visibility, cloud base, wind speed and direction, as well as the present
weather. The authors used visibility to determine the two weather situations needed
for the model. They defined weather conditions as “good” when visibility was greater
than or equal to 5 000 metres, and “adverse” when visibility was less than 5 000 metres.
The authors used visibility as their leading parameter because various weather
conditions affect visibility, and the forecast quality for visibility is worse than for other
parameters, which prevents the overestimation of the economic benefits connected
with the use of TAFs. Additionally, there are clear rules concerning visibility and airport
operations (time between landings, closure of runways, and the like), whereas the
same cannot be said for the other available parameters. Based on the verification of the
TAF forecasts between April 2008 and March 2010, the authors calculated the relative
frequencies of the forecast and actual weather conditions.
E.7.3
Key findings and results
This paper demonstrates that the use of TAFs at Zurich airport generates significant
economic benefits for domestic airlines. Results of the analysis indicate that the
economic benefits of TAFs amount to between SwF 73 and SwF 1 780 (US$ 78–
US$ 1 906)37 per landing, depending on the duration of the flight. In 2009, there were
roughly 110 000 landings registered at Zurich airport, of which 60% were generated by
domestic airlines. Together, the two airlines included in this study generated more
than 95% of all the landings by domestic airlines. Thus, the authors estimated the
overall economic benefits of TAFs to Switzerland’s domestic airlines at Zurich airport by
adding the benefits of the landings by the two airlines and extrapolating average
benefits per landing to the other 5% of landings. Based on this methodology, the
authors evaluated the total economic benefits of TAFs at approximately SwF 14 million
(US$ 15 million) per year. The authors did not report the costs associated with
installing and using TAFs.
These results are based on costs estimated by the airlines involved in the study. To take
into account the uncertainty in these calculations, the authors evaluated total benefits
based on benefit-maximizing and benefit-minimizing estimates provided by the
airlines (see von Grünigen et al. (2014) for more information on these scenarios). These
calculations yield a range of values for the economic benefits to domestic airlines at
Zurich airport of between SwF 11 million and SwF 17 million (US$ 12 million–
US$ 18 million) per year.
37
Exchange rate used in the report.
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The authors extrapolated these results to Geneva airport based on the average benefit
per flight to estimate the total economic benefits of TAFs to Switzerland’s domestic
airlines at the two main airports. This analysis indicates that total economic benefits of
TAFs amount to between SwF 13 million and SwF 21 million (US$ 14 million–
US$ 22 million) per year. However, this valuation does not account for the different
economic and aeronautical conditions at Geneva airport. In addition, all results are
very sensitive to changing fuel prices, as the authors found fuel to be the most
important cost factor within the context of this study.
E.7.4
Tailoring the study to NMHS circumstances
This study was performed by a consultant, in coordination with MeteoSwiss, over a
period of about nine months. The cost of the study amounted to approximately
SwF 91 000 (US$ 100 000). This included interviews with airline representatives to help
develop the decision model and provide important inputs. The decision model
employed is relatively simple, and could potentially be completed in-house with the
adequate expertise and resources.
In the authors’ view, one main lesson from their work can be useful for similar studies:
companies know quite well where and why they use meteorological information;
however, they often cannot easily quantify the benefits related to that use. Thus,
NMHSs should not rely on surveys or interviews to learn about the monetary benefits
of meteorological information. Instead, they should conduct explorative interviews to
understand the decisionmaking process within the companies. Then, based on that
knowledge, the agencies should build, validate and use a decisionmaking model to
evaluate the monetary benefits.
Interviews with airline managers and flight dispatchers conducted as part of a broader
study (Bade et al., 2011) on the economic benefits of meteorological services in the
Swiss transport sector confirmed this observation. According to von Grünigen et al.,
the interviews showed that meteorological information is very important for the safety
and profitability of the aviation industry. However, in most cases, interviewees could
not separate the contribution of meteorological information to safety and profitability
from other contributions (for example, organizational measures).
In the current context, the use of a decisionmaking model to analyse the economic
benefits of TAFs enabled the authors to draw, ceteris paribus (that is, all else equal),
conclusions concerning the influence of TAFs on the profitability of airlines. This simple
model provides (at minimum) order-of-magnitude estimates for the economic benefits
that can be expected from the use of met/hydro services.
REFERENCES
Bade, S., S. von Grünigen, W. Ott, N. Kaiser, M. Häcki, T. Frei, S. Willemse and Y. Abrahamsen,
2011: Der volkswirtschaftliche Nutzen von Meteorologie in der Schweiz – Verkehr und Energie.
APPENDIX E. CASE STUDIES
257
Report prepared for MeteoSwiss, https://www.yumpu.com/de/document/view/6028139/
der-volkswirtschaftliche-nutzen-von-meteorologie-in-meteoschweiz.
Frei, T., 2010: Economic and social benefits of meteorology and climatology in Switzerland.
Meteorological Applications, 17:39–44.
Frei, T., S. von Grünigen and S. Willemse, 2014: Economic benefit of meteorology in the Swiss
road transportation sector. Meteorological Applications, 21:294–300.
von Grünigen, S., S. Willemse and T. Frei, 2014: Economic value of meteorological services to
Switzerland’s airlines: The case of TAF at Zurich airport. Weather, Climate and Society,
6:264–272.
258
E.8
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CASE STUDY 7: EVALUATING THE AVOIDED COSTS OF THE
FINNISH METEOROLOGICAL INSTITUTE’S MET/HYDRO SERVICES
Case study 7 highlights an economic assessment prepared by VTT to evaluate the
benefits of the met/hydro services of FMI (published as part of Hautala and
Leviӓkangas (2007) and Leviӓkangas and Hautala (2009)).
E.8.1
Background
The Finnish Meteorological Institute was one of the first NMHSs in Europe to conduct
an economic valuation of its services. The institute initiated this effort in 2006, even
ahead of the Madrid Action Plan, as well as impending service model changes
associated with the European Union’s INSPIRE directive. The institute’s goal for this
study was to determine the value that met/hydro services generate per euro of FMI
budget.
At the time that FMI initiated its analysis, VTT was in the midst of developing EVASERVE
(www.EVASERVE.fi), a set of evaluation tools designed to support the development
and implementation of different types of information services in Finland. The Technical
Research Centre launched EVASERVE in 2006 because it believed that information
services had not penetrated the market to the extent possible with modern information
and communication technologies.
Leveraging resources from both agencies, FMI and VTT worked together to integrate
the economic assessment of FMI services into the EVASERVE project – FMI reported
that partnering with VTT helped ensure a reasonable degree of independence for the
assessment, thereby raising the credibility of the results. Staff members from VTT,
Raine Hautala and Pekka Leviӓkangas, served as the lead analysts and lead authors for
the assessment.
Following the EVASERVE framework, the authors focused on developing monetized
benefit valuations for various sectors and user groups. Specifically, the economic
assessment evaluated the impacts and benefits of FMI met/hydro services for
transportation, construction and facilities management, logistics, energy, and
agricultural production. For most sectors, the authors’ assessment provides initial,
order-of-magnitude estimates. The Finnish Meteorological Institute continues to
develop more in-depth benefit assessments to help evaluate specific weather service
products. For example, for road transport and rail services additional valuations have
been made (Nurmi et al., 2012; Nurmi et al., 2013).
The study was conducted in 2006 and 2007 and lasted approximately 12 months.
Besides the two above-mentioned senior researchers, nine other VTT researchers
contributed. The Finnish Meteorological Institute steering group had eight members,
mainly senior managers, including the Director-General of FMI at that time. Fifty-two
persons were interviewed, of whom five experts of FMI. Two FMI experts contributed
to the main VTT report. The overall work effort for FMI amounted to approximately
2.5 person months. Several FMI experts indicated that in the year after completion of
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APPENDIX E. CASE STUDIES
the study some working days were also used for dissemination activities, for example,
visiting sister organizations abroad. The work effort of VTT was embedded in the
EVASERVE programme and therefore the specific effort for the evaluation of the services
of FMI is hard to obtain in retrospect, but was probably between 15 and 20 person
months. It should be realized that the socioeconomic impact evaluation (as it was
called) of the FMI services at the time was the first of its kind for VTT. The programme
EVASERVE was mainly funded by the Finnish Funding Agency for Innovation, although
other stakeholders, such as FMI, did contribute with moderate amounts.
E.8.2
Methods
This section describes the general methods that the authors used to assess the benefits
of FMI services, including an overview of the assessment framework, input data and
valuation methods.
Assessment framework
The authors applied a general framework to evaluate the benefits of met/hydro
services within each sector (Figure E.2). First, they identified “impact mechanisms”
associated with different met/hydro services. Impact mechanisms represent decisions
or behaviour that can be altered in response to met/hydro information. For example, in
the road transportation sector, drivers may decide to stay at home or avoid specific
areas in response to information on adverse weather and road conditions. In this case,
driver behaviour is the impact mechanism.
Pre-study
Literature
Interviews,
workshops
Statistical analysis;
review of empirical data;
analytical model construction
Impact
mechanisms
Impacts
Pricing,
cost data
Analyst
Benefits
Validation by
experts
Figure E.2. Valuation process, repeated for each sector
Source: Leviӓkangas and Hautala (2009)
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Second, the authors identified and quantified the actual impacts (often referred to as
outcomes) resulting from changes in the identified decisions or behaviour. Following
the example above, changes in driver behaviour in response to relevant weather
information would likely reduce the number and severity of accidents on the roadway.
This reduction would represent the impact of the weather information.
Finally, when feasible, the authors attached unit prices to the identified impacts to
obtain benefit estimates in terms of avoided costs. For the road transportation
example, the authors evaluated benefits based on the avoided costs associated with
the reduction in the number and severity of car accidents.
The authors then applied this framework to evaluate the impacts and benefits of (a)
current FMI services, and (b) services that deliver perfect information.
To assess the value of current services, the authors used data and interviews to
determine the current level of use of met/hydro services, how individuals and
organizations change their decisions in response to this information, and how this
benefits the decisionmaker, or others. The authors then evaluated FMI services under a
perfect information scenario, where they assumed perfect forecast accuracy and that
all potential users of met/hydro information had access to it, used it and adjusted their
behaviour and decisions accordingly. The authors used the concept of perfect
information so that FMI would have a reference point for the maximum benefits that
could be achieved through the dissemination of met/hydro information.
As noted above, the authors evaluated the impacts and benefits of FMI met/hydro
services only for Finland’s transportation, construction and facilities management,
logistics, energy and agricultural sectors. However, many other economic sectors are
likely also to benefit greatly from the FMI services. The authors excluded these sectors
from the analysis because of lack of available data or difficulties in expressing benefits
in monetary terms. In addition, VTT did not have the expertise or resources to conduct
an exhaustive analysis. The authors assumed that the sectors included in the analysis
represented the greatest beneficiaries of FMI services. However, this study is only a
partial analysis of the total benefits of FMI services.
Input data and valuation methods
To determine the impacts and benefits of FMI services for each sector, the authors
started with an extensive review of existing literature on the economic valuation of
met/hydro services. With the exception of the agricultural sector, for which they relied
on data from a previous study, the authors also conducted interviews with sector
experts and FMI representatives.
When possible, the authors used available data, statistics and models to quantify the
impacts associated with the use of met/hydro services in each sector. They relied on
literature, interviews, market price data and other available information to assign
monetary values to the quantified impacts. Box E.2 provides a brief description of the
pricing regimes used in this valuation.
APPENDIX E. CASE STUDIES
261
Box E.2: Unit costs used to obtain benefit valuations
Accident costs: To obtain benefit valuations in terms of avoided accident costs, the authors
used official accident unit costs published by the Finnish Road Administration. These
estimates include costs associated with personal injuries (including hospital and health-care
costs and loss of production), loss of well-being and human suffering (based on Nordic
studies of WTP) and material damages. The Finnish Road Administration and the Ministry of
Transport and Communications update these unit costs on an annual basis. With the
exception of material damages, the authors applied the same costs to the number of
avoided accidents resulting from the use of met/hydro services whether in the road, rail,
water or aviation transportation sectors.
Time costs: Met/hydro information can also reduce travel and transport time. To monetize
this benefit, the authors applied standard values for time, as established by the Ministry of
Transport and Communications for use in Finnish transport investment calculations. These
values are based on (a) average salaries of transport operator personnel (for example, bus
drivers, truck drivers, train engineers) and business travellers, as determined based on
national labour statistics; and (b) time values for commuters and leisure travellers, based on
WTP studies carried out in Nordic countries.
Cost savings in operations and other benefits: To evaluate operational cost savings
associated with the use of met/hydro information, the authors primarily relied on interviews
and the confidential statistics that interviewees provided. The authors conducted a total of
60 in-depth interviews with managers and experts from various fields. They used the cost
information obtained in these interviews to evaluate costs for the whole of Finland. When
the uncertainties of upscaling were too high, the authors did not use monetary estimates.
Information was provided by FMI on the costs of producing selected services. In
addition, because FMI shares the Finnish meteorological information market with one
other major met/hydro service provider, Foreca Ltd., the authors had to estimate the
percentage of total benefits generated solely by FMI services. The authors determined
this percentage based on the estimated market share of the two providers. Using
information from interviews, customer data and the judgment of VTT experts, the
authors estimated FMI’s total market share to be approximately 70%. Thus, they
assumed that FMI services generate 70% of the total benefits that result from the use of
met/hydro services in Finland.
Because the authors used different methods and varying levels of analysis to evaluate
impacts and benefits for different sectors, they consider some estimates to be more
reliable than others. For example, to evaluate benefits for the road transportation
sector, the authors used an existing impact model that applied standard methods and
data. The authors and interviewees also had a comprehensive understanding of the
use and benefits of met/hydro services in the transportation sector. The authors
therefore considered the estimates for the sector to be fairly reliable. On the other
hand, although the value of met/hydro information was explicitly recognized by
railway managers, little data and few existing studies supported the benefit valuations
for the rail transportation sector. Similarly, there were very little data on the use and
value of met/hydro services in the logistics and supply-chain operations sector. The
authors therefore analysed benefits for these sectors based on interviews and
subjective scaling of impacts to the national level and considered the reliability of these
valuations to be relatively weak.
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Table E.11. Evaluated benefits of the Finnish Meteorological Institute’s current
services and the additional value of perfect information
Sector
Impact
Road transportation
Reduction in accidents, more efficient infrastructure
maintenance
Pedestrians and cyclists
Reduction in slipping accidents, more efficient
maintenance
Waterways and marine
transportation
Reduction in accidents and environmental damage,
more efficient operations, reduction in fuel
consumption
Aviation
Reduction in accidents and emissions, more efficient
operations, time savings for travellers
Rail transportation
Higher accuracy of train timetables, passenger and
freight time savings
Logistics, supply chain
Higher predictability of deliveries, reduction in
storage costs and risks
Construction, facilities
management
Mould and mildew damage prevention, more-efficient
maintenance
Energy production and
distribution
Improved production capacity and availability
predictions, reduced damage, prevention of
production and distribution interruptions
Agriculture
Crop protection, pest control and damage reduction,
improved harvest timing
Total
Source: Leviӓkangas and Hautala (2009)
E.8.3
Results and key findings
As shown in Table E.11, the authors evaluated the annual benefits of current FMI
services for the selected sectors at between € 262 million and € 285 million (2006
euros) per year (between US$ 359 million and US$ 390 million).38 The annual budget
of FMI is between € 50 million and € 60 million (US$ 68.5 million to US$ 82.2 million).
Thus, the annual BCR for existing services is at least 5 to 1, and potentially up to 10
38
Based on an average 2007 exchange rate of US$ 1.37 to € 1.
APPENDIX E. CASE STUDIES
Value of current FMI services
(€ millions)
263
Value of additional benefits with perfect information
(€ millions)
Accidents: 9–18
Maintenance: 2
Accidents: 9–18
Maintenance: not calculated
Slipping accidents: 113
Slipping accidents: 122–203
Maintenance: not calculated
Accidents: 14–28
Efforts to combat oil spills: 10
Rescue operations fuel savings: 1
Not calculated
Accidents: 46
Fuel savings: 4
Airport maintenance: 3
Environmental damage: 1
4 total
Time savings: 0.3
Time savings: 0.2
Not calculated
5 total
Construction: 10
Facilities management: 5
Construction: 10
Facilities management: 5
Prevention of interruptions: 2
Production predictions: 3
Peat production: 5
Prevention of interruptions: 3–8
Production predictions: 5–15
Increased crops: 12
Crop damage: 12
More efficient cultivation: 8
Other benefits: 2
3–15 total
262–285
166–283
to 1. In the case of perfect information, the benefits of FMI services would increase
by 65% to 100%.
For the road transportation sector, the authors evaluated the avoided costs associated
with accident reduction to be from € 9 million to € 18 million per year and that perfect
information would double these benefits. Furthermore, met/hydro services would
generate another € 2 million in annual benefits in terms of avoided road maintenance
costs. In the aviation, and waterways and marine transportation sectors, accident
reduction benefits amounted to approximately € 14 million to € 46 million per year in
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avoided costs. The authors evaluated the total benefits of current met/hydro services at
approximately € 34 million per year for agriculture. This figure included both avoided
damage costs and improved productivity.
A somewhat surprising result of the study was that warnings about slipperiness for
pedestrians and cyclists appear to be the single most beneficial service. The reduction
in medical costs, lost working hours, avoided lifelong injuries and even lives saved was
evaluated at € 113 million per year at the current level of services. A population
accessing perfect information would avoid another € 120 million per year. These
figures are somewhat uncertain because of attribution issues and the varying valuation
basis of the avoided cost elements. However, even if the benefits for this sector were
halved, the amount would still be significant. Furthermore, the result would still signal
that the costs avoided for non-motorized transport modes are more significant than for
motorized ones.
E.8.4
Finnish Meteorological Institute outcomes
According to FMI, the VTT valuation illustrated the potential to capture additional
benefits by also improving the later stages of the value chain associated with FMI
services. Following the study, FMI intensified its engagement with the media and
various user groups, conducting surveys at intervals of two to three years. This
engagement has resulted in a steady flow of improvements and innovations in weather
and climate services, both in the public and commercial domains. In addition, FMI has
also developed new services for the public sector (for example, emergency services) in
cooperation with other public agencies and ministries.
Finally, after this study was completed, FMI also established a research group to
assess the societal impacts of climate change and climate adaptation, as well as
economic valuation of weather and climate services. Economists from this group have
assessed SEBs of selected services for some sectors. Efforts have also been increased
by FMI to develop a large database with joint observations of impacts and weather or
climate conditions by time period and area. Such databases enable more thorough
economic valuations of impacts and impact reduction attributable to weather
services. More recently, the group is elaborating on the notion that assessment of the
effectiveness of improved weather services can also apply to climate change
adaptation studies (Perrels et al., 2013; Pilli-Sihvola et al., forthcoming). Studies by this
group reaffirm the significance of monitoring and improving all stages of the value
chain (Nurmi et al., 2013).
E.8.5
Tailoring analysis to NMHS circumstances
The study we have summarized has provided order-of-magnitude valuations for the
benefits of met/hydro services in terms of avoided costs for Finland’s transportation,
construction management, facilities management, energy and agriculture sectors. The
assessment framework provided a straightforward process that NMHSs can use to
APPENDIX E. CASE STUDIES
265
evaluate the benefits of met/hydro services within the context of the met/hydro
services value chain.
To complete the study, the authors made a number of assumptions regarding the use
and impacts of met/hydro services across sectors. The reliability of valuations such as
these depends largely on the availability of impact models and relevant data, as well as
the knowledge and understanding of the use and value of met/hydro services by the
experts that contributed to the study.
Furthermore, this study excluded several economic sectors that would likely benefit
greatly from the services of FMI because of lack of available data, expertise and
resources. The authors assumed that the sectors included in the analysis represent the
greatest beneficiaries of FMI services. However, the study primarily focused on
transportation subsectors.
In addition, although the study accounted for priced weather services in particular
sectors (that is, the authors subtracted these costs from the benefit estimates to obtain
net benefits), it did not consider media costs associated with information acquisition
and processing. The BCR for met/hydro services would be slightly lower if these costs
were taken into account.
The authors also did not account for price effects associated with increased efficiency in
relevant sectors. Finally, since the applied valuation methods involved both actual costs
and WTP estimates, readers should consider some of the study’s aggregate sums with
caution and avoid making direct comparisons with GDP or the total public budget.
Despite these limitations, NMHSs can use this type of analysis to justify their budgets
and to begin to understand the value chain for met/hydro services in different sectors.
Such an effort can lead to more detailed valuations of specific services, serving as an
important feedback tool in the development process.
REFERENCES
Hautala, R. and P. Leviäkangas (eds.), 2007: Ilmatieteen Laitoksen Palveluiden Vaikuttavuus. Hyötyjen
Arviointi ja Arvottaminen eri Hyödyntäjätoimialoilla [The Effectiveness of the Services of the
Finnish Meteorological Institute – Evaluation and Judgment of Benefits for Various Sectors].
VTT publications No. 665. Espoo, Technical Research Centre of Finland.
Leviäkangas, P. and R. Hautala, 2009: Benefits and value of meteorological information services
– The case of the Finnish Meteorological Institute. Meteorological Applications, 16:369–379.
Nurmi, P., A. Perrels and V. Nurmi, 2013: Expected impacts and value of improvements in
weather forecasting on the road transport sector. Meteorological Applications, 20:217–223.
Nurmi, V., A. Perrels, P. Nurmi, D. Seitz, S. Michaelides, S. Athanasatos and M. Papadakis, 2012:
Economic value of weather forecasts on transportation – Impacts of weather forecast
quality developments to the economic effects of severe weather. EWENT report D5.2, http://
ewent.vtt.fi/Deliverables/D5/D5_2_16_02_2012_revised_final.pdf.
266
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Perrels, A., A. Harjanne, V. Nurmi, K. Pilli-Sihvola, C. Heyndricx and A. Stahel, 2013: Sector
specific and generic impacts of enhanced weather and climate services in a changing
climate. Report for deliverable 2.2. ToPDaD Consortium.
Pilli-Sihvola, K., V. Nurmi, A. Perrels, A. Harjanne, P. Bösch, F. Ciari, forthcoming: Innovations in
weather services as a crucial building block for climate change adaptation in road transport.
European Journal of Transport Infrastructure Research.
APPENDIX E. CASE STUDIES
E.9
267
CASE STUDY 8: ECONOMIC BENEFITS OF IMPROVED MET/HYDRO
SERVICES IN MOZAMBIQUE
This case study39 highlights an economic analysis that was conducted as part of the
Strategic Programme for Climate Resilience project for Mozambique to better
understand the costs and benefits of improving met/hydro services in the country. This
analysis included a three-pronged approach to benefit valuation: (a) a benefit-transfer
approach, (b) an expert elicitation related to specific economic sectors, and
(c) a stated-preference survey of the general public. This case study focuses primarily
on the stated-preference survey of the general public.
E.9.1
Background
In recent years, Mozambique has been hit by several major flooding events. In 2000,
2001, 2007 and 2013, extreme weather and water events collectively resulted in over
1 200 deaths, displacement of 1.5 million people and destruction of US$ 1.5 billion in
physical infrastructure. Most recently, extreme flooding hit Mozambique in the lower
stretches of the Limpopo, Incomati and Zambezi river basins in January and February
of 2013. Over 170 000 people were evacuated, 113 lives were lost, and 89 000 hectares
of crops were destroyed. The spread of malaria and schistosomiasis increased with the
rising, stagnant waters. The economic costs of the physical damages were estimated to
be in the order of US$ 403 million.
The mandate for water and weather observation and forecasting is delegated to
several agencies across two government ministries in Mozambique. In the Ministry of
Public Works and Housing (Ministério das Obras Públicas e Habitação), the National
Directorate of Water (Direcção Nacional de Águas) and the five Regional Water
Authorities (Administrações Regionais de Águas) are responsible for hydrology. The
Ministry for Transport and Communication (Ministério dos Transportes e
Comunicações) delegates responsibility for meteorology to the National Institute for
Meteorology (INAM – Instituto Nacional de Meteorologia).
Since the mid-1990s, the World Bank and other international partners have actively
supported the water sector in Mozambique. Building on a programme of water sector
support, the World Bank developed a Country Water Resources Assistance Strategy for
Mozambique in 2009. This programme committed the Bank to identify financial
resources for enhancing met/hydro data for the core operation of water resources
planning, infrastructure development and transboundary cooperation with
neighbouring countries.
The Country Water Resources Assistance Strategy for Mozambique spurred a number
of activities and investments related to improving met/hydro services in the country. In
2011, Mozambique initiated a National Water Resources Development Programme,
39
Development of this case study benefited significantly from materials provided by Louise
Croneborg, one of the World Bank task team leads for this work. Any remaining errors are solely
the responsibility of Jeff Lazo who was lead on the economic analysis. For more information on this
study please see Lazo and Croneborg (forthcoming).
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with the support of the World Bank’s International Development Association, that
included a dedicated project for strengthening the country’s met/hydro services. That
same year, the World Bank’s Climate Investment Fund created a Strategic Programme
for Climate Resilience for Mozambique, which established a pilot investment for met/
hydro services. Following approval of the Strategic Programme for Climate Resilience,
Mozambique’s Council of Ministers endorsed a National Strategy for Climate Change
in which they specified the need to strengthen the work of INAM, the Direcção
Nacional de Águas and the Administrações Regionais de Águas as a key national
priority. In 2013, the World Bank approved additional funding for the National Strategy
for Climate Change for a dedicated project to improve met/hydro services within the
country. This project is also financed by parallel financing from the Nordic
Development Fund.
The objective of the economic analysis, which was funded by the World Bank, was to
evaluate and quantify the assumption that improved met/hydro services will increase
productivity in economic sectors, and to enhance resilience to water and weatherrelated hazards. The analysis evaluated met/hydro services in economic terms in order
to improve dialogue and decisionmaking on policy, planning and budget allocation (as
well as inform project design and implementation). Equally important, the analysis was
intended to enable the responsible government agencies to evaluate their
interventions, optimize the use of current resources and guide future research and
investments.
E.9.2
Methods
The public benefits valuation comprised a multipart, in-person survey to (a) assess
preferences for met/hydro services among Mozambican households, and (b) estimate
household WTP for various services. To assess WTP, the survey included a CV-method
question. The following sections describe the methods that Lazo used to develop and
implement the survey, and also some of the key issues associated with the CV-method
approach.
E.9.2.1
Survey methods – Development, sampling and implementation
The survey was developed based on prior work using the CV approach primarily in the
United States and a limited number of developing countries. Prior CV-method surveys
implemented in other contexts in developing countries were also consulted specifically
to address issues of income limitations, which can impact a respondent’s stated WTP.
A number of surveys on other topics implemented in Mozambique were also used to
base questions specific to Mozambique. For the stated-choice portion of the survey,
a set of weather forecast improvement attributes were defined and quantified based
on a set of focus groups with INAM employees and through a stakeholders workshop
held in Maputo. Once the survey was developed and translated into Portuguese a
small number of in-person preliminary tests were conducted to identify potential
survey issues. Based on these preliminary tests, the survey was revised prior to final
implementation.
APPENDIX E. CASE STUDIES
269
As the survey was conducted in person it was not possible to undertake a random
sample national survey. Instead, the authors selected a limited number of sites for
implementation, attempting to achieve a cross-section of the population based on a
range of country characteristics: urban to be compared to rural areas; southern to be
compared to central and northern areas; different weather and climate regimes. Some
provinces were not sampled at all due to the sparse population, difficulty in getting to
locations and (at the time of implementation) potential violence and political conflicts
in certain areas. Future work should target some of these less accessible areas as they
are also less likely to have access to weather, water and climate information.
The survey was conducted from 11 June to 18 June 2013. Data were collected either
onto hard copy written survey instruments by the interviewer or using personal digital
assistants data capture. In some areas a local public official accompanied the
interviewer and assisted in translation if needed. The survey company did not record
the number of contacts made in order to achieve the target sample size, and therefore
response rates could not be computed. While interviewers did record interview start
times, the company did not record completion time or time to complete. Verbal reports
indicated that interviews lasted 30 minutes or more in general.
E.9.2.2
Contingent valuation method
Given the public-good nature of weather forecasts, the economic value of most
weather forecasting services is not directly observed in the market. It is therefore
difficult to determine the economic value of changes to the services provide, although
this is exactly what is required to undertake a BCA.
In stated-preference method studies such as the one described here, value is estimated
using surveys in which a representative sample of the relevant population expresses a
stated preference that can be directly or indirectly used to determine WTP for a good
or service. The value obtained for the good or service is contingent on the nature of the
constructed market described in the survey scenario. Stated-preference methods
include the CV method and stated-choice methods, both of which were used in the
study. Case study 8 focuses on the CV method aspect of the study. Use of a CV method
refers to the hypothetical transaction framework in which subjects are directly asked to
give information about their values for specific goods or services. Contingent valuation
is often defined to include direct open-ended questions such as “How much would
you be willing to pay for … ?”.
Relative to information a respondent may already have about a commodity, CV studies
need to define the commodity to be valued, including characteristics such as the
timing of provision, certainty of provision and availability of substitutes and
complements. For weather forecasts, it is likely that individuals already have
considerable experience with and a reasonable understanding of such information.
This reduces the cognitive burden of defining and explaining the commodity
compared to other commodities (such as the effects of airborne acid deposition on
cultural monuments).
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Respondents must also be informed about the framework of the transaction, including
the method and timing of payment, and they should be aware of their budget
constraints. The context in which the hypothetical payment decision would take place
is clearly defined to encourage respondents to answer based on their actual
preferences, so individuals are able to identify their own best interests, and to minimize
strategic behaviour. When these conditions are met, it is more likely that individuals’
stated preferences will be consistent with economic measures of welfare change.
Several potential biases or confounding aspects of CV-method studies are generally
addressed in survey design, implementation and analysis. Three that we discuss in this
case study are (a) income constraints; (b) scenario rejection, and (c) altruistic
motivations. Examining such potential biases or confounding issues helps the
researcher have a better understanding of the true value of the commodity of interest
– in this case the value of improved weather information.
E.9.2.3
Income constraints
A significant concern in undertaking non-market valuation studies in developing
countries is that many individuals have no monetary income, and thus asking WTP in
monetary terms may not yield meaningful results regarding the value to a respondent.
We attempted to address this issue by identifying respondents with a monetary
constraint and factoring that into the analysis of responses. Of the respondents
interviewed, 32.1% (185 of 576) indicated that they had no monetary income (another
4.7% refused to answer this question). Rather than imputing a wage based on value of
labour or developing a wealth measure, we developed a variable “money constrained”,
where a zero means there is no difficulty in getting money and 12 means it is
impossible for the individual to get money for these approaches. We feel this scale thus
represents a measure of the individual’s access to monetary activities, whether due to
restricted income or by inability to access monetary transactions. Values on the scale
ranged from no constraint (2.78% of respondents) to extreme constraint (6.60% of
respondents).
E.9.2.4
Scenario rejection
Potential scenario rejection has been a longstanding issue in the CV literature. If the
individual does not understand or believe some aspect of the hypothetical scenario,
she/he may not state a true value for the commodity. In general, it is suspected that
individuals will state a zero WTP if they reject the scenario. It is also possible that
individuals will understate their true value if they feel uncertain about the commodity
or the likelihood of its provision. Some researchers suggest that a high number of zero
bids in an open-ended or payment-card CV survey is evidence of potential scenario
rejection. Because scenario rejection most likely cannot be eliminated from survey
instruments, the most productive approach to dealing with scenario rejection is to
identify potential scenario rejectors through debriefing questions or by examining
responses to questions that would indicate that the individual does in fact have a
positive value for the commodity.
APPENDIX E. CASE STUDIES
271
In an effort to identify and account for potential scenario rejection, we include
debriefing questions exploring individuals’ motivations for their value statement. A
factor analysis of these statements is used to generate a “rejection score” that is then
included in regression analysis as an explanatory variable. Individuals with a high
rejection score are expected to understate their true value or to state a zero value for
the commodity. Not accounting for this potential bias could lead to significant
underestimates of true WTP.
E.9.2.5
Altruistic and bequest values
A third issue we considered is whether individuals’ motivation for stating their WTP for
forecast improvements could be the value they place on their own use or the value
potentially to others (altruistic values), or even to future generations (bequest values).
Such values have been shown to play a significant role in the value of non-market
environmental commodities (for example, clean air or species preservation) but we
had no reason a priori to think such aspects would play a significant role for the value
of weather information, which we feel is primarily for individual use.
E.9.2.6
Payment card
The survey was implemented using a payment-card approach where individuals are
presented the hypothetical scenario and then asked to circle the number on the card
indicating their maximum WTP for the programme (see Figure E.3). Two versions of
the survey were implemented (respondents only saw one of the two versions). One
version had a programme of intermediate improvements on all attributes and the
second version had maximal improvements on all attributes. The payment card was
then followed by debriefing questions regarding potential scenario rejection and
potential altruistic or bequest motivations.
E.9.3
Results
At the time of writing we have not completed a comparison of sample
sociodemographics to population sociodemographics but this should be undertaken
to assess the ability to generalize to the population. The study found:
–
A little less than half of respondents indicated they were single (48%); 45% are
married or in a marital union and the remainder (7%) divorced or widowed;
–
The average length of residence within 50 kilometres or current location is
14.5 years (median was 13 years);
–
Only 9.9% of the respondents indicated being employed full-time; another 23.8%
indicated part-time employment and 22.2% were unemployed; 13.9% were
self-employed or business owners (this is not exclusive of full- or part-time
employment);
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Version: 1
WILLINGNESS TO PAY FOR IMPROVEMENT PROGRAMME
Rather than comparing programmes, we now want you to consider a single programme to improve
weather forecasts as indicate by Programme I below.
Current Accuracy of Forecasts

Programme Q

Cyclone warnings and advisories
lead time
Current lead time 2 days
Increase lead time to 3 days
All other warnings and
advisories lead time
Current lead time one day
Increase lead time to 2 days
Geographic detail
Three sections of country (south,
central, north)
Province level (10+Maputo City)
Time period covered
Currently for entire day
Information broken down
between night and day
Accuracy of high and low
temperature forecasts
One day generally accurate ±2°C
Extend to 2 days with same
accuracy as current 1 day
Accuracy of rainfall information
Correct 75% of the time
Being correct 80% of the time
Maritime information
Correct 70% of the time
Being correct 80% of the time
Reliability of seasonal forecasts
Reliable 65% of the time
Being reliable 70% of the time
Accuracy of flooding and water
levels
Correct 70% of the time
Being correct 80% of the time
hat is the maximum amount you would be willing to pay each year for this single
CVM1 W
programme to improve weather forecasts? Please circle the number below indicating the
maximum annual amount your household would be willing to pay for this programme.
MT 0 (I would
pay nothing)
MT 15
MT 30
MT 60
MT 120
MT 240
MT 480
MT 720
MT 1,440
MT 2,160
MT 3,240
MT 5,400
MT 9,000 or
more
Other (enter amount) ___________
Note: MT = Mozambique meticais.
Figure E.3. Contingent valuation question and payment cards used in the study
APPENDIX E. CASE STUDIES
–
273
A little less than 19% were students, 24.3% were retired and 0.5% considered
themselves homemakers.
A survey code book was developed that shows for each question the frequency of
responses, mean, median, standard deviation, number of responses and number of
missing responses. Initial visual examination of this information allows the researcher
to develop a good “feeling” for the data as well as to check for any coding errors and
assess the potential impact of missing data. This type of data quality assurance/quality
control should be conducted with all survey data prior to analysis.
E.9.3.1
Data adjustments, missing values and fitted income estimation
As is common practice in survey data analysis we selectively replaced a limited number
of missing responses with either the mean or median values so that these observations
were not lost in subsequent multivariable analysis. A set of dummy and recoded
variables were created from questions with multiple categorical responses for
purposes of subsequent data analysis. Specifically, these included dummy variables for
each respondent to indicate: (a) whether they lived in an urban or rural area;
(b) whether they lived in the south part of Mozambique or north-central areas;
(c) if they were employed (full or part-time) or not; or (d) if they had any type of
monetary income. Additional variables were adjusted for analysis including a question
asking whether individuals had experienced any impact from weather or a weather
event over the prior 10 years; their level of money constraint; education in years; and
how long they had lived in the area where they currently lived. Additional
sociodemographic information included gender, age, household size and income. As a
significant portion of respondents did not report income levels (18.8% indicated
“Don’t know” and 17.9% refused the information) we used a linear regression analysis
to generate fitted values of income for all individuals.
E.9.3.2
Results from “non-economic” portions of the public survey
An important and valuable aspect of the survey work was the information collected on
respondents’ sources, understanding of, preferences for, and uses of weather, water
and climate information. These data were collected in part to develop the context for
the valuation portions of the survey as well as to generate useful data for the NMHS on
the public’s hydrometeorological information process. This portion of the survey
elicited information on respondents’:
–
Experience with weather impacts;
–
Concern with future weather events;
–
Awareness of weather impacts and information;
–
Source of weather information.
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250
200
150
100
50
0
TV
Radio
Friends
Govt.
agency
Non-govt. Newspaper
org.
Internet
Telephone
Figure E.4. Annual frequency of exposure to weather information sources (n = 576)
We cannot present results from this aspect of the work in detail, but provide an
example of the type of information and analysis related to two questions from this
“non-economic” portion of the survey – specifically questions on respondents’ sources
of weather information. We first provided a definition of what weather forecasts are,
including information on water and climate conditions, to clarify the use of
terminology throughout the remainder of the survey. Specifically we indicated that
“Weather forecasts are predictions about future weather, water or climate conditions”.
Only 72 respondents (12.5%) overall indicated that they did not have access to weather
forecasts through any means (such as television, radio, newspapers or friends). As may
be expected, a statistically significantly higher portion did not have access in rural
areas (17.5% in rural areas and 5.4% in urban areas).
We then asked what respondents’ sources were for weather information and the
frequency with which they used a number of potential communication channels (see
Lazo et al. (2009) for results from a similar question asked in the United States). The
question was phrased (“How often do you get, see or use weather forecasts from the
sources listed below?”) to determine all exposure to forecasts and not just how often
they actively seek information. Response options ranged from “Never/rarely” to “Two or
more times a day” for each of eight possible information channels. The responses were
recoded into “times per year” using lower bound values so as to not overstate
frequencies. For instance, “Two or more times a day” was recoded to 730 times per year.
Figure E.4 shows the average annual frequency by source (as recoded from verbal
items indicating frequency). The average total frequency across all sources was slightly
over 600 per year with a median of 365 (or once a day). This strongly suggests that
weather information does play a role in day-to-day decisionmaking for average
Mozambicans.
An analysis of differences between rural and urban areas showed that respondents in
the rural areas accessed weather information approximately 60% more often than
275
APPENDIX E. CASE STUDIES
those in the urban areas in Mozambique (almost 770 times a year in the rural areas
versus 480 in urban Mozambique). Those in rural areas were significantly more likely to
access weather information by television, newspaper, telephone and Internet. We also
examined differences in sources by respondents in the two “zones” (south and northcentral Mozambique), finding that respondents in the south accessed weather
information about 50% more often than those in the upper areas in Mozambique
(almost 700 times a year in the south versus 463 in the rest of Mozambique). Those in
the southern region were significantly more likely to access weather information by
television, and via government and non-government agencies, whereas those in the
north-central region were significantly less likely to access weather information by
newspaper. Finally, a factor analysis on source frequency generated three factors: (a)
“frequent sources” such as radio and television; (b) non-government organizations
and government agencies; and (c) “infrequent sources” such as Internet, newspaper
and telephone.
Table E.12. Attributes and levels for two versions of
the contingent valuation-method question
Current accuracy of
forecasts
Version 1
Version 2
Cyclone warnings and
advisories lead times
Current lead time
2 days
Increase lead time
to 3 days
Increase lead time
to 5 days
All other warnings and
advisories lead times
Current lead time
1 day
Increase lead time
to 2 days
Increase lead time
to 4 days
Geographic detail
Three sections of
country (south,
central, north)
Province level
(10 + Maputo City)
District level
(128 districts)
Time period covered
Currently for
entire day
Information broken Information broken
down between
into 3-hour
night and day
increments
Accuracy of high- and
low-temperature forecasts
1 day generally,
accurate ±2°C
Extend to 2 days
Extend to 5 days
with same accuracy with same accuracy
as current 1 day
as current 1 day
Accuracy of rainfall
information
Correct 75%
of the time
Being correct 80%
of the time
Being correct 90%
of the time
Maritime information
Correct 70%
of the time
Being correct 80%
of the time
Being correct 90%
of the time
Reliability of seasonal
forecasts
Reliable 65%
of the time
Being reliable 70%
of the time
Being reliable 80%
of the time
Accuracy of flooding and
water levels
Correct 70%
of the time
Being correct 80%
of the time
Being correct 90%
of the time
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Table E.13. Frequency of willingness-to-pay responses for two versions of
the payment card (a single response that was entered as an open-ended
verbal response was replaced with the median value of 30 meticais (MT))
V2
MT 15
MT 30
MT 60
MT 120
MT 240
MT 480
MT 720
MT 1 440
MT 2 160
MT 3 240
MT 5 400
MT 9 000
Other
n
V1
MT 0
Version
What is the maximum amount you would be willing to pay each year for this single programme to
improve weather forecasts? Please circle the number below indicating the maximum annual amount
your household would be willing to pay for this programme.
52
56
33
50
36
19
3
0
0
3
0
0
2
14
268
19.4% 20.9% 12.3% 18.7% 13.4% 7.1%
63
73
41
37
39
22
20.5% 23.7% 13.3% 12.0% 12.7% 7.1%
E.9.3.3
1.1% 0.0% 0.0% 1.1% 0.0% 0.0% 0.7% 5.2%
4
2
0
0
1
0
0
26
308
1.3% 0.6% 0.0% 0.0% 0.3% 0.0% 0.0% 8.4%
Results from the payment card contingent valuation question
As noted before we implemented a payment-card CV method using two versions of
the survey with different levels of the attributes for programme improvements. Figure
E.3 shows the payment-card question for version 1 of the survey. Table E.12 shows the
attributes and levels from the two versions of the survey. Table E.13 shows the
frequency distribution of WTP responses for the two versions of the survey as well as
the total number of respondents who saw each version of the survey.
A regression was run on the stated WTP from the payment card to explore issues of
monetary constraints, scenario rejection, and altruistic and bequest values. Table E.14
reports these results. In addition the regression examines other factors influencing
stated WTP such as sociodemographic characteristics of the respondents and
perceptions, uses and sources of weather information. Standardized regression
coefficients are reported that are based on independent variables normalized so that
their standard deviation is one. The reported coefficients thus indicate the relative
influence of the different explanatory variables on the independent variable. The
Pr > |t| column reports the significance level of the parameter estimates. Values below
0.10 (or 10%) suggest that the parameters are significantly related to the stated WTP
and thus have an influence on individuals’ values for the improvements in weather
forecasts. Variance inflation factors are also reported to examine potential colinearity
between the independent variables. As all the variance inflation factors are less than
three we conclude that colinearity is not a problem in this regression.
Urban, more highly educated, and higher-income respondents, those with positive
motivations for improved forecasts (as measured by the variable CVM1_Valid_Positive),
those with greater use values (as measured by the variable CVM2_Benefit_Me), and
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Table E.14. Regression on payment card stated WTP
(n = 576; adjusted R-square = 0.108)
Variable
Standardized
estimate
Pr > |t|
Variance
inflation
factor
Intercept
0.00
0.75
0.00
Urban_Rural_Dummy
0.11
0.02
1.34
Zone_South_Dummy_Vbl
-0.01
0.80
1.44
Sociodemographics
Age
-0.04
0.35
1.04
Education_Continuous
0.13
0.01
1.38
Gender_Male_Dummy_Vbl
0.00
0.95
1.06
Income_Continuous_Final
0.12
0.01
1.35
Monetary_Constraint
-0.01
0.85
1.30
Employed_Dummy
-0.03
0.52
1.12
Married_Dummy_Vbl
0.00
0.94
1.12
HH_Size
0.00
0.90
1.06
Length_of_residency
0.01
0.88
1.11
Forecast satisfaction and uses
PartB_Q18_satis_fcst
0.03
0.46
1.13
PartB_Q10_freq_imm_area
0.00
0.94
1.26
Use_Total_Freq
0.05
0.29
1.47
Sources of forecast information – factor scores
Sources_Factor1_Agencies
-0.09
0.03
1.19
Sources_Factor2_Infrequent_Sourc
0.02
0.72
1.19
Sources_Factor3_Frequent_Sources
-0.01
0.87
1.38
Concern about weather impacts – factor scores
Wx_Concern_Factor1_Lower_Concern
-0.02
0.70
1.23
Wx_Concern_Factor1_Higher_Concer
0.07
0.14
1.25
0.01
1.12
Scenario rejection and response motivations
CVM1_Rejection
-0.11
CVM1_Valid_Positive
0.07
0.10
1.17
CVM1_Factor3
0.02
0.71
1.90
Altruistic and bequest values
CVM2_Benefit_Me
0.11
0.09
2.68
CVM2_Benefit_Family
-0.06
0.38
3.05
CVM2_Benefit_Future_Gen
0.11
0.06
2.28
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those with greater bequest values (as measured by the variable CVM2_Benefit_Future_
Gen) were willing to pay more for improved forecast information (as indicated by the
positive and significant parameter estimates).
As expected, those who didn’t reveal their true WTP due to some form of scenario
rejections (as measured by CVM1_Rejection) stated a lower WTP. Not accounting for
this potential bias would understate the public’s true WTP for weather forecast
improvements.
Interestingly, those who more frequently accessed forecasts provided by public
agencies such as INAM or the Direcção Nacional de Águas (as measured by Sources_
Factor1_Agencies) were willing to pay less for improved forecasts than others. This is a
counter-intuitive result that should be investigated in further depth in future studies.
Using results from the regression analysis we estimated “fitted values” for each
individual for the forecast improvement scenario they evaluated. Table E.15 shows
summary statistics on these fitted values for the two levels of improvement. The mean
and median values for the programmes are very similar (or even a little less for the
programme with the larger improvements) which raises questions of “scope” with
respect to results from this analysis. A “scope test” would normally require a larger
value for the larger forecast improvement. Future analysis will evaluate potential scope
issues in further depth.
E.9.4
Communication of results and outcomes
Preliminary results have been broadly presented in several professional venues
including the American Meteorological Society meetings, the World Weather Open
Science Conference, and the 2014 Weather Economics Association International
meeting. At the time of writing the researchers are in the process of completing the
analysis and reporting on this survey. A completion report will be submitted to the
World Bank and made available to the relevant agencies in Mozambique. A project
report will also be available on the University Corporation for Atmospheric Research
open-access library system (https://opensky.library.ucar.edu/). The information,
including the survey instrument, code books and report will be available to any
interested parties for adaptation of the survey instrument and implementation and
analysis methods to other contexts (for example, in other countries). Following further
analysis, results will also be submitted to peer-reviewed publications for broader
dissemination.
E.9.5
Challenges and limitations
Implementation of this study faced many challenges and limitations typically
associated with less developed countries. Due to the low level of Internet use and
limited phone or mail access, as well as time and resource constraints, the survey was
implemented using a non-random sample. While the researchers feel the final sample
was reasonably diverse and reached some vulnerable populations, it likely cannot be
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APPENDIX E. CASE STUDIES
Table E.15. Summary statistics on predicted maximum willingness to pay by version
Survey version
No. observations
Mean
Std. dev.
Median
CVM version 1
268
2.97
1.26
2.86
CVM version 2
308
2.87
1.27
2.84
generalized to the entire Mozambican population. Regardless of this limitation, the
total value for improved forecasts that could be attributed to the sampled population
is still likely to be significantly more than the World Bank programme cost and thus
would satisfy basic benefit–cost criteria for programme valuation.
Another challenge in implementing the survey was the number of primary languages
spoken in Mozambique. While Portuguese is the official language, a significant portion
of the population speaks one of 43 or more other languages. It was not feasible to
implement the survey in all potential languages and thus some populations may have
been excluded due to language barriers.
With a significant portion of the Mozambican population being subsistence farmers in
rural areas, the research also likely underrepresents that portion of the population in
this analysis. Technically, from a strict benefit–cost perspective, subsistence farmers will
have very low or non-existent WTP due to their severe or total income constraints.
From a broader societal perspective, it is very important to represent their sources,
uses, preferences and needs for weather, water and climate information. More work
could focus on reaching these potentially more vulnerable populations in order to
meet societal goals that transcend the standard benefit–cost economic framework.
REFERENCES
Lazo, J.K. and L. Croneborg, forthcoming: Survey of Mozambique Public on Weather, Water, and
Climate Information. Final report to the World Bank, to be available at https://opensky.library.
ucar.edu/.
Lazo, J.K., R.E. Morss and J.L. Demuth, 2009: 300 billion served: Sources, perceptions, uses and
values of weather forecasts. Bulletin of the American Meteorological Society, 90(6):785–798.
280
E.10
VALUING WEATHER AND CLIMATE:
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CASE STUDY 9: SOCIOECONOMIC EVALUATION OF IMPROVING
MET/HYDRO SERVICES FOR BHUTAN
This summary40 depicts the main features of the subproject Socio-Economic Study on
Improved Hydro-Meteorological Services in the Kingdom of Bhutan, which was part of
a project entitled Strengthening Hydro-Meteorological Services for Bhutan, funded by
the Ministry for Foreign Affairs of Finland. The SEB study was carried out in 2013. The
final approved report was published in February 2014 (Pilli-Sihvola et al., 2014).
The SEB study served three purposes:
(a) To provide a qualitative overview of the potential benefits of improved met/hydro
services to Bhutan’s economic sectors;
(b) To provide feedback to the Bhutanese Department of Hydro-Met Services
(DHMS) on the needs of their current and potential future stakeholders and
services;
(c) To provide an estimate of the costs and, where possible, monetary benefits of the
future services provided by DHMS to the Bhutanese economy and society.
The study covers the effects of climate, weather forecast and early warning services.
The study is forward looking, meaning that the assessed services are not yet provided,
or at least not provided in the way envisaged in the socioeconomic study. Therefore, it
provides an estimate of the net SEBs generated once the observation, data-processing
and forecasting systems are installed and operating, and the consequent new services
are fully available.
Bhutan is expected to be subjected to very significant climate change effects, which
necessitates the development of adequate climate services that can in turn serve
adaptation planning in various sectors. In addition to climate change, Bhutan is subject
to the variability of current weather and to extreme weather and hydrological events.
Furthermore, the most important economic sectors, namely electricity generation with
renewable energy resources (hydro, solar and wind), agriculture and forestry, and
tourism are highly sensitive to weather and climatic conditions. Due to the
combination of the objectives to be served, some service improvements will start to
produce benefits soon after establishment (for example, in case of early warning
services), whereas others will build up over time (notably climate services, which
depend on long observation series).
E.10.1
Overall approach and methods used
The evaluation was carried out over four types of met/hydro services and the benefits
were assessed for 15 sectors/categories. The broad scope was intended to assess the
macroeconomic sensibility of an overall upgrade of the met/hydro services in Bhutan
40
Summary made by Adriaan Perrels and Karoliina Pilli-Sihvola (both of FMI).
APPENDIX E. CASE STUDIES
281
and not intended to assess particular investments in great detail. As a consequence,
many parts of the study have the character of a so-called “quick scan”. For pragmatic
reasons, such as limitations on availability and quality of data, various methods have
been used in parallel.
A key distinction in the study is how the deployment of the evaluated services is
expected to develop, since the deployment largely steers how generated SEBs develop
over time. This feature also illustrates how the purpose of a study steers the structuring
of the analysis – not unlike the industrial design adage “form follows function”.
Based on the eleventh five year plan of DHMS, four service categories were identified
for socioeconomic evaluation:
(a) Compilation and distribution of information on past weather and hydrological
conditions – that is, basic services based on historical data, notably observations;
(b) Provision of information on the current state of rivers (water level), flood
information and atmospheric conditions – that is, hydrological and
meteorological monitoring services;
(c) Provision of forecasts, notably general forecasts for the community at large and
specialized forecasts for a range of users – three-days-ahead weather forecasts,
seasonal precipitation forecasts and flood forecasts;
(d) Generating warnings about severe weather, climate or hydrological conditions for
the community at large and specialized warnings for a range of users.
The socioeconomic effects were evaluated for renewable energy, agriculture,
construction of buildings and infrastructure, disaster management, road transport and
road maintenance, public health and civil aviation sectors. For each sector, the study
assesses how the four envisaged services could affect operations (services in points (b),
(c) and (d)) and investments (point (a)). Benefits are generated both by avoiding
damage (to crops, infrastructure, and the like) and by better exploiting opportunities
(for example, optimal sizing and location of hydro, wind and solar power units, and
optimized crop choice). Potential benefit estimates are based upon simple cost–loss
analysis (for example, applying changes in damage probability owing to the use of
forecasting information) or by estimating changes in productivity associated with
forecast use (for example, changes in average annual energy production due to
optimized sizing and location choice based on climatic and current observation data).
For each service and sector, the benefits have been further qualitatively assessed
through the filtering steps of the weather service chain approach (Nurmi et al., 2013)
emphasizing the need to give attention to the rest of the value chain, beyond
information generation.
Information sources comprised: (a) statistics (climatic, economic sectors),
(b) interviews (adding in-depth sector information) and (c) two workshops (for initial
indications of the significance of the envisaged services and impacts and feedback for
initial results). The benefit estimates are often based on benefit transfer (results or
282
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
modelling parameters taken from other studies). In some cases, lower and higher
estimates are produced, for example, in relation to the expected growth of a sector
(such as hydropower production). Because an explicit formalized accounting for
uncertainties is often difficult due to scarcity of data, a general principle of caution is
applied, meaning that conservative figures are used for representing changes in service
quality and uptake of services by users.
The benefit assessments do account for economic and/or population growth
developments in various sectors, but indirect and induced economic (that is,
macroeconomic) effects are not taken into account. For example, higher productivity
in various sectors is assumed not to affect product prices in these sectors. It is also
assumed that only DHMS will provide the considered services in Bhutan, which in this
case is a fair assumption.
Next to an estimate of generated benefits, the costs required to improve the level of
services were considered. Included are:
(a)
The installation and maintenance of a lightning location system;
(b)
A ceilometer for Paro international airport;
(c)
Upper air sounding – acquisition and maintenance;
(d)
Data management capacity (including staffing);
(e)
Observation station maintenance and calibration;
(f)
Staffing and equipment for expanding the forecasting services.
The various investments considered, including extra staffing needed, were planned to
be implemented in the first few years of the considered evaluation periods.
For items in points (a), (d), (e) and (f), a gradual build-up is assumed in the study, with
space for learning and stepwise upgrading to more sophisticated systems (such as in
case of a lightning location system) and sufficient attention for maintenance and
adequate staffing.
E.10.2
Results
With regard to the benefits of current observations, only the aviation sector appeared
to be a significant user of such data. Other user groups may become interested if
observation data, of appropriate resolution and in relevant areas, become available.
Considering the investment and development orientation of the study, the
quantification efforts concentrated on the other three service categories, these being
large-scale hydro, tourism and road transportation. Table E.16 shows the benefits of
historical met/hydro information and Table E.17 the benefits of forecast services.
Furthermore, given the varied quality of the available information, the results are in
283
APPENDIX E. CASE STUDIES
the first place presented by means of a cardinal rating method, indicating one to five
plus (+) signs, depending on the estimated significance of the benefit. The
preliminary results presented in this way were discussed with stakeholders and other
experts in a workshop in Bhutan. For some of the sectors more precise monetized
effects are indicated.
Table E.16. Benefits of historical met/hydro information (basic climate services)
Current network;
quality-controlled data;
benefits for 2015–2030
Extended network,
2015–2030
Small-scale
energy
production
Improved design of
small-scale hydropower
plants
+
Improved design of
small-scale hydropower
plants
+
Improved design
of wind, solar and
hydropower plants
++++
Large-scale
hydropower
Improved design of
hydropower plants
++
Improved design of
hydropower plants
++
Estimated yearly value
Nu 67 million (about
€ 790 000) per plant
+++++
Agriculture
Long-term planning
of most suitable crops,
weather index-based
insurance scheme
++
Long-term planning
of most suitable crops,
weather index-based
insurance scheme
+++
Long-term planning
of most suitable crops,
weather index-based
insurance scheme
+++++
Tourism
Marketing to increase
the number of tourists,
especially during lean
seasons
++
Marketing to increase
the number of tourists,
especially during lean
seasons
++
Estimated yearly value
approximately
US$ 1.4 million
(starting 2020)
++++
Disaster risk
reduction
Hazard mapping,
land use and spatial
planning
+++
Hazard mapping,
land use and spatial
planning
++++
Hazard mapping,
land use and spatial
planning
+++++
Public health
Forecasting and
assessment of
outbreaks
++
Forecasting and
assessment of
outbreaks
++
Forecasting and
assessment of
outbreaks
+++
Water resource
management
National water resource Management of water
inventory
resources
+++
+++
Management of water
resources
++++
Climate change
Climate change
monitoring
+++
Climate change
monitoring
++++
Sector
Climate change
monitoring
+++
Extended network;
2020/2025–2030
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VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
Table E.17. Benefits of forecast services
72-hour forecast –
3-hour time resolution;
2015/2020–2030
Sector
Seasonal forecasts;
2015–2030
Small-scale
energy
production
Production estimations
Consumption and production
estimations, secure electricity supply +
(starting 2020), aid in operation
++
Large-scale
hydropower
Production estimation, improved
operation and maintenance,
yearly value Nu 65.8 million
(approximately € 771 445)
++
Electricity
distribution
Prepare for damage, inform
customers
++
Agriculture
Improved farming practice
++++
Adaptation to yearly variation in
rainfall patterns
+++++
Tourism
Expand tourism to areas currently
without forecast; nice-to-know
information
+
Increase the number of tourists,
improved planning and
preparedness
+
Aviation
Benefits from nowcasts
+++
Public health
Benefits from warnings on extreme
temperatures, heatwaves and cold
waves
++
Road
transportation
Prepare for road blocks and mobilize Improved planning and
preparedness
the workforce earlier, inform the
+
public
++
Natural resource
use
Optimize operations in the stone
quarries and forests
++
E.10.3
Production estimations
+
Prepare for outbreaks, inform the
public
++
Optimize operations in the stone
quarries and forests
++
Benefits of early warning services
The high uncertainties regarding benefits of early warning services made numerical
assessment at this stage less meaningful. Furthermore, the evolving effectiveness and
specificity of the forecast services will affect the value generation capacity of the
285
APPENDIX E. CASE STUDIES
warning services. Also, efforts further down the value chain, aimed at actually reaching
users with timely and understandable messages, are essential for significant benefit
generation. It is, however, obvious that the benefits potential is very large as soon as
various parts of the value chain have sufficiently improved in quality. Benefit–cost
ratios easily surpass 10 under such conditions (Perrels et al., 2013).
The report also presents an overall assessment of the development of (quantifiable)
benefits and costs for the period 2015–2030. A summary is shown in Figure E.5. The
benefit–cost ratio based on the NPV of these monetized flows (see section 8.3.1) is
approximately 3.1 when considering the high initial costs of modernizing DHMS.
Excluding the initial costs increases the NPV BCR to 5.5. The yearly benefit ratio
increases substantially in 2025, up to 8–9, when the benefits of the historical data start
to accrue.
The preliminary results of the assessment were presented to the stakeholders of DHMS
at the second workshop held in Thimphu in January 2014. The final report has been
shared with all government ministries in Bhutan to inform other sectors of the value of
met/hydro services in the country. However, it is challenging to estimate the long-term
value of the study as it usually takes a long time for the benefits to accrue.
The SEB study has functioned as an effective underpinning for the need for service
development and related investments in up-to-date observation, data-processing and
forecasting capacity. It has also helped priority-setting and awareness-raising among
potential end users due to the two stakeholder workshops and particularly due to the
extensive stakeholder interviews organized during the study.
Producing a full-blown BCA would require substantial data from different sectors,
which were not available for the study, and sectorial and macroeconomic modelling
efforts, which were not possible due to the limitations of the study. Indeed, for a
relatively young met/hydro service, a quick scan of the costs and benefits of improved
Million euros
6
5
4
MONETARY BENEFIT
3
TOTAL COST
2
1
0
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
Figure E.5. Annual quantifiable direct benefits and costs of improved weather,
hydrological and climate services in Bhutan
Source: Pilli-Sihvola et al. (2014)
286
VALUING WEATHER AND CLIMATE:
ECONOMIC ASSESSMENT OF METEOROLOGICAL AND HYDROLOGICAL SERVICES
services, such as undertaken in this study, provides a good starting point for future
service improvements and the development of interactions with potential stakeholder
and user groups. The workshops and interviews in Bhutan were highly successful, as
they increased the visibility of the NHMS among key future stakeholders.
The study includes two recommendations regarding SEB studies:
(a) DHMS should regularly involve stakeholders in the service development process
and also develop systematic interaction with stakeholders to ensure regular
feedback on service quality and indications for future service development;
(b) DHMS is advised to conduct a follow-up economic valuation in 2020, to learn,
inter alia, to what extent outcomes deviate from projections and why.
It is planned by DHMS to update and expand this study in order to sustain government
and partner support in advancing the service system to provide greater relevance and
utility for Bhutanese society.
The socioeconomic benefits associated with met/hydro services are highly context and
location dependent. Therefore, if the study is done by an external, foreign consultant,
the researcher(s) need to obtain a good understanding of the societal, economic and
cultural context of the country as they determine how information is used and where it
creates value. However, the benefits of a foreign consultant arise from the better
objectivity of the results of the study. Therefore, each study needs to be designed for
the context. In developing countries, where the data on economic societal and
performance factors are often scarce, producing a thorough qualitative analysis can
also serve the purpose of demonstrating the benefits to society. A well-done qualitative
analysis is often better than a poor, highly uncertain quantitative analysis. Therefore,
the context and location often determines the method used to conduct the SEB study
as well. The described SEB study in Bhutan was mostly an interview-based qualitative
study as there was data scarcity and uncertainty regarding the future development of
the society; for instance in the agricultural sector. However, for policymakers,
quantitative monetary results are usually of more value. Therefore, studies should
strive to include elements of both.
REFERENCES
Nurmi, P., A. Perrels and V. Nurmi, 2013: Expected impacts and value of improvements in
weather forecasting on the road transport sector. Meteorological Applications, 20:217–223.
Perrels, A., T. Frei, F. Espejo, L. Jamin and A. Thomalla, 2013: Socio-economic benefits of weather
and climate services in Europe. Advances in Science and Research, 1:1–6.
Pilli-Sihvola, K., P. Namgyal and C. Dorji, 2014: Socio-Economic Study on Improved HydroMeteorological Services in the Kingdom of Bhutan. Report prepared for the Strengthening
Hydro-Meteorological Services for Bhutan (SHSB) project. Bhutan, Finnish Meteorological
Institute and Department of Hydro-Met Services.
For more information, please contact:
World Meteorological Organization
7 bis, avenue de la Paix – P.O. Box 2300 – CH 1211 Geneva 2 – Switzerland
Communications and Public Affairs Office
E-mail: [email protected]
www.wmo.int
JN 15388
Tel.: +41 (0) 22 730 83 14/15 – Fax: +41 (0) 22 730 80 27
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