Mah2008a

Mah2008a
Atmos. Chem. Phys., 8, 6199–6221, 2008
www.atmos-chem-phys.net/8/6199/2008/
© Author(s) 2008. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmospheric
Chemistry
and Physics
Validation of ACE-FTS v2.2 measurements of HCl, HF, CCl3F and
CCl2F2 using space-, balloon- and ground-based instrument
observations
E. Mahieu1 , P. Duchatelet1 , P. Demoulin1 , K. A. Walker2,3 , E. Dupuy3 , L. Froidevaux4 , C. Randall5 , V. Catoire6 ,
K. Strong2 , C. D. Boone3 , P. F. Bernath7 , J.-F. Blavier4 , T. Blumenstock8 , M. Coffey9 , M. De Mazière10 , D. Griffith11 ,
J. Hannigan9 , F. Hase8 , N. Jones11 , K. W. Jucks12 , A. Kagawa13 , Y. Kasai13 , Y. Mebarki6 , S. Mikuteit8 , R. Nassar14 ,
J. Notholt15 , C. P. Rinsland16 , C. Robert6 , O. Schrems17 , C. Senten10 , D. Smale18 , J. Taylor2 , C. Tétard19 , G. C. Toon4 ,
T. Warneke15 , S. W. Wood18 , R. Zander1 , and C. Servais1
1 Groupe
Infra-Rouge de Physique Atmosphérique et Solaire (GIRPAS), Institute of Astrophysics and Geophysics,
University of Liège, Liège, Belgium
2 Department of Physics, University of Toronto, 60 St. George Street, Toronto, Ontario, M5S 1A7, Canada
3 Department of Chemistry, University of Waterloo, 200 University Avenue West, Waterloo, Ontario, N2L 3G1, Canada
4 Jet Propulsion Laboratory, California Institute of Technology , Pasadena, CA, USA
5 University of Colorado, CO, USA
6 Lab. de Physique et Chimie de l’Environnement, CNRS – Univ. d’Orléans (UMR 6115), 45071 Orléans Cedex 2, France
7 Department of Chemistry, University of York, Heslington, York, YO10 5DD, UK
8 Institute for Meterorology and Climate Research (IMK), Forschungszentrum Karlsruhe and University of Karlsruhe,
Karlsruhe, Germany
9 National Center for Atmospheric Research, CO, USA
10 Belgian Institute for Space Aeronomy, Brussels, Belgium
11 University of Wollongong, Australia
12 Harvard-Smithsonian Center for Astrophysics, Cambridge, MA, USA
13 National Institute of Communications and Information Technology, 4-2-1 Nukui-kita, Koganei, Tokyo 184-8795, Japan
14 Harvard University, Cambridge, MA, USA
15 Institute of Environmental Physics, University of Bremen, Germany
16 Langley Research Center, VA, USA
17 Alfred Wegener Insitute for Polar and Marine Research, Bremerhaven, Germany
18 National Institute of Water and Atmospheric Research Ltd, Lauder,Central Otago, New Zealand
19 Laboratoire d’Optique Atmosphérique, Université des sciences et technologies de Lille (UMR 8518),
59655 Villeneuve d’Ascq, France
Received: 4 December 2007 – Published in Atmos. Chem. Phys. Discuss.: 18 February 2008
Revised: 30 June 2008 – Accepted: 9 September 2008 – Published: 27 October 2008
Abstract. Hydrogen chloride (HCl) and hydrogen fluoride
(HF) are respectively the main chlorine and fluorine reservoirs in the Earth’s stratosphere. Their buildup resulted from
the intensive use of man-made halogenated source gases,
in particular CFC-11 (CCl3 F) and CFC-12 (CCl2 F2 ), during the second half of the 20th century. It is important to
Correspondence to: E. Mahieu
(emmanuel.mahieu@ulg.ac.be)
continue monitoring the evolution of these source gases and
reservoirs, in support of the Montreal Protocol and also indirectly of the Kyoto Protocol. The Atmospheric Chemistry
Experiment Fourier Transform Spectrometer (ACE-FTS) is a
space-based instrument that has been performing regular solar occultation measurements of over 30 atmospheric gases
since early 2004. In this validation paper, the HCl, HF, CFC11 and CFC-12 version 2.2 profile data products retrieved
from ACE-FTS measurements are evaluated. Volume mixing
Published by Copernicus Publications on behalf of the European Geosciences Union.
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E. Mahieu et al.: Validation of HCl, HF, CCl3 F and CCl2 F2 from ACE-FTS
ratio profiles have been compared to observations made from
space by MLS and HALOE, and from stratospheric balloons
by SPIRALE, FIRS-2 and Mark-IV. Partial columns derived
from the ACE-FTS data were also compared to column measurements from ground-based Fourier transform instruments
operated at 12 sites. ACE-FTS data recorded from March
2004 to August 2007 have been used for the comparisons.
These data are representative of a variety of atmospheric and
chemical situations, with sounded air masses extending from
the winter vortex to summer sub-tropical conditions. Typically, the ACE-FTS products are available in the 10–50 km
altitude range for HCl and HF, and in the 7–20 and 7–25 km
ranges for CFC-11 and -12, respectively. For both reservoirs,
comparison results indicate an agreement generally better
than 5–10% above 20 km altitude, when accounting for the
known offset affecting HALOE measurements of HCl and
HF. Larger positive differences are however found for comparisons with single profiles from FIRS-2 and SPIRALE. For
CFCs, the few coincident measurements available suggest
that the differences probably remain within ±20%.
1
Introduction
Under unperturbed atmospheric conditions, hydrogen chloride (HCl) and hydrogen fluoride (HF) are the two most
abundant halogenated species of the inorganic chlorine and
fluorine families (respectively denoted Cly and Fy ; see e.g.
Prinn et al. (1999)) in the stratosphere. Since the 1970s, their
atmospheric concentrations have significantly increased, followed by a recent slowing down in their accumulation, and
even a decrease for HCl (Mahieu et al., 2004; Froidevaux et
al., 2006b). Indeed, the respective HCl and HF mean upper stratospheric concentrations have risen from 2500 and
760 pptv in the mid-1980s to 3800 and 1800 pptv in the first
years of the new millennium (e.g., Zander et al., 1992; Gunson et al., 1994; Nassar et al., 2006a, b). These increases are
due to the extensive use of man-made chlorofluorocarbons
(CFCs), further augmented, and then replaced, with substitutes such as hydrochlorofluorocarbons (HCFCs). Among
these source gases, the main contributors are CCl2 F2 (CFC12) and CCl3 F (CFC-11), with current mean tropospheric
concentrations of 540 and 250 pptv, respectively (WMO Report Nr. 50, 2007). Transport of these long-lived compounds
to the stratosphere leads to their photodissociation, with release of chlorine and fluorine atoms (e.g., Kaye et al., 1991).
Rapid recombination of these atoms with hydrogenated compounds (e.g., CH4 , H2 ) respectively produces HCl and HF,
the two reservoir species of interest here. However, before the formation of HCl, Cl can be involved in the ClOx
catalytic cycle which contributes to ozone depletion (e.g.,
Molina and Rowland, 1974).
HF is a remarkably stable species in the stratosphere (e.g.,
Stolarski and Rundel, 1975), making it an ideal tracer of
Atmos. Chem. Phys., 8, 6199–6221, 2008
transport and dynamics in this atmospheric region (Chipperfield et al., 1997). Conversely, HCl can be activated under
specific conditions occurring mainly in the stratospheric polar atmosphere and in wintertime, with the production of active chlorine species (e.g., ClO) which are able to destroy
ozone. This reactivation occurs through various heterogeneous reactions taking place on Polar Stratospheric Clouds
(PSCs), at temperatures below 200 K (e.g. Solomon et al.,
1999; WMO Report Nr. 50, 2007, and references therein).
Even before the unambiguous confirmation of the significant role of anthropogenic chlorine in the destruction of the
Earth’s protective ozone layer, monitoring networks such as
the AGAGE (Advanced Global Atmospheric Gases Experiment) and NOAA/ESRL (National Oceanic and Atmospheric
Administration – Earth System Research Laboratory) have
been measuring increases in a large number of source gases,
including all major long-lived CFCs and HCFCs, by in situ
surface sampling (e.g., O’Doherty et al., 2004; Montzka et
al., 1999, and references therein). These increasing tropospheric loadings were at the heart of the alarming threat to
ozone suggested by Molina and Rowland (1974). This theory
was soon supported by the first detections in the stratosphere
of HF (Zander et al., 1975), of HCl (Farmer et al., 1976; Ackerman et al., 1976), and of CFC-11 and -12 (Murcray et al.,
1975).
The ATMOS (Atmospheric Trace MOlecule Spectroscopy, http://remus.jpl.nasa.gov/atmos) Fourier Transform InfraRed (FTIR) instrument was one of the pioneering space-based experiments that measured the vertical distributions of nearly 30 atmospheric gases, during four shuttle flights that took place from 1985 to 1994 (Gunson et
al., 1996). Among the many results of ATMOS, chlorine
and fluorine budgets were evaluated using Northern latitude measurements of halogenated sources and reservoirs,
supplemented by balloon and model data for a few missing species (Raper et al., 1987; Zander et al., 1987, 1992
and 1996). HALOE (HALogen Occultation Experiment;
Russell et al. (1993)) has contributed over the longer term,
recording regular, global occultation measurements of HCl
and HF between September 1991 and November 2005. The
HALOE data set has been used to derive the first global distributions and decadal trends of HCl and HF from space
(e.g., Anderson et al., 2000; WMO Report Nr. 50, 2007).
These stratospheric species have also been remotely monitored from the ground, using FTIRs. Data sets now spanning more than 30 years are available from the Jungfraujoch station, allowing long-term trends in HCl and HF to
be characterized (e.g., Rinsland et al., 2002; Mahieu et al.,
2004; WMO Report Nr. 50, 2007). Other sites equipped
with FTIRs and affiliated with the Network for the Detection
of Atmospheric Composition Change (NDACC, previously
NDSC, http://www.ndacc.org), have also contributed to this
effort. Observations from nine sites spread from Northern
high- to Southern mid-latitudes have detected the leveling-off
of HCl, which peaked around the mid-1990s (Rinsland et al.,
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E. Mahieu et al.: Validation of HCl, HF, CCl3 F and CCl2 F2 from ACE-FTS
2003). In parallel, experiments using balloon-borne instruments, often focusing on polar vortex chemistry in the low
stratosphere, have provided complementary information for
both the source and reservoir species (e.g., Sen et al., 1998).
Among the space-borne instruments currently performing observations of these species, MLS (Microwave Limb
Sounder) onboard Aura has collected HCl data over the
last three years and is still in operation (Froidevaux et
al., 2006b). ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer), onboard the Canadian SCISAT satellite, is also still fully operational after
more than four years in space and is the only instrument
presently in orbit which measures HF. Previous work using
ACE-FTS observations has included studies of the global inventories and partitioning of stratospheric chlorine and fluorine, using the version 2.2 (v2.2) data set (Nassar et al.,
2006a, b).
Although the HCl and HF version 1.0 (v1.0) data products were targets of initial comparisons (e.g., McHugh et al.,
2005; Mahieu et al., 2005), the more extensive v2.2 database
still requires validation. Therefore, the present study aims at
investigating the consistency and reliability of the ACE v2.2
HCl, HF, CFC-11 and -12 level 2 products, prior to their official release to the scientific community. For this purpose,
the present manuscript has been organized into several sections. Section 2 briefly describes the ACE-FTS instrument
and measurements, as well as the strategy adopted in the retrieval processes. Section 3 gives an overview of the correlative data sets and instruments involved, as well as details on selected data filtering and collocation criteria. Section 4 deals with intercomparison results, on a per-molecule
and per-instrument basis. Finally, conclusions are given in
Sect. 5.
2
The ACE-FTS measurements of HCl, HF, CFC-11
and -12
The ACE-FTS instrument was launched onboard the SCISAT
satellite on 12 August 2003. A low altitude (650 km) high
inclination (74◦ ) circular orbit was selected in order to allow for coverage of polar to tropical regions, in agreement
with the mission’s objectives (Bernath et al., 2005). The platform also carries a spectrophotometer (MAESTRO – Measurement of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation, (McElroy et al., 2007))
as well as two filtered solar imagers (ACE-imagers, Gilbert
at al., 2007). The ACE-FTS instrument achieves a maximum
spectral resolution of 0.02 cm−1 in the broad 750–4400 cm−1
spectral interval (2.2 to 13 micrometers). The initial requirement for the S/N of the instrument was 100 over the whole
spectral range. Over most of the interval, this has been exceeded by a factor 2 to 3 (Châteauneuf et al., 2004). Since the
beginning of routine operations on 21 February 2004, this instrument has recorded up to 15 sunrise (sr) and sunset (ss) ocwww.atmos-chem-phys.net/8/6199/2008/
6201
cultations per day (about every 90 min); successive infrared
(IR) solar spectra are collected from 150 km altitude down
to the cloud tops, with a vertical resolution of about 3–4 km,
corresponding to 1.25 mrad field of view of ACE-FTS. As a
result of the 2 s needed to record an interferogram and of the
orbital beta angle, the vertical spacing of the measurements
varies between 1.5 and 6 km (without including the effects of
atmospheric refraction).
Analyses of ACE-FTS spectra (level 1 data) are performed
at the University of Waterloo (Ontario, Canada). The algorithm is thoroughly described by Boone et al. (2005). In a
first step, temperature and pressure are retrieved using CO2
spectral lines, assuming a realistic profile. Subsequent retrievals of target species combine the information from several microwindows that are carefully selected to minimize
the impact of interfering gases in the altitude range of interest, i.e., generally from the lower mesosphere to the upper troposphere. Inversion of a series of successive spectra
recorded during a solar occultation event produces volume
mixing ratio (vmr) profiles of the target gases, on the measured altitude grid. These profiles are also interpolated onto a
standard altitude grid, consisting of 150 levels of 1 km thickness, which are considered to be homogeneous in terms of
pressure, temperature and vmr of the various gases.
While profiles of more than 30 species are now retrieved from the ACE-FTS measurements, a group of primary (“baseline”) data products have been selected by the
ACE Science Team as the focus of this validation exercise.
These include O3 , CH4 , H2 O, NO, NO2 , ClONO2 , HNO3 ,
N2 O, N2 O5 , HCl, CCl3 F, CCl2 F2 , HF, CO, aerosols, temperature and pressure.
ACE-FTS retrievals considered here have been performed
using the standard edition of the HITRAN-2004 line parameter and cross section compilation (Rothman et al., 2005).
The microwindows used in the HCl, HF, CFC-11 and CFC12 retrievals are listed in Table 1, together with the main interfering species and the altitude range in which each microwindow is used. Several spectral intervals encompassing
discrete lines are simultaneously used to retrieve HCl and HF
vmrs.
For CFCs, broad spectral features are used to retrieve their
vertical distributions, typically between the tangent height of
10 and 25 km.
Version 2.2 retrievals are identical to v1.0 settings, except
for HCl. In the new approach, microwindows encompassing absorption lines of the H37 Cl isotopologue have been included, 22 spectral intervals are used instead of the 13 used
previously. It should be noted that, to date, no formal complete error budget has been produced for the ACE-FTS v2.2
retrievals.
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Table 1. Microwindows used for the ACE-FTS retrievals of HCl,
HF, CFC-11 and -12.
Central Freq
(cm−1 )
Width
(cm−1 )
Alt.Range
(km)
Remarks
0.3
0.3
0.4
0.3
0.3
0.35
0.3
0.3
0.4
0.3
0.26
0.3
0.5
0.3
0.3
0.4
0.3
0.4
0.5
0.5
0.3
0.3
8–36
35–47
8–45
47–55
40–55
51–57
20–54
18–57
20–50
15–57
38–57
45–57
20–48
44–50
17–57
15–54
10–57
25–48
8–57
40–57
45–51
52–57
Interfering molecules for HCl
windows: O3 below 40 km
CH4 below 50 km
0.3
0.3
0.3
0.35
0.3
0.4
0.4
0.35
0.3
0.3
0.45
0.35
0.4
25–35
10–30
10–25
10–23
10–25
10–44
18–48
10–50
27–50
10–50
10–50
25–46
15–40
Interfering molecules
for HF windows:
H2 O below 30 km
O3 below 35 km
N2 O below 25 km
CH4 below 23 km
3
Correlative data sets
In the following sub-sections, all instruments and corresponding measurements will be briefly described; specific
methodology for comparison, if any, as well as the criteria
used for selecting the coincidences will also be provided.
HCl
2701.26
2703.03
2727.77
2751.97
2775.75
2798.95
2819.48
2821.47
2841.63
2843.67
2865.16
2906.30
2923.57
2923.73
2925.90
2942.67
2944.95
2961.00
2963.11
2981.00
2995.88
2998.14
HF
1815.78a
1987.34b
2010.70a
2667.47c
2814.40d
3788.33
3833.71
3877.75
3920.39
4001.03
4038.87
4109.94
4142.97
a Included to improve results for interferer O
3
b Included to improve results for interferer H O
2
c Included to improve results for interferer CH
4
d Included to improve results for interferer N O
2
CCl3 F (CFC-11)
842.50
25
5–22
CO2 below 22 km
HNO3 below 22 km
H2 O below 22 km
O3 below 22 km
CCl2 F2 (CFC-12)
922
1161
4
1.2
6–28
12–25
O3 below 25 km
N2 O below 25 km
Atmos. Chem. Phys., 8, 6199–6221, 2008
3.1 MLS v2.2 measurements of HCl
Continuous (day and night) global measurements of HCl
have been provided since August 2004 by MLS onboard the
Aura satellite. MLS measures thermal emission lines from
trace gases at millimeter and sub-millimeter wavelengths, as
discussed by Waters et al. (2006). Validation of the MLS
HCl version 2.2 (v2.2) data has been described recently by
Froidevaux et al. (2008). This data version has been used
since March 2007. The reprocessing of the MLS data is still
ongoing. The single profile precision of MLS HCl is 0.5 ppbv
or less in the stratosphere, and the HCl accuracy estimate is
about 0.2 ppbv. The recommended altitude range for MLS
HCl profiles is from 100 to 0.15 hPa; the data can be used
down to 150 hPa at high latitudes, although a high MLS bias
is observed at low to mid-latitudes versus aircraft in situ data
at this pressure level (Froidevaux et al., 2008). More details
regarding the MLS experiment and the HCl data screening
are provided in the above references; per these references,
we follow the MLS flags that screen out a small percentage
of profiles with bad “Status”, and poor “Quality” (from radiance fits) or “Convergence” (retrieval issue). In this work, the
comparisons of coincident profiles between MLS and ACEFTS include 4731 ACE-FTS occultations between 84◦ N and
84◦ S latitude. The number of MLS v2.2 reprocessed days
available at the time of writing for 2004, 2005, and 2006
were 28, 179 and 154, respectively. For 2007, the comparisons include data from MLS and ACE-FTS until the end
of August, although no MLS HCl data were obtained from
15 July through 9 August, due to a temporary instrument
anomaly. The coincidence criteria used here are the same
as those used in the analyses by Froidevaux et al. (2008).
For each ACE-FTS profile, the closest MLS profile (on the
same day) within ±2 degrees of latitude and ±8 degrees of
longitude is selected. The ACE-FTS profiles are interpolated
(linearly versus log of pressure) onto the MLS retrieval grid,
using the retrieved pressures from the ACE-FTS data.
3.2
HALOE v19 measurements of HCl and HF
The HALOE instrument was in operation onboard the UARS
platform (Upper Atmospheric Research Satellite; Reber et
al. (1993)) for 14 years, from September 1991 to November 2005, when the mission was ended. Therefore, it operated throughout most of the first two years of the ACE mission operations phase. Given the UARS orbital inclination of
57◦ and the satellite altitude (close to 600 km), HALOE was
able to sample the Earth’s atmosphere almost globally (from
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E. Mahieu et al.: Validation of HCl, HF, CCl3 F and CCl2 F2 from ACE-FTS
about 80◦ N to 80◦ S), in solar occultation mode, from the
lower mesosphere to the upper troposphere. Eight IR channels allow the measurements of several trace gases (e.g., O3 ,
CH4 , H2 O) with a vertical resolution of ∼2 km. HCl and HF
vertical distributions are among the available data products.
Earlier version 17 (v17) HALOE HCl data were found to
agree with correlative measurements to within about 10–20%
in the stratosphere, with a possible low bias (Russell et al.,
1996a). Comparisons between version 19 (v19) HALOE and
v1.0 ACE-FTS data were described by McHugh et al. (2005),
who found that ACE-FTS HCl was within ±10% of HALOE
below 20 km, and 10–20% higher than HALOE from 20 to
48 km. In a recent paper, Lary et al. (2007) have compared
several space-based measurements of HCl, by ACE-FTS, ATMOS, HALOE and MLS, obtained between 1991 and 2006,
using a neural network. They further confirmed the low bias
of HALOE with respect to all other instruments.
For HF, v17 HALOE data were found to agree with correlative balloon measurements to better than 7% from 5 to
50 hPa (i.e., between about 20 and 35 km) (Russell et al.,
1996b), but had a similar 10–20% low bias with respect to
ATMOS as was observed for HCl (Russell et al., 1996a).
Comparisons between v19 HALOE and v1.0 ACE-FTS data
were also performed by McHugh et al. (2005), who found
that ACE-FTS HF was about 10–20% higher than HALOE
from 15 to 45 km.
The latest version (v19; available from e.g. http://badc.
nerc.ac.uk/data/haloe) data release has been used in the
present statistical analyses, for both HCl and HF.
The HALOE and ACE-FTS data sets were searched for coincident profile measurements, defined as occurring within 2
hours in time and 500 km in geographic distance. A total of
36 coincidences were found; 5 corresponding to sunrise occultations and 31 to sunset occultations. Relaxing the time
criterion to one day did not result in any new coincidences.
Twenty nine coincidences occurred from 4 to 10 July 2004
(average latitude 66◦ N) and two on 15 August 2005 (average latitude 49◦ S); the five sunrise coincidences occurred on
6 and 7 September 2004 (5 coincidences, average latitude
60◦ N). Thus most of the comparisons correspond to polar
summer conditions in the Northern Hemisphere.
3.3
SPIRALE measurements of HCl
SPIRALE (SPectroscopie Infra-Rouge d’Absorption par
Lasers Embarqués) is a balloon-borne instrument operated by LPCE (Laboratoire de Physique et de Chimie de
l’Environnement, CNRS – Université d’Orléans) and routinely used at all latitudes, in particular as part of European validation campaigns for the Odin and Envisat missions. This six tunable diode laser absorption spectrometer
(TDLAS) has been previously described in detail (Moreau et
al., 2005). In brief, it can perform simultaneous in situ measurements of about ten chemical species from about 10 to
35 km height, with a high frequency sampling (∼1 Hz), thus
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enabling a vertical resolution of a few meters depending on
the ascent rate of the balloon. The diode lasers emit in the
mid-infrared domain (from 3 to 8 µm) with beams injected
into a multipass Herriott cell located under the gondola and
exposed to ambient air. The cell (3.5 m long) is deployed
during the ascent when pressure is lower than 300 hPa. The
multiple reflections obtained between the two cell mirrors
give a total optical path of 430.78 m. Species concentrations are retrieved from direct infrared absorption, by adjusting synthetic spectra calculated using the HITRAN 2004
database (Rothman et al., 2005) to match the observation.
Specifically, the ro-vibrational line at 2925.8967 cm−1 was
used for HCl. Measurements of pressure (from two calibrated and temperature-regulated capacitance manometers)
and temperature (from two probes made of resistive platinum
wire) aboard the gondola allow the species concentrations to
be converted to vmrs.
Uncertainties in these pressure and temperature parameters have been evaluated to be negligible relative to the other
uncertainties discussed below. The global uncertainties on
the vmrs have been assessed by taking into account the random errors and the systematic errors, and combining them
as the square root of their quadratic sum. The two important sources of random error are the fluctuations of the laser
background emission signal and the signal-to-noise ratio. At
lower altitudes (below 16 km), these are the main contributions. Systematic errors originate essentially from the laser
line width (an intrinsic characteristic of the diode laser),
which contributes more at lower pressure (higher altitudes)
than at higher pressures. The impact of the spectroscopic parameter uncertainties (essentially the molecular line strength
and pressure broadening coefficients) on the vmr retrievals is
almost negligible. After quadratic combination, the random
and systematic errors result in total uncertainties of 20% below 16 km altitude, decreasing to 13% at 23 km and to a constant value of 7% above 23 km.
The SPIRALE measurements occurred on 20 January
2006 between 17:36 UT and 19:47 UT. An HCl vertical profile was obtained during ascent, between 11.3 and 27.3 km
height. The measurement position remained rather constant
with a mean location of the balloon at (67.6±0.2)◦ N and
(21.55±0.20)◦ E. The comparison is made with the ACEFTS sunrise occultation (sr13151) that occurred 13 h later (on
21 January 2006 at 08:00 UT) and was located at 64.28◦ N–
21.56◦ E, i.e., 413 km distant from the mean SPIRALE position.
3.4
FIRS-2 measurements of HCl, HF, CFC-11 and CFC12
The Far-InfraRed Spectrometer (FIRS)-2 is a thermal emission FTIR spectrometer designed and built at the Smithsonian Astrophysical Observatory. The balloon-borne limbsounding observations provide high-resolution (0.004 cm−1 )
spectra in the wavelength range 7–120 µm (80–1400 cm−1 )
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(Johnson et al., 1995), at altitude levels from the tropopause
to the balloon float altitude (typically 38 km). The retrievals
are conducted in a two-step process. First, the atmospheric
pressure and temperature profiles are retrieved from observations of CO2 spectral lines around 15 µm. Then, vertical profiles of atmospheric trace constituents are retrieved
using a nonlinear Levenberg-Marquardt least-squares algorithm (Johnson et al., 1995). Vertical vmr profiles are routinely produced for ∼30 molecular species including HCl,
HF, CFC-11 and CFC-12. In particular, FIRS-2 retrieves HCl
and HF using 11 and 3 rotational lines, respectively. CFC-11
and CFC-12 are retrieved using the same bands as ACE-FTS
(see relevant part of Table 1).
Uncertainty estimates for FIRS-2 contain random retrieval
error from spectral noise and systematic components from
errors in atmospheric temperature and pointing angle (Jucks
et al., 2002; Johnson et al., 1995). The HCl retrievals yield
total errors decreasing with increasing altitude from 55% at
12 km to 9% at 22 km and smaller than 7% above 22 km. The
HF errors are small (<10%) from 16 to 31 km, with larger
values (∼60%) below this range. For CFC-11, the total error
for the profile used in this study increases with increasing
altitude, from 24% at 12 km to 90% around 20 km. Lastly,
the error values for CFC-12 increase from 55 to 100% over
the same altitude range.
Measurements from FIRS-2 have been used previously
in conjunction with other balloon-borne instruments to validate observations of the v17 HCl data product from HALOE
(Russell et al., 1996a). HALOE showed a positive bias with
respect to FIRS-2 decreasing with altitude, with mean differences ranging from +19% at ∼17 km (100 hPa) to +9%
at ∼31 km (5 hPa) (Russell et al., 1996a). A comparison of
the HALOE v17 HF retrievals with data from the same balloon flights, presented in the companion paper of Russell et
al. (1996b), yielded agreement within ±7% in the altitude
range ∼21–31 km (50–5 hPa) with much larger differences
at the lowermost comparison levels (−53% at 100 hPa or
17 km) (Russell et al., 1996b).
The FIRS-2 profiles were acquired on 24 January 2007 at
10:11 UT (68◦ N, 22◦ E). The coincident ACE-FTS profiles
were obtained at sunrise on 23 January 2007 at 08:25 UT
(occultation sr18561, 64.7◦ N, 15.0◦ E; distance: ∼481 km).
The low float altitude (∼28 km) of the balloon for this particular flight limits the vertical range of the comparison to
31 km. It should be noted that the precision for the CFCs
was below normal for this specific FIRS-2 flight, given the
short time at float altitude and very cold temperatures lowering the signal-to-noise ratio (S/N) in the wavelength region from which CFCs are retrieved. The FIRS-2 profiles,
provided on a 1 km-spacing altitude grid, are interpolated
onto the ACE-FTS altitude grid (1 km-spacing). The position of the FIRS-2 footprint was well inside the Arctic vortex,
while the ACE-FTS footprint was near the edge of the vortex. As a result, atmospheric subsidence mismatches could
possibly affect the comparisons. We have therefore looked at
Atmos. Chem. Phys., 8, 6199–6221, 2008
the equivalence between altitude and potential temperature
(θ ), for both subsets. This has indicated that maximum vertical shifting resulting from the use of potential temperature
would never exceed 0.9 km, for a θ of 340 K, around 12 km.
Over the whole range spanning available measurements from
both instruments, the mean computed shift is equal to 0.3 km.
Hence, comparisons performed using either altitude or potential temperature shows very similar pattern for the absolute and relative differences. We have therefore decided to
present all the comparisons between FIRS-2 and ACE-FTS
against altitude, for consistency with all other investigations
reported here.
3.5
Mark-IV measurements of HCl, HF, CFC-11 and -12
The Jet Propulsion Laboratory (JPL) Mark-IV (hereinafter
MkIV) Interferometer (Toon, 1991) is an FTIR spectrometer designed for remote sensing of atmospheric composition and is optically very similar to the ATMOS instrument.
It has been used for ground-based observations as well as
balloon-borne measurements since 1985. When flown as part
of a high-altitude balloon payload, it provides solar occultation measurements in the spectral range 1.77–15.4 µm (650–
5650 cm−1 ), with high signal-to-noise ratio and high resolution (0.01 cm−1 ).
The retrieval altitude range generally extends from the
cloud tops (5–10 km) to the float altitude (typically 38 km),
with a vertical spacing of 0.9–3 km (depending on latitude
and altitude) and a circular field-of-view of 3.6 mrad, yielding a vertical resolution of ∼1.7 km for a 20 km tangent
height (Toon et al., 1999).
The retrievals are conducted in two distinct steps. Firstly,
slant column abundances are retrieved from the spectra using non-linear least squares fitting. Secondly, the matrix
equation relating these measured slant columns to the unknown vmr profiles and the calculated slant path distances
is solved. This produces retrieved vmr vertical profiles for a
large number of trace gas species including HCl, HF, CFC-11
and CFC-12 (Toon et al., 1999).
The uncertainty in the MkIV profiles is dominated by measurement noise and spectroscopic errors. Other error sources
(such as temperature uncertainties or pointing error) can usually be neglected (Sen et al., 1998). The reported error for
the HCl profiles used in the following analyses ranges from
3 to 10% above ∼18 km. At lower altitudes, the error increases but remains smaller than 100% above ∼15 km. The
HF errors are also quite small (<10%) from 20 to 38 km,
with values rapidly increasing below this range (e.g., 50–
70% at 17 km depending on the flight). The total error on
the CFC-11 retrievals is within 20% below 25 km but, above
this altitude, it becomes considerable. For CFC-12, the profiles used in this study have errors of 3 to 30% (typically 5%)
over most of the altitude range (from 10 to 35 km) with larger
values (<100%) at the uppermost levels (Sen et al., 1998).
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E. Mahieu et al.: Validation of HCl, HF, CCl3 F and CCl2 F2 from ACE-FTS
6205
Table 2. Ground-based sites operating FTIR instruments involved in the present study.
Station
Latitude ◦ N
Longitude ◦ E
Altitude (m)
78.9
76.5
67.8
65.1
53.1
46.5
43.7
28.3
−20.9
−34.5
−45
−77.8
11.9
−68.7
20.4
−147.4
8.8
8
−79.4
−16.5
55.5
150.9
169.7
166.7
20
30
419
610
50
3580
174
2367
50
30
370
200
Ny Ålesund
Thule
Kiruna
Poker Flat
Bremen
Jungfraujoch
Toronto
Izaña
Reunion Island
Wollongong
Lauder
Arrival Heights
The quality of the MkIV observations was assessed
through comparison with twelve in situ instruments embarked on the NASA ER-2 aircraft (Toon et al., 1999). The
MkIV balloon and ER-2 aircraft flights occurred around Fairbanks (Alaska, USA) in 1997 as part of the Photochemistry
of Ozone Loss in the Arctic Region In Summer (POLARIS)
experiment. These comparisons included three of the four
species considered here. Briefly, a very good agreement was
found between MkIV and the in situ instrument, with differences for HCl and CFC-11 within ±10% and as low as
±5% for CFC-12. In all three cases, there was no apparent
systematic bias between MkIV and the coincident measurements (Toon et al., 1999).
Prior to the present study, MkIV data have been used for
satellite validation studies including several papers in the
Journal of Geophysical Research special issue for UARS validation (J. Geophys. Res, 101(D6), 9539–10473, 1996) and
the validation of ILAS data (Toon et al., 2002). More recently, the MkIV data have been compared with the MLS
HCl product (Froidevaux et al., 2006a; Froidevaux et al.,
2008). For HCl, MLS coincident profiles were compared
with two MkIV observations around Ft. Sumner, New Mexico (34.4◦ N, 104.2◦ W) in September 2004 and showed good
agreement – within the error bars – of 5 to 20% (Froidevaux
et al., 2008).
For this work, we compare vmr profiles of HCl, HF, CFC11 and CFC-12 retrieved from MkIV observations around
Ft. Sumner, New Mexico, in September 2003, 2004 and 2005
with zonal averages of ACE-FTS data. There were no direct coincidences between ACE-FTS and the MkIV balloon
flights, because ACE measurements around 35◦ N never occur during the late-September turnaround in stratospheric
winds. The ACE-FTS profiles were thus selected within a
10◦ latitude band around Ft. Sumner between August and
October in 2004, 2005 and 2006. At this time of the year,
the atmospheric layers sounded by the instruments are sufwww.atmos-chem-phys.net/8/6199/2008/
Related publication
Notholt et al. (2000)
Goldman et al. (1999)
Kopp et al. (2003)
Kagawa et al. (2007)
Notholt et al. (2000)
Zander et al. (2008)
Wiacek et al. (2007)
Schneider et al. (2005)
Senten et al. (2008)
Paton-Walsh et al. (2005)
Griffith et al. (2003)
Connor et al. (1998)
ficiently stable to allow for meaningful qualitative comparisons. About 90 ACE-FTS profiles were available in a latitude bin of ±5◦ width centered at 34.4◦ N. These were averaged to provide a zonal mean profile.
3.6
Ground-based FTIR column measurements of HCl and
HF
High-resolution IR solar spectra recorded under clear-sky
conditions with ground-based FTIR (gb-FTIR) instruments
have been analyzed to supply data for comparison with ACEFTS v2.2 products. These observations have been recorded at
12 ground-based sites within the framework of the NDACC,
with latitudes widely distributed among the two hemispheres.
Table 2 lists the station coordinates. Most instruments
are commercial Bruker interferometers, either IFS-125HR,
-120HR or -120M, except at the Toronto and Wollongong
stations where Bomem DA8 spectrometers are operated.
These interferometers are equipped with mercury-cadmiumtelluride (Hg-Cd-Te) and indium-antimonide (InSb) detectors, which allow coverage of the 650–1500 and 1650–
4400 cm−1 spectral intervals, respectively. Spectral resolutions, defined as the inverse of the maximum optical path
difference, range from 0.002 to 0.008 cm−1 .
All ground-based instruments involved here perform regular measurements encompassing the main IR absorption features of HCl, HF, CFC-11 and CFC-12. For the source gases
however, the ground-based measurements are mostly sensitive to the tropospheric contribution of their absorptions, with
poor or no vertical information available. These features are
used to retrieve information on the atmospheric loadings of
these two CFCs, and on their trends (e.g., Zander et al., 2005;
Rinsland et al., 2005). Comparison with ACE-FTS measurements of the CFCs was not possible, as the ACE profiles
are limited to the upper troposphere and lower stratosphere.
Consequently, the FTIRs will contribute here to the validation of ACE-FTS v2.2 HCl and HF products, for which both
Atmos. Chem. Phys., 8, 6199–6221, 2008
6206
E. Mahieu et al.: Validation of HCl, HF, CCl3 F and CCl2 F2 from ACE-FTS
ground- and space-based viewing geometries provide reliable, compatible and comparable information, in the same
altitude region of the atmosphere.
The retrievals have been performed using two algorithms.
PROFFIT92 was used to analyze the Kiruna and Izana observations, SFIT2 (v3.8 or v3.9) in all other cases. Both
codes are based on the Optimal Estimation Method (OEM)
(Rodgers, 1976), they allow to retrieve information on the
vertical distribution of most of the FTIR target gases, including HCl and HF. The two algorithms have been compared
by Hase et al. (2004) for a series of tropospheric and stratospheric species and proved to be highly consistent, for profile
and column retrievals; in particular, the agreement was better
than 1% for both HCl and HF.
The OEM implemented in both algorithms helps to characterize the retrieved products, using the averaging kernel
and related eigenvector formalism (e.g., Barret et al., 2003).
Tools have been developed to perform these assessments and
to evaluate the impact of the various fitting options, a priori
inputs and assumptions made, on the information content.
Instead of using a single standardized retrieval strategy,
approaches have been optimized by the FTIR data providers
in order to generate the maximum information content for
HCl and HF, taking into account specific observation conditions at each site (dryness, altitude, latitude, . . . ) as well
as instrument performance characteristics, such as the typical signal-to-noise ratio achieved and the spectral resolution.
Table 3 provides detailed information about the microwindows used simultaneously, the fitted interferences, the number of independent pieces of information available (given by
the trace of the averaging kernel matrix) or Degrees Of Freedom for Signal (DOFS) and the altitude range of maximum
sensitivity. Typical averaging kernels and eigenvectors corresponding to the adopted settings indicate that the retrievals of
HCl and HF are mainly sensitive in the 12 to 35 km altitude
range, with DOFS typically ranging from 1.4 to 3.8 for HCl
and from 1.5 to 3.0 for HF (see Table 3). For Jungfraujoch,
the first two eigenvalues (λ1 and λ2 ) are typically equal to
0.98 and 0.76, 0.98 and 0.66, respectively for HCl and HF,
demonstrating that in both cases the impact of the a priori
on the corresponding retrieved partial column is negligible,
of the order of 2%. For most sites, additional information
on the retrieval approaches adopted for HCl can be found in
Appendix A of Rinsland et al. (2003). Relevant references
are also provided in the last column of Table 2. It is worth
noting that HITRAN-2004 line parameters (Rothman et al.,
2005) were adopted in all cases, for target and interfering
species, consistent with the ACE-FTS. Since the official release of HITRAN 2004 however, there has been several line
parameter updates made available for gases interfering in the
HCl or HF fitted intervals (e.g. H2 O, O3 ). We have therefore
performed retrievals using these various HITRAN updates
to evaluate the impact of each linelists on the ground-based
products. They have been found to be completely negligible.
The impact of systematic uncertainties affecting the spectroAtmos. Chem. Phys., 8, 6199–6221, 2008
scopic parameters of these species can therefore be neglected
in the error budget.
On the basis of the Jungfraujoch retrievals, statistical error
analyses complemented with estimates based on the perturbation method have indicated that the smoothing error is the
main contribution to the error budget, followed by the measurement error and instrumental line shape uncertainties, independently evaluated with regular cell measurements. Once
combined, the relative errors corresponding to stratospheric
columns are on average about 2.6 and 3.2% for HCl and
HF, respectively. Comparative and complementary error estimates have been generated from PROFFIT runs for typical
Kiruna observations, including evaluation of the impact of
random error sources such as zero level uncertainties, channeling and tilt, fitted interferences, temperature uncertainties,
and effect of spectrum signal-to-noise. For both species, uncertainties in the temperature and zero level are the dominant
error sources in this list. After quadratic combination, stratospheric column errors amount to ∼2.5% for HCl, and ∼3.0%
for HF, i.e., commensurate with other estimates performed
above.
Finally, HCl error budget evaluations performed in previous studies (e.g. Rinsland et al., 2003) further confirm the
values quoted here, with a 3% random error associated with
a single stratospheric column retrieval from Kitt Peak spectra.
As mentioned earlier, both PROFFIT and SFIT2 use the
OEM formalism. This is particularly useful when performing comparisons between measurements obtained with significantly different vertical resolutions. Indeed, it has been
shown by Rodgers and Connors (2003) that a fair comparison requires convolution of the high-vertical-resolution measurement (ACE-FTS here) with the averaging kernel of the
low-vertical-resolution data (gb-FTIR) using the following
equation:
xS = xa + A(xACE − xa )
(1)
where xS is the resulting smoothed profile, xa is the FTIR
a priori, xACE is the ACE-FTS retrieved vertical distribution
and A is the FTIR averaging kernel.
Actual or typical averaging kernels have been used to perform these operations, after proper extrapolation of the ACEFTS profile down to the altitude site, using xa . For verification, extensions with other plausible vertical distributions
were also performed for part of our dataset; we noted only
marginal impact (on the order of a few tenths of a percent on
average) on the partial columns computed on the basis of the
smoothed ACE-FTS profiles.
For most sites, time and space criteria for coincidence
with ACE-FTS measurements have been set to ±24 h and
1000 km. However, the distance criterion was tightened to
500 km for Kiruna and Thule to minimize possible influence
of the Polar vortex. For Reunion Island, it was relaxed to
1200 km to increase the number of coincidences, since there
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E. Mahieu et al.: Validation of HCl, HF, CCl3 F and CCl2 F2 from ACE-FTS
6207
Table 3. Information about retrieval strategies adopted at each ground-based site, corresponding information content and sensitivity ranges.
HCl
HF
Microwindows and
fitted interferences
DOFSa and
sensitivity range
Microwindows, and
fitted interferences
DOFSa and
sensitivity range
Ny Ålesund
2727.60–2727.95
2925.80–2926.00
H2 O, O3 , CH4
3.85
10–41.3 km
4038.80–4039.15
H2 O, HDO, CH4
2.00
13.6–31.6 km
Thule
2727.60–2727.95
2775.60–2775.95
2925.7–2926.1
HDO , O3 , CH4
1.7
12.2–31.4 km
4000.80–4001.20
4038.75–4039.20
H2 O, HDO, CH4
1.7
12.2–31.4 km
Kiruna
2727.73–2727.82
2752.01–2752.05
2775.70–2775.79
2821.51–2821.62
2843.55–2843.65
2925.80–2926.00
2963.23–2963.35
3045.00–3045.10
H2 O, HDO, O3 , CH4
3.25
11.7—41.6 km
4000.9–4001.05
4038.85–4039.08
H2 O, HDO
3.07
11.7–41.6 km
Poker Flat
2925.80–2926.00
H2 O, O3 , CH4 , NO2
2.0
12–40 km
4038.80–4039.15
H2 O, HDO
1.9
14–40 km
Bremen
2727.60–2727.95
2925.80–2926.00
H2 O, O3 , CH4
2.78
10.0–39.2 km
4038.80–4039.15
H2 O, HDO, CH4
1.97
12.4–34.1 km
Jungfraujoch
2727.73–2727.83
2775.70–2775.80
2925.80–2926.00
O3 , CH4 , NO2
2.00±0.35
10–27 km
4038.8–4039.11
H2 O, HDO, CH4
1.80±0.20
12–27 km
Toronto
2925.80–2926.00
O3 , CH4 , NO2
3.10
14–39 km
4038.77–4039.13
H2 O, HDO, CH4
2.0
20–35 km
Izaña
Same as per Kiruna
2.35
11.7–41.6 km
Same as per Kiruna
1.95
11.7–41.6 km
Reunion Island
2843.3–2843.8
2925.7–2926.6
H2 O, O3 , CH4 , NO2
1.54±0.12
10.0–43.6 km
4038.7–4039.05
H2 O, HDO, CH4
1.51±0.06
14.8–39.2 km
Wollongong
2925.75–2926.05
H2 O, O3 , CH4 , NO2
1.72±0.11
14–36 km
4038.80–4039.05
H2 O, HDO, CH4
1.47±0.08
14–34 km
Lauder
2925.75–2926.05
H2 O, O3 , CH4
2.52±0.24
18–38 km
4038.78–4039.10
H2 O,HDO,CH4
2.67±0.21
14–36 km
Arrival Heights
2925.75–2926.05
H2 O, O3 , CH4
2.45±0.35
14–40 km
Station
–
a DOFS were computed using either typical averaging kernel or the actual subsets of matrices used for the smoothing process; in the latter
case, the standard deviation around the mean is given.
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Atmos. Chem. Phys., 8, 6199–6221, 2008
E. Mahieu et al.: Validation of HCl, HF, CCl3 F and CCl2 F2 from ACE-FTS
P = 46.4 hPa
0.1
1.5
-0.0
1.0
-0.1
20-50oN
-0.2
0.1
1.5
-0.0
1.0
-0.1
20-50oS
-0.2
0.1
1.5
-0.0
1.0
-0.1
50-90oS
-0.2
HCl / ppbv
0.2
0.0
50-90oN
-0.2
0.4
0.3
2.8
0.2
2.6
0.1
2.4
0.0
20-50oN
-0.1
-0.2
0.4
0.3
2.8
0.2
2.6
0.1
2.4
0.0
20-50oS
-0.1
-0.2
0.4
0.3
2.8
0.2
2.6
0.1
2.4
0.0
50-90oS
2.2
2.0
-0.3
-0.1
Difference / ppbv
0.1
2.4
2.2
2.0
3.2
3.0
-0.3
0.3
2.0
0.5
0.0
HCl / ppbv
0.2
0.2
2.6
0.3
2.2
2.0
3.2
3.0
-0.3
0.3
2.0
0.5
0.0
3.0
2.5
HCl / ppbv
2.0
2.8
2.2
2.0
3.2
3.0
-0.3
0.3
0.2
0.4
Difference / ppbv
-0.2
3.2
3.0
Difference / ppbv
50-90oN
HCl / ppbv
-0.1
Difference / ppbv
1.0
Difference / ppbv
HCl / ppbv
0.1
-0.0
0.5
0.0
3.0
2.5
HCl / ppbv
0.2
1.5
0.5
0.0
3.0
2.5
HCl / ppbv
P = 2.2 hPa
0.3
Difference / ppbv
2.0
ACE-FTS
MLS
ACE - MLS
Difference / ppbv
HCl / ppbv
3.0
2.5
-0.1
Difference / ppbv
6208
-0.2
S N J5 M M J S N J6 M M J S N J7 M M J S
S N J5 M M J S N J6 M M J S N J7 M M J S
Fig. 2. Same as Fig. 1 but for 2.2 hPa.
Fig. 1. Time series of HCl monthly mean mixing ratios at 46 hPa
from ACE-FTS and Aura MLS in four latitude bins identified in
Figure
2. Same as Figure 1 but for 2.2 hPa.
Figure 1. Time series of HCl monthly mean mixing ratios at 46 hPa from ACE-FTS
and Aura
each panel. The zonal means for each month and latitude bin are
MLS
in
four
latitude
bins
identified
in
each
panel.
The
zonal
means
for
each
month
and
for
Environmental
Prediction) data, or on p-T soundings perobtained by averaging all available coincident profiles from both
formed
in
the
vicinity
of the site.
data sets;
gaps
are largely
causedallbyavailable
gaps incoincident
the reprocessing
of both data sets;
latitude
bin are
obtained
by averaging
profiles from
MLS
version
2.2
data,
along
with
a
few
gaps
in
the
ACE-FTS
data.
gaps are largely caused by gaps in the reprocessing of MLS version 2.2 data, along with a few
Black triangles are the differences (ACE-FTS minus MLS, see right
gaps in the ACE-FTS data. Black triangles are the differences (ACE-FTS minus4MLS,
see
Comparisons
between ACE-FTS measurements and
axis scale). Mixing ratio error bars represent the 2-σ standard erright
axis
scale).
Mixing
ratio
error
bars
represent
the
2-σ
standard
errors
for
the
zonal
correlative
data
rors for the zonal means, based on the available single-profile error
estimates;
for the
differenceserror
are estimates;
the root sum
means,
basederror
on thebars
available
single-profile
error square
bars forof
the differences are
The following subsections will present the HCl, HF, CFC-11
these
estimated
standard
errors
in
the
means.
the root sum square of these estimated standard errors in the means.
are fewer ACE-FTS measurements available at tropical latitudes.
Determination of the altitude range for partial column
comparisons were objectively based on averaging kernel and/or eigenvector inspections, following the practical
methods described previously in Barret et al. (2003) and
Vigouroux et al. (2007). The adopted values are listed in
columns 3 and 5 of Table 3, for each site and for both reservoir species.
Densities have been computed using the pressuretemperature (p-T) information associated with each data
set. For ACE-FTS, p-T profiles retrieved from the spectra
(Sect. 2) and made available together with the vmr distributions were used. For ground-based FTIRs, the daily p-T
information used in the PROFFIT or SFIT2 retrievals was
adopted; they are either based on NCEP (National Centers
Atmos. Chem. Phys., 8, 6199–6221, 2008
and CFC-12 comparisons, starting with space-based instruments, 45then balloon-borne and ground-based FTIRs, in this
order and when available.
Fractional differences (1) between the vmrs or partial
columns from ACE-FTS and the validating instrument (VAL)
have been computed using the following formula:
1=2×
(xACE − xVAL )
(in %)
(xACE + xVAL )
(2)
Relative differences are statistically characterized by the
standard deviation around the √
mean (denoted σ ) and the standard error on the mean (as σ/ N for N coincidences).
4.1
4.1.1
HCl comparisons
MLS
The version 2.2 ACE-FTS HCl profiles have been shown to
agree quite well with MLS v2.2 HCl retrievals, within about
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4
E. Mahieu et al.: Validation of HCl, HF, CCl3 F and CCl2 F2 from ACE-FTS
Fig. 3. Left panel: average profiles (thick lines) for all coincident
Figure 3. Left panel: average profiles (thick lines) for all coincident measurements between
measurements
between ACE-FTS (red) and HALOE (black), as a
ACE-FTS (red) and HALOE (black), as a function of altitude. Thin lines are the profiles of
function
of altitude. Thin lines are the profiles of standard deviastandard deviations (1-σ) of the distributions, while error bars (often too small to be seen)
tions
(1-σ ) of the distributions, while error bars (often too small to
represent the standard error. Absolute differences based on all 36 coincidences are shown in
be
seen) represent the standard error. Absolute differences based on
the centre panel while fractional differences are reproduced on the right panel.
all
36 coincidences are shown in the centre panel while fractional
differences are reproduced on the right panel.
5 to 10% on average, from 100 to 0.2 hPa (i.e. approximately
from 16 to 60 km) (Froidevaux et al., 2008); furthermore,
the latitudinal distribution observed by MLS is well matched
by that obtained from coincident ACE-FTS profiles. The
above reference made use of data comparisons from mid2004 through 2006; the results are essentially the same if one
uses comparisons from 2007 alone, and they are not shown
47
here. Instead, we show the time dependence of monthly
zonal mean comparisons from all (4731) available coincident ACE-FTS and MLS profile pairs in Fig. 1, at the 46 hPa
pressure level (around 20 km). The monthly mean HCl averages from ACE-FTS and MLS are in good agreement, as
shown by the error bars (2-σ ) on the abundances as well as
the differences in Fig. 1. As one would expect, the number of
monthly coincidences is largest for the high latitude bins (the
maximum number being 285); the error bars in this figure
give a good indication of the relative number of coincidences.
Figure 2 provides a similar view for the upper stratosphere
(at 2.2 hPa or about 41 km), where the variations are smaller,
but nevertheless well matched between these two data sets.
It should be pointed out that such time series comparisons
are not meant to represent the best description of actual atmospheric variations versus time, as only coincident profile
pairs, based on the ACE-FTS sampling pattern, are included;
we simply demonstrate that similar temporal changes can be
obtained from such matched profiles.
4.1.2
HALOE
Figure 3 shows the average HCl profiles measured by both
instruments for all 36 available coincidences (left panel), i.e.
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6209
Fig. 4. Standard deviations of the distributions relative to the mean
Figure 4. Standard deviations of the distributions relative to the mean HCl vmr at each
HCl vmr at each altitude, for all coincident events, for ACE-FTS
altitude, for all coincident events, for ACE-FTS (red) and HALOE (black).
(red) and HALOE (black).
considering simultaneously the sunset and sunrise events.
Both instruments show vmrs increasing with altitude, with
the ACE-FTS vmrs biased high compared to HALOE above
about 20 km. The thin lines in left panel of Fig. 3 represent
the standard deviations of the distribution of profiles measured by each instrument, indicating that both instruments
measure similar variability. Measurement variability is quantified more clearly in Fig. 4, which shows the standard deviations of the distributions relative to the mean mixing ratios.
There is excellent agreement between the standard deviations
48
of ACE-FTS and HALOE at all altitudes, with values on the
order of about 5% from 20 to 55 km.
The right panel of Fig. 3 shows the fractional differences
as a function of altitude. Average differences are around 10–
15% throughout the stratosphere, with the ACE-FTS biased
high compared to HALOE above 17 km. This offset is commensurate with earlier intercomparisons (see Sect. 3.2), concluding that the HCl observations by HALOE are biased low
with respect to other relevant data sets. This is also consistent with the conclusions from the MLS versus HALOE
comparisons performed by Froidevaux et al. (2008). These
authors have noted that, despite a systematic bias, the MLS
and HALOE spatial variations are very similar and of the
same amplitude and sign as the one derived here.
4.1.3
SPIRALE
After locating the ACE-FTS occultation that was closest to the SPIRALE measurement, an additional “coincidence criterion” was investigated.
Using the MIMOSA (Modélisation Isentrope du transport Mésoéchelle
de l’Ozone Stratosphérique par Advection) contour advection model (Hauchecorne et al., 2002), potential vorticity
(PV) maps in the region of both measurements have been
Atmos. Chem. Phys., 8, 6199–6221, 2008
6210
E. Mahieu et al.: Validation of HCl, HF, CCl3 F and CCl2 F2 from ACE-FTS
Fig. 5. HCl vertical profiles (on the left) obtained by ACE-FTS
Figure 5. HCl vertical profiles (on the left) obtained by ACE-FTS (from occultation sr13151,
(from occultation sr13151, in red) and SPIRALE (in black and blue)
in red) and SPIRALE (in black and blue) on 20-21 January 2006, near Kiruna. The solid blue
on 20–21 January 2006, near Kiruna. The solid blue line correline corresponds to the SPIRALE measurements (very high vertical resolution) and the black
sponds to the SPIRALE measurements (very high vertical resoludiamonds correspond to the SPIRALE profile smoothed with a triangular function (see text).
tion) and the black diamonds correspond to the SPIRALE profile
The centre panel shows absolute difference between the two profiles while corresponding
smoothed with a triangular function (see text). The centre panel
relative differences (∆) are presented on the right.
shows absolute difference between the two profiles while corresponding relative differences (1) are presented on the right.
calculated at each hour between 17:00 UT on 20 January
2006 and 08:00 UT on 21 January 2006 on isentropic surfaces, every 50 K from 350 K to 800 K (corresponding to altitudes between 12.8 and 30 km). From these PV fields it
can be deduced that SPIRALE and ACE-FTS vertical profiles
were located in similar air masses in the well-established po49
lar vortex over the whole range of altitudes. The dynamical
situation was very stable with PV agreement better than 10%.
Thus the meteorological situation was considered suitable to
allow direct comparison between these two data sets.
Before performing any comparison, the difference in the
vertical resolution of the two instruments had to be taken
into account, because ACE-FTS has a vertical resolution of
3–4 km while that of SPIRALE is on the order of meters.
A triangular weighting function of width equal to 3 km at
the base (corresponding to the ACE-FTS estimated vertical
resolution) was therefore applied to SPIRALE data at each
of the ACE-FTS measurement altitudes, as in, e.g., Dupuy
et al. (2008; Sect. 4, Eq. 1). Consequently, the SPIRALE
profile was truncated by 1.5 km at the bottom and at the
top. Then, the resulting profile was interpolated on to the
ACE 1 km-grid. The ACE-FTS and SPIRALE HCl profiles
(Fig. 5) are in good agreement between 16 and 20 km and
above 23 km. Over these altitude ranges, the fractional differences (see right panel) lie between −2 and +27%. The lower
(by more than 40%) HCl values observed by SPIRALE in
the layer 20–23 km height are probably due to a PSC crossed
by the gondola from 19.3 to 20.7 km height (detected by
the onboard aerosol counter). Indeed, the use of the HYSPLIT model (HYbrid Single-Particle Lagrangian Integrated
Atmos. Chem. Phys., 8, 6199–6221, 2008
Fig.
6. Comparison of an HCl profile from FIRS-2 on 24 JanFigure 6. Comparison of an HCl profile from FIRS-2 on 24 January 2007 at 10:11 UT with a
uary
2007 at 10:11 UT with a profile from ACE-FTS occultation
profile from ACE-FTS occultation sr18561 obtained on 23 January 2007 at 08:25 UT. Left:
sr18561
obtained on 23 January 2007 at 08:25 UT. Left: Measured
Measured vmr profiles from FIRS-2 (solid black) and ACE-FTS (dashed red). Error bars
vmr
profiles
from FIRS-2 (solid black) and ACE-FTS (dashed red).
show uncertainty estimate for FIRS-2 and fitting error for ACE-FTS every 2 km. Middle:
Error
bars
show inuncertainty
estimate
for FIRS-2
and
fitting/ (ACE
error+
Absolute
differences
ppbv. Right: Fractional
differences
2 x (ACE
- FIRS-2)
for
ACE-FTS
FIRS-2)
in percent.every 2 km. Middle: Absolute differences in ppbv.
Right: Fractional differences 2×(ACE−FIRS-2)/(ACE+FIRS-2) in
percent.
Trajectory, see http://www.arl.noaa.gov/ready/hysplit4.html)
shows that the temperature encountered along the trajectories above 20.7 km during two days before the measurements
were compatible with the formation of PSC particles, on
which HCl may be adsorbed. At the time of the SPIRALE50
and of the aerosol counter measurements, the PSC has sedimented. In general, the ACE-FTS HCl vmr values are larger
than those of SPIRALE for the whole altitude range except
at 24.5 km.
4.1.4
FIRS-2
The comparison between ACE-FTS and FIRS-2 HCl profiles
is shown in Fig. 6. ACE-FTS reports systematically more
HCl over the altitude range 12–31 km, with largest fractional
differences (>+90%) below 15 km where the HCl abundance
is small (less than 0.4 ppbv). Above 15 km, the profile shapes
are similar for ACE-FTS and FIRS-2, but the ACE-FTS vmr
values are significantly larger than those of FIRS-2. The fractional differences are within +20 to +66% with smallest values at the uppermost levels. There are also indications of a
high bias for MLS versus FIRS-2 HCl profiles in Froidevaux
et al. (2008), although it’s hard to compare since these coincidences were obtained at different latitudes and seasons.
At present, the large difference between ACE-FTS and
FIRS-2 remains unexplained. All eleven HCl lines used
in the FIRS-2 retrievals provide consistent results over the
whole altitude range. These measurements were indeed obtained further north with respect to ACE-FTS, and they were
performed in PSCs. However, a feature at 20 km in the
ACE-imager extinction profiles supports the idea that the
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E. Mahieu et al.: Validation of HCl, HF, CCl3 F and CCl2 F2 from ACE-FTS
6211
ACE-FTS observations could also have been influenced by
PSCs, at least partially. Onboard the same gondola than
FIRS-2, the Submillimeterwave Limb Sounder (SLS) measured large amounts of ClO. Although HCl measurements
performed by SLS were also higher than FIRS-2, it was not
by the amount suggested by the comparison performed here
and part of the difference could result from real HCl variability in winter high latitude stratosphere, in particular when
comparing vortex-edge and inside-of-vortex air masses.
4.1.5
Mark-IV
The comparison between ACE-FTS and MkIV HCl profiles
is shown in Fig. 7. The ACE-FTS zonal mean vmrs are in
very good agreement (to better than ±7%) with the MkIV
measurements above 20 km. Between 17 and 20 km, ACEFTS reports less HCl than MkIV, by up to −20%. Below
17 km, the relative differences become extremely large. This
is mostly due to very small vmr values for both ACE-FTS
and MkIV.
4.1.6
Ground-based FTIRs
Individual site comparisons have been performed, on the basis of the coincidence criteria defined in Sect. 3.6. Statistical
results consisting of the mean fractional differences, corresponding standard deviations and standard errors are listed in
Table 4, except when only a few coincidences are available.
The next column in Table 4 provides the number of coincidences; 174 ACE-FTS occultations are used here, recorded
from March 2004 to March 2007. Furthermore, a global
mean and corresponding statistics are given at the end of the
table, for all coincidences considered at once. Although no
clear picture emerges from the statistics, it should be pointed
out that (i) very few relative differences are significant at the
1-σ level; (ii) no PV filtering is included while the largest
positive differences (1; see Eq. 2) are generally obtained for
high latitude sites (Ny Ålesund and Arrival Heights); (iii) although two of the three negative mean values are observed in
the Southern Hemisphere (Wollongong and Lauder), no conclusion should be drawn regarding a latitudinal pattern in the
differences, given the uncertainties affecting the means.
The overall relative difference is (6.9±15.9) % (1-σ ), or
(6.9±1.2) % (standard error). This would suggest a slight
overestimation of HCl partial columns by ACE-FTS, on the
order of a few percent. We note however that the largest
individual fractional differences, all observed at high northern and southern latitudes during the winter-spring time period, are included in this evaluation. In order to minimize the
contribution of spatial variability on the global statistics, we
have further limited the latitude difference to 200 km, with no
additional restriction on the longitude spread. Corresponding statistics are given in the last line of Table 4. We note
a significant improvement, with a mean 1 found equal to
(2.0±11.7) % (1-σ ), or (2.0±1.8) % (standard error).
www.atmos-chem-phys.net/8/6199/2008/
Fig. 7. Comparison of three HCl profiles from MkIV (20 September
Comparison
of three HCl
profiles
from MkIV
(20 September
2003 – 01:25 UT, 24
2003 – Figure
01:257.UT,
24 September
2004
– 01:00
UT and
21 Septem◦
◦W –
ber 2005
– 01:25
UT)– 01:00
around
Sumner
(34.4
104.2UT)
September
2004
UTFort
and 21
September
2005N,
– 01:25
around Fort Sumne
New Mexico,
a zonal
average
of all
ACE-FTS
(34.4ºN, USA),
104.2ºWwith
– New
Mexico,
USA), with
a zonal
averageprofiles
of all ACE-FTS profile
obtainedobtained
in August,
September
October
2004,
and
2006
in August,
September and
and October
2004,
2005 2005
and 2006
within
a latitude bin of ±5
within a latitude bin of ±5◦ centered at 34.4◦ N. The ACE-FTS
centered at 34.4ºN. The ACE-FTS zonal mean profile is shown in red, with error bar
zonal mean profile is shown in red, with error bars corresponding
corresponding to the 1-σ standard deviation of the mean. The individual measurements from
to the 1-σ standard deviation of the mean. The individual measureMkIVMkIV
are shown
the dashed
blackdashed
curves, black
with corresponding
uncertainties
given by the
ments from
arebyshown
by the
curves, with
corshadeduncertainties
area. The number
of ACE-FTS
occultations
used
in the
zonal averages
is indicated
responding
given
by the shaded
area.
The
number
of
every
5 km on the right-hand
ACE-FTS
occultations
used in side.
the zonal averages is indicated every
5 km on the right-hand side.
In addition, all coincident HCl partial columns from ACEFTS and from all 12 ground-based sites involved here have
been included in a scatter plot (Fig. 8). Sites are identified by
various symbols and colors, data from all latitudes and seasons are included. It is worth mentioning that the magnitude
of the partial columns is influenced by the altitude ranges
considered at each site in the partial column calculations (see
Table 3 and Sect. 3.6). Moreover, measurements are not performed year-round at all sites. Hence, no direct conclusion
should be drawn from their relative values and distribution.
The linear regression to all data is reproduced by the dashdotted black line, its slope and intercept are respectively
equal to 0.90 and 5.52×1014 molecules/cm2 , with a correlation coefficient R of 0.87. When restricting the data set to
coincidences occurring within less than 200 km of latitude
difference (see continuous black line and crossed-symbols),
the correlation improves significantly with a slope of 1.02, an
intercept of 2.25×1013 molecules/cm2 and a correlation coefficient of 0.96. This fitted straight line is compatible with
the 1:1 line correlation, at the 95% confidence level. This improvement suggests that part of the comparisons still include
natural spatial variability for HCl, in particular in vortex-type
situations, where subsided or chlorine-depleted air might be
Atmos. Chem. Phys., 8, 6199–6221, 2008
51
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E. Mahieu et al.: Validation of HCl, HF, CCl3 F and CCl2 F2 from ACE-FTS
Table 4. Fractional differences between ACE-FTS and ground-based partial column measurements of HCl and HF, together with standard
deviations and standard errors on the means. The number of coincidences is given in columns 3 and 5. The last two lines provide the
statistical parameters considering all coincidences at once, within 1000 km (500 km for Kiruna and Thule, 1200 km for Reunion Island) and
when further restricting latitude difference to less than 200 km, respectively.
HCl
Station
Mean 1 (%)
1-σ and [stand. error]
# coinc.
Mean 1 (%)
1-σ and [stand. error]
# coinc.
Ny Ålesund
Thule
Kiruna
Poker Flat
Bremen
Jungfraujoch
Toronto
Izaña
Reunion Island
Wollongong
Lauder
Arrival Heights
15.45±19.29 [4.21]
2.19±9.46 [2.85]
9.77±8.35 [2.23]
7.1±10.02 [2.90]
12.16±15.09 [4.03]
10.76±12.75 [2.50]
6.20±12.95 [3.46]
–
–
−5.68±16.88 [3.46]
−2.84±6.25 [1.33]
8.41±25.38 [5.41]
21
11
14
12
14
26
14
5
5
8
22
22
12.34±7.74 [2.00]
6.54±7.42 [1.98]
6.60±9.58 [2.76]
6.96±7.94 [2.12]
–
7.42±10.88 [2.43]
–
–
–
–
13.54±9.34 [2.20]
–
15
14
12
14
–
20
5
4
2
4
18
–
6.95±15.94 [1.21]
2.03±11.74 [1.81]
174
42
7.40±11.38 [1.10]
2.80±8.70 [1.59]
108
30
All
Lat.diff. <200 km
sampled. This is consistent with the statistically significant
drop between the actual ranges of the fractional differences,
from (5.8 to 7.8) % to (0.2 to 3.8) % reported here above (see
Table 4, 1±standard error). If we assume that the closest
comparisons are not significantly affected by spatial variability, we can evaluate that at least a third of the fractional differences characterizing the complete dataset can be attributed to
natural variability. The remaining contribution corresponds
to a negligible up to a reasonable bias between the groundbased FTIRs and the ACE-FTS partial columns, of less than
4%. Hence, the latter value has to be considered as the most
representative upper limit bias between the space- and the
ground-based instruments. Also, it should be noted that restriction of the time differences (e.g., to ±12 h) does not improve the correlation.
4.2
4.2.1
HF
HF comparisons
HALOE
Similarly to Fig. 3, Fig. 9 shows the average HF profiles measured by both instruments for all coincidences, in left panel.
Here again, results for averages over all of the coincidences
are reported. Both instruments show very similar profile
shapes, but the ACE-FTS vmrs are biased high compared to
HALOE throughout most of the altitude range. Qualitatively,
it is clear that both instruments measure similar variability
below 30 km, but that ACE-FTS variability is higher above
30 km. Measurement variability is quantified more clearly
in Fig. 10. As noted above, the ACE-FTS instrument shows
Atmos. Chem. Phys., 8, 6199–6221, 2008
higher variability above 30 km, probably indicative of poorer
precision. Nevertheless, the standard deviation profiles have
similar shapes, with both instruments measuring an increase
in variability near 30 km. This suggests that the larger variability near 30 km is a real geophysical feature. Although not
shown here, this is analogous to the standard deviations seen
in e.g., the CH4 comparisons (De Mazière et al., 2008). We
believe that this is likely the result of summertime longitudinal variations arising from differential meridional transport
caused by breaking of westward-propagating waves that are
evanescent in the summer easterly flow (e.g., Hoppel et al.,
1999).
The right panel of Fig. 9 shows the percent differences between the instruments while the centre panel shows the absolute differences. Measurements from the ACE-FTS are
biased high compared to HALOE, with mean differences
around 5–20% from 15 to 49 km. As for HCl, the HF concentration measurements by HALOE have consistently revealed low biases when compared to other independent relevant datasets (i.e., Russell et al., 1996b; McHugh et al.,
2005), whose magnitude is confirmed here.
4.2.2
FIRS-2
The results of the comparison for HF are shown in Fig. 11.
ACE-FTS is systematically biased high with respect to FIRS2. The extremely large relative differences at the lowermost altitude levels (>100% below 17 km) can be explained by the very low values of the HF vmr at these altitudes, and by the negative vmr values (below 16 km) found
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E. Mahieu et al.: Validation of HCl, HF, CCl3 F and CCl2 F2 from ACE-FTS
6213
Fig. 10. Same as Fig. 4 but for comparison of HF profiles from
Figure
10. Same
Figure 4 but for comparison of HF profiles from HALOE and ACE-FTS.
HALOE
andas ACE-FTS.
Figure 8. Scatter plot of the ACE-FTS partial columns versus the ground-based coincident
Fig.
8. Scatter
plot ±of24hthe
partial
versus
the
measurements,
taken within
and ACE-FTS
1000 km (restricted
to 500columns
km for Kiruna
and Thule,
ground-based
coincident
measurements,
taken
within
±24
h
and
relaxed to 1200 km for Reunion Island, see text). See inserted legend for identification of the
1000
km (restricted
to 500
km foras Kiruna
andblack
Thule,
relaxed
to
sites. Linear
fit to all data points
is reproduced
a dash-dotted
line. When
restricting
1200
km difference
for Reunion
See inserted
legend
for idenlatitudinal
to less Island,
than 200 see
km text).
(see symbols
with plusses),
the correlation
is
tification
of athe
Linearblack
fit line)
to all
is reproduced
as
improved, with
linearsites.
fit (continuous
closedata
to thepoints
1:1 line (dashed
line).
a dash-dotted black line. When restricting latitudinal difference to
less than 200 km (see symbols with plusses), the correlation is improved, with a linear fit (continuous black line) close to the 1:1 line
(dashed line).
52
54
Fig. 11. Same as Fig. 6 but for comparison of HF profiles from
FIRS-2 and ACE-FTS.
Figure 11. Same as Figure 6 but for comparison of HF profiles from FIRS-2 and ACE-FTS.
HCl comparison, the HF differences remain significant over
the whole altitude range. This is unexplained thus far, and
such similar discrepancies are not confirmed when looking
at ozone (Dupuy et al., 2008; Fig. 26).
4.2.3
Fig. 9. Same as Fig. 3 but for comparison of HF profiles from
Figure 9. Same
Figure 3 but for comparison of HF profiles from HALOE and ACE-FTS.
HALOE
andas ACE-FTS.
in the FIRS-2 profile. This is also the range where the
FIRS-2 quoted uncertainties are the largest (∼60%). Above
17–18 km, significant differences ranging between +17 and
+50% are found, i.e., in any case larger than the 10% uncertainty estimates for FIRS-2. Although smaller than for the
www.atmos-chem-phys.net/8/6199/2008/
Mark-IV
The results of the comparison for HF are shown in Fig. 12.
Here also, there is good agreement between the ACE-FTS
vmrs and MkIV. The relative differences are within ±10%
above 19 km. For the same reasons as mentioned for HCl55
in Sect. 4.1.5, the discrepancies increase rapidly below this
altitude.
4.2.4
Ground-based FTIRs
The same approach has been used to compare ACE-FTS
and ground-based FTIR partial columns of HF. The last two
Atmos. Chem. Phys., 8, 6199–6221, 2008
6214
E. Mahieu et al.: Validation of HCl, HF, CCl3 F and CCl2 F2 from ACE-FTS
Fig. 12. Same as for Fig. 7 but for comparison of HF profiles from
MkIV and
ACE-FTS.
Figure
12. Same as for Figure 7 but for comparison of HF profiles from MkIV and ACE-FTS.
Figure 13. Same as Figure 8, but for comparison of ACE-FTS and ground-based FTIR partial
Fig.
13.
Same as Fig. 8, but for comparison of ACE-FTS and
columns
for HF.
ground-based FTIR partial columns for HF.
columns of Table 4 give the corresponding statistical results
and number of available coincidences, found between March
2004 and December 2006, using the same temporal and spatial criteria as before. Here again, most results are compatible
with a no bias at the 1-σ level, although the number of coincidences is generally lower than for HCl. When considering
all data together, we found a mean relative difference and
corresponding standard deviation of (7.4±11.4) % (1-σ ); or
(7.4±1.1) % (standard error). As for the HCl comparison,
restriction of the dataset by considering maximum latitude
difference of 200 km significantly reduces the mean bias to
(2.8±8.7) % (1-σ ) and (2.8±1.6) % (standard error), respectively.
Similarly to Fig. 8, Fig. 13 shows the HF partial column
scatter plot. No direct comparison should be made between
the HCl and HF scatter plots and data point distributions,
as ground-based observations of these two species are not
performed simultaneously, and HF is currently not available
from all sites involved in our study. We notice that the distribution of the 108 data points is already quite compact.
The linear regression yields a slope of 1.05, an intercept
of 0.43×1014 molecules/cm2 and a correlation coefficient of
0.96. Corresponding parameters indicate that the correlation is not improved when restricting the dataset to the 30
closer measurements in latitude (symbols with plusses), with
values of 0.94, 1.37×1014 molecules/cm2 and 0.96, respectively. Here again, this fitted function is compatible with the
1:1 line correlation, at the 95% confidence level Contrary to
the HCl comparisons, chemical activation cannot be invoked
to explain dissimilarities between in- and out-of-vortex air
masses, but the impact of vertical dynamical motion could
result in large partial column differences. Such situations
Atmos. Chem. Phys., 8, 6199–6221, 2008
might have been encountered for a series of points corresponding to winter-spring time measurements above highlatitude sites of the Northern Hemisphere. As per HCl (see
Sect. 4.1.6), the improvement noted for the mean fractional
difference, from (6.3 to 8.5) % to (1.2 to 4.4) %, is consistent
57
with a significant contribution of natural spatial variability
to the bias computed with the relaxed collocation criteria.
For HF, the upper limit bias between the ACE-FTS and the
ground-based
FTIR instruments is lower than 5%. Overall
56
conclusions are unchanged if measurements closer in time
are considered.
4.3
4.3.1
CFC-11 comparisons
FIRS-2
The CFC-11 comparison results are presented in Fig. 14.
There is a very good agreement below 16 km with differences
smaller than −10% (−20 pptv) from 12 to 16 km, with ACEFTS reporting slightly smaller CFC-11 vmrs than FIRS-2.
Above 16 km, the fractional differences increase with increasing altitude, up to ∼−87% at 19 km. It should be noted
that these differences consistently remain within the uncertainty estimates for the FIRS-2 profile.
4.3.2
Mark-IV
Figure 15 shows the results of the CFC-11 comparison. The
agreement is quite good. However, ACE-FTS vmr values are
systematically smaller than those of MkIV, with differences
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E. Mahieu et al.: Validation of HCl, HF, CCl3 F and CCl2 F2 from ACE-FTS
Fig. 14. Same as Fig. 6 but for comparison of CFC-11 (CCl3 F)
profiles
from FIRS-2 and ACE-FTS.
Figure 14. Same as Figure 6 but for comparison of CFC-11 (CCl3F) profiles from FIRS-2 and
ACE-FTS.
6215
Fig. 16. Same as Fig. 6 but for comparison of CFC-12 (CCl2 F2 )
profiles from FIRS-2 and ACE-FTS.
Figure 16. Same as Figure 6 but for comparison of CFC-12 (CCl2F2) profiles from FIRS-2
and ACE-FTS.
58
60
Fig. 15. Same as Fig. 7 but for comparison of CFC-11 (CCl3 F)
profiles from MkIV and ACE-FTS.
Fig. 17. Same as Fig. 7 but for comparison of CFC-12 (CCl2 F2 )
profilesFigure
from17.
MkIV
and ACE-FTS.
Same as Figure 7 but for comparison of CFC-12 (CCl F ) profiles from MkIV and
Figure 15. Same as Figure 7 but for comparison of CFC-11 (CCl3F) profiles from MkIV and
ACE-FTS.
2 2
ACE-FTS.
on the order of −10% above 12 km and increasing to larger
values (about −20%) below.
4.4
titude range 17–24 km, the differences decrease with increasing altitude from +48% (+108 pptv) to −160% (−91 pptv) at
the top of the comparison altitude range.
CFC-12 comparisons
4.4.2
4.4.1
FIRS-2
The ACE-FTS – FIRS-2 comparison for CFC-12 is shown
in Fig. 16. Here, the vmr profiles for ACE-FTS and FIRS2 have different shapes. The FIRS-2 profile has large uncertainty and shows only a slight decrease with increasing
altitude, while the ACE-FTS vmr profile is more similar to
that of CFC-11. Relative differences are positive (ACE-FTS
vmrs larger than FIRS-2) from 12 to 20 km, with values close
to +50% up to 17 km and decreasing quickly above. In the alwww.atmos-chem-phys.net/8/6199/2008/
Mark-IV
Lastly, the ACE-FTS – MkIV comparison for CFC-12 is
shown in Fig. 17. The differences are similar to the results
found for CFC-11, with ACE-FTS vmrs systematically lower
than MkIV but with maximum differences on the order of
−10%. These negative differences in the CFCs comparisons
with MkIV
are consistent with the low biases noted in the
59
comparison with FIRS-2.
Atmos. Chem. Phys., 8, 6199–6221, 2008
61
6216
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E. Mahieu et al.: Validation of HCl, HF, CCl3 F and CCl2 F2 from ACE-FTS
Conclusions
In this paper, we have compared ACE-FTS v2.2 products
with a series of available coincident or comparable profile or
column measurements performed from space, balloons and
from the ground, for HCl, HF, CFC-11 and CFC-12. Broad
latitudinal and time coverage has been achieved for the reservoir species, with co-located measurements obtained from
March 2004 to August 2007, from high-northern to highsouthern latitudes, including sub-tropical and mid-latitude
regions of both hemispheres.
For HCl, we have confirmed the very good agreement
found by Froidevaux et al. (2008) between the ACE-FTS
and MLS v2.2 data, when including the latest available 2007
coincidences. Related comparison of vmr profiles between
100 and 0.2 hPa (16 to 60 km) indicates very good consistency, with bias lower than 5%, and with no significant altitude pattern over this broad range of altitudes. Time series of monthly mean vmrs show very good agreement, in
latitude, altitude and time. Statistical comparison with 36
HALOE v19 coincident HCl measurements suggests a systematic bias between both instruments, with the ACE-FTS
vmrs 10 to 15% larger than those of HALOE over the whole
stratosphere. The variability captured by both space instruments is, however, in very good agreement.
ACE-FTS HCl vmr profiles have been further compared
with balloon-borne measurements. A single coincidence
with a SPIRALE high-vertical resolution measurement performed near 67◦ N in January 2006 is also included. A good
agreement (better than ∼20%) is found between retrieved in
situ HCl vmrs from 16 to 20 km and above 23 km. Below
16 km and between 20 and 23 km, we found the largest differences (ACE-FTS being higher), of more than 40%, and
thus larger than combined uncertainties of both experiments.
The analysis of the PV field does not suggest that large atmospheric inhomogeneities in sounded vortex air account for
the observed discrepancies, but the presence of a PSC detected in situ by SPIRALE may explain the disagreement in
the height range 20–23 km. Comparison with a single FIRS2 profile obtained near 68◦ N in January 2007 shows large
differences, from 0.1 to 0.7 ppbv (i.e., with ACE-FTS always
larger by at least 20%, and up to 65%, relative to FIRS-2)
in the 13 to 31 km altitude range. An ACE-FTS zonal mean
profile was compared with three MkIV observations obtained
in the fall of 2004 and 2005 around 35◦ N. Very good agreement to better than ±7% is obtained above 20 km and hence
lower than the MkIV estimated uncertainty of ±10%. The
agreement is less satisfactory at lower altitudes, where the
HCl vmrs decrease rapidly while the corresponding uncertainties for both instruments are rapidly increasing.
Finally, comparisons of stratospheric partial columns were
performed with NDACC FTIR data, collected over a wide
range of latitudes. To minimize the impact of spatial natural
variability of HCl on the computed differences, we have considered together coincident measurements taken within less
Atmos. Chem. Phys., 8, 6199–6221, 2008
than 24h and at maximum latitude difference of 200 km. We
found a compact correlation between ACE-FTS and gb-FTIR
data, with a correlation coefficient (R) of 0.96, a slope of 1.02
and an intercept of 2.25×1013 molecules/cm2 . The same
group of points suggests that ACE-FTS might be slightly biased high, with a mean fractional difference of (2.0±1.8) %
(standard error), at worst by about 4%.
The same set of coincident measurements from ACE-FTS
and HALOE was used for HF comparisons. On average,
they indicate that ACE-FTS provides similarly shaped profiles, but larger by 5 to 20% in the 15–49 km range, which
is in line with earlier HALOE-related intercomparisons discussed in Sect. 3.2. Both instruments show further evidence
of larger HF variability around 30 km, which is believed to
be a real geophysical characteristic of the data sets used here.
Similarly to the HCl comparison, the FIRS-2 vertical distribution systematically shows lower vmr values for HF (0.2 to
0.6 ppbv), with relative differences exhibiting similar vertical structure but lower amplitudes, generally between 20 and
50%. In contrast, zonal mean comparisons with MkIV data
yield good agreement above 19 km, the relative differences
being smaller than ±10%, i.e., in line with the 10% error
associated to these balloon-borne measurements.
ACE-FTS and gb-FTIR HF partial columns have also been
compared. As per HCl, only the tighter spatial coincidences
have been considered to determine the mean relative difference between both datasets and corresponding statistics, here
equal to (2.8±1.6) % (standard error). The scatter plot based
on the same 30 coincidences shows a compact correlation,
with R equal to 0.96, a slope and an intercept of 0.94 and
1.37×1014 molecules/cm2 , respectively.
For CFC-11 and CFC-12, there was less data available
for comparison with ACE-FTS. Single comparisons with a
FIRS-2 flight and zonal mean comparison with MkIV data
suggest however that the ACE-FTS vmr vertical distributions are reasonably good, although they generally seem to
be lower in most of the altitude range, i.e., between 12 and
20 km. However, the low number of coincidences for both
CFC-11 and CFC-12 limits the significance of these findings.
Overall, and when excluding the single SPIRALE and
FIRS-2 measurements, which may have sampled significantly different air masses than ACE-FTS, the various comparisons indicate a good agreement for HCl with MLS, the
NDACC FTIRs and MkIV, with averaged differences always
lower than 10%. Comparison with HALOE would suggest
larger positive values (10–15%), however HALOE profiles
are known to be biased low, so that the actual differences are
likely to be much smaller. For HF, we have less data available. Comparisons with the gb-FTIRs and MkIV also indicate agreement within 10%. Here again, HALOE indicate
larger HF differences (10–20%) whose magnitudes might
not be representative. Most of the differences are clearly attributable to the bias affecting the HALOE data. Hence, this
intercomparison exercise indicates a generally good agreement to better than 5–10% for HCl and HF, with available
www.atmos-chem-phys.net/8/6199/2008/
E. Mahieu et al.: Validation of HCl, HF, CCl3 F and CCl2 F2 from ACE-FTS
reference data sets, i.e., within the uncertainties affecting
both ensembles. It should be noted that these uncertainties
are valid for HCl and HF measurements taken down to about
20 km. Below this altitude, it is anticipated that the precision of the measurements will rapidly drop with decreasing
altitude and vmr values. The lowermost ACE-FTS measurements available for HCl and HF should therefore be considered with care by the data users. No significant latitude or
altitude difference was found when considering the various
comparisons, covering a broad range of latitudes and seasons. It is therefore possible to capture natural atmospheric
variability as well as particular events, using these measurements. Moreover, the results appear to be consistent over the
three years of ACE-FTS data available at the time of writing,
with no apparent degradation over time, allowing assessment
of longer-term changes. For CFCs, the limited number of
data sets for comparison did not allow us to derive statistically reliable results. Nevertheless, we estimated that the
differences stay within 20% in most of the altitude ranges
accessible to ACE-FTS, in particular for CFC-11.
Acknowledgements. Work at University of Liège was primarily
supported by the Belgian Federal Science Policy Office (PRODEX
Programme), Brussels. We thank the International Foundation High
Altitude Research Stations Jungfraujoch and Gornergrat (HFSJG,
Bern) for supporting the facilities needed to perform the observations. We further acknowledge the vital contribution from all colleagues in performing the ground-based observations used here. We
would also like to thank Olivier Flock and Diane Zander for programming and secretarial supports, respectively.
The Atmospheric Chemistry Experiment (ACE), also known as
SCISAT, is a Canadian-led mission mainly supported by the Canadian Space Agency (CSA) and the Natural Sciences and Engineering Research Council (NSERC) of Canada.
The authors thank the HALOE Science and Data Processing Teams
for providing the profiles used in this work.
All the ground-based FTIR stations operate within the framework of
the Network for the Detection of Atmospheric Composition Change
(NDACC, see http://www.ndacc.org), and are nationally funded and
supported.
The National Center for Atmospheric Research is supported by
the National Science Foundation. The NCAR FTIR observation
program at Thule, GR is supported under contract by the National
Aeronautics and Space Administration (NASA).
The University of Bremen acknowledges financial support by the
ESA project TASTE.
The support by the local Swedish Institute of Space Physics (IRF)
staff in Kiruna is highly appreciated.
Work at the Toronto Atmospheric Observatory was supported by
NSERC, Canadian Foundation for Climate and Atmospheric Sciences, ABB Bomem, Ontario Research and Development Challenge
Fund, the Premier’s Research Excellence Award, the University of
Toronto, and a grant from the CSA.
The NIWA contribution to this study work was conducted within
the FRST funded Drivers and Mitigation of Global Change programme (C01X0204). Support and logistics for the ground based
www.atmos-chem-phys.net/8/6199/2008/
6217
measurements FTIR at Arrival Heights was supplied by Antarctica
New Zealand. We would like to thank Greg Bodeker for allowing
us access to his “Potential Vorticity” database.
The SPIRALE balloon measurements could only be performed
thanks to the technical team (L. Pomathiod, B. Gaubicher, G. Jannet); the flight was funded by ESA and French space agency
CNES for the ENVISAT validation project; the CNES balloon
launching team is greatly acknowledged for successful operations.
A. Hauchecorne is acknowledged for making available the use of
MIMOSA advection model and F. Coquelet for useful help in the
PV calculations and ACE data formatting.
Work at the Jet Propulsion Laboratory, California Institute of
Technology, was done under contract with NASA. We thank the
Columbia Scientific Balloon Facility (CSBF) for the balloon flights
whose data are used in this work.
Cora Randall contribution was funded by NASA grant
NNG04GF39G. We would like to thank Lynn Harvey (LASP) who
processed all the ACE data into a suitable format for the ACE vs
HALOE comparisons.
Financial support by the EU-projects SCOUT, GEOMON and
HYMN is further acknowledged.
Edited by: A. Richter
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