tc 5 1057 2011

tc 5 1057 2011
The Cryosphere, 5, 1057–1081, 2011
www.the-cryosphere.net/5/1057/2011/
doi:10.5194/tc-5-1057-2011
© Author(s) 2011. CC Attribution 3.0 License.
The Cryosphere
Spatial and temporal variability of snow accumulation rate on the
East Antarctic ice divide between Dome Fuji and EPICA DML
S. Fujita1 , P. Holmlund2 , I. Andersson3 , I. Brown2 , H. Enomoto4,1 , Y. Fujii1 , K. Fujita5 , K. Fukui1,* , T. Furukawa1 ,
M. Hansson2 , K. Hara6 , Y. Hoshina5 , M. Igarashi1 , Y. Iizuka7 , S. Imura1 , S. Ingvander2 , T. Karlin2 , H. Motoyama1 ,
F. Nakazawa1 , H. Oerter8 , L. E. Sjöberg3 , S. Sugiyama7 , S. Surdyk1 , J. Ström9 , R. Uemura10 , and F. Wilhelms8
1 National
Institute of Polar Research, Research Organization of Information and Systems, Tokyo, Japan
of Physical Geography and Quaternary Geology, Stockholm University, Stockholm, Sweden
3 Division of Geodesy and Geoinformatics, The Royal Inst. of Technology, Stockholm, Sweden
4 Kitami Institute of Technology, Kitami, Japan
5 Graduate School of Environmental Studies, Nagoya University, Nagoya, Japan
6 Department of Earth System Science, Faculty of Science, Fukuoka University, Fukuoka, Japan
7 Institute of Low Temperature Science, Hokkaido University, Sapporo, Japan
8 Alfred Wegener Institute for Polar and Marine Research, P.O. Box 120161, 27515, Bremerhaven, Germany
9 Department of Applied Environmental Science, Stockholm University, Stockholm, Sweden
10 Faculty of Science, Department of Chemistry, Biology, and Marine Science, University of the Ryukyus, Okinawa, Japan
* now at: Tateyama Caldera Sabo Museum, Toyama, Japan
2 Department
Received: 10 July 2011 – Published in The Cryosphere Discuss.: 8 August 2011
Revised: 1 November 2011 – Accepted: 7 November 2011 – Published: 28 November 2011
Abstract. To better understand the spatio-temporal variability of the glaciological environment in Dronning Maud Land
(DML), East Antarctica, a 2800-km-long Japanese-Swedish
traverse was carried out. The route includes ice divides between two ice-coring sites at Dome Fuji and EPICA DML.
We determined the surface mass balance (SMB) averaged
over various time scales in the late Holocene based on studies
of snow pits and firn cores, in addition to radar data. We find
that the large-scale distribution of the SMB depends on the
surface elevation and continentality, and that the SMB differs
between the windward and leeward sides of ice divides for
strong-wind events. We suggest that the SMB is highly influenced by interactions between the large-scale surface topography of ice divides and the wind field of strong-wind events
that are often associated with high-precipitation events. Local variations in the SMB are governed by the local surface
topography, which is influenced by the bedrock topography.
In the eastern part of DML, the accumulation rate in the second half of the 20th century is found to be higher by ∼15 %
Correspondence to: S. Fujita
([email protected])
than averages over longer periods of 722 a or 7.9 ka before
AD 2008. A similar increasing trend has been reported for
many inland plateau sites in Antarctica with the exception of
several sites on the leeward side of the ice divides.
1
1.1
Introduction
Surface mass balance of Antarctica
Sea-level rise has been a debated issue in recent climatological studies related to global warming (Lemke et al., 2007).
One of the main uncertainties arises from the still unknown
contribution of the Antarctic ice sheet (Alley et al., 2005).
Hence, assessing the mass balance and surface mass balance
(SMB) of the Antarctic ice sheet has been a major concern of
recent studies (Arthern et al., 2006; Chen et al., 2006; Davis
et al., 2005; Giovinetto and Zwally, 2000; Helsen et al., 2008;
Van de Berg et al., 2006; Velicogna and Wahr, 2006). In addition, several approaches for constraining the mass balance
of the Antarctic ice sheet are based on the interpolation of accumulation rates obtained from field data such as firn cores,
snow pits or stake readings, sometimes using background
Published by Copernicus Publications on behalf of the European Geosciences Union.
1058
S. Fujita et al.: Snow accumulation in Dronning Maud Land, East Antarctica
fields from satellite data to control the interpolation scheme
(Arthern et al., 2006; Giovinetto and Zwally, 2000; Vaughan
et al., 1999). However, large parts of the vast East Antarctic Plateau remain uncovered by the ground-based measurements needed for these continent-wide interpolations. Obtaining thorough data sets for the SMB of the East Antarctic
Plateau has been a priority in this regard. In the period of the
International Polar Year 2007–2009(IPY), several inland traverses were undertaken to achieve a range of scientific goals
including determining the SMB (e.g., Anschütz et al., 2009;
Holmlund and Fujita, 2009). A number of preliminary results have already been presented, in addition to those described in the present paper. An example of such efforts is
the Norwegian-USA traverse (IPY) through East Antarctica.
The traverse has provided new data sets for the SMB based
on ground-based accumulation measurements through large
parts of DML to the South Pole (Anschütz et al., 2009, 2011;
Müller et al., 2010).
Another important concern related to the SMB is whether
or not snowfall-driven growth of the East Antarctic ice sheet
mitigates recent sea-level rises. Bromwich et al. (2004)
used the mesoscale model MM5 as well as the so-called
dynamic retrieval method (DRM) to study spatial and temporal variability of Antarctic precipitation. They also estimated the redistribution of snow due to snow drift using
MM5 surface wind fields. Cullather et al. (1998) compared
the spatial and temporal variability of net precipitation (precipitation minus sublimation) derived from European Centre for Medium-Range Weather Forecasts (ECMWF) operational analysis data with a variety of glaciological and meteorological observations and data sets. Glaciological estimates of the Antarctic mass balance have been performed
repeatedly; over the last four decades many such compilations (e.g., Arthern et al., 2006; Giovinetto and Zwally, 2000;
Vaughan et al., 1999) have been presented, with continuously
increasing amounts of data and using increasingly sophisticated methods. Although considerable differences in the
results of regional investigations exist, most studies agree
that there has been a slight increase in Antarctic precipitation/accumulation during the past few decades (Lemke et
al., 2007). However, Monaghan et al. (2006) derived a 50year time series of snowfall accumulation over the Antarctic continent by combining model simulations and primarily
ice-core observations. They found that there has been no significant change in snowfall since the 1950s, which indicated
that Antarctic precipitation is not mitigating global sea level
rise as expected. A study using a stretched-grid atmospheric
general circulation model (GCM) by Krinner et al. (2007)
yielded results predicting an increase of 32 mm w.e. yr−1 in
the Antarctic mass balance until the end of the 21st century,
which represents an increase of about 21 %.
The Cryosphere, 5, 1057–1081, 2011
1.2
Earlier studies of regional SMB
Many regional investigations have identified an increase in
accumulation rate during the second half of the 20th century.
In DML, ice cores covering a time span of ∼1000 yr have indicated temporal variations of the accumulation rate. Oerter
et al. (2000) reported that accumulation rates decreased in
the 19th century and increased in the 20th century in Amundsenisen, covering a 10◦ W-10◦ E sector of DML. Hofstede et
al. (2004) demonstrated that the mean increase in the SMB
in DML during the early 20th century was the largest within
the past 1000 yr. A recent study by Igarashi et al. (2011)
produced a time series of accumulation rates at Dome Fuji
over the last 740 yr, and showed a remarkable resemblance to
the data presented by Oerter et al. (2000) and Hofstede et al.
(2004) near the EPICA DML site. A compilation of the 37-yr
history of the SMB at the South Pole (Mosley-Thompson et
al., 1999) suggested an increase in the annual accumulation
rate since 1965. At Dome C, Frezzotti et al. (2005) found a
recent accumulation rate increase to 32 kg−2 a−1 , which can
be compared to the long-term mean of 25.3 kg−2 a−1 (1815–
1998). They also reported a general increase in the accumulation rate at several drill sites along the transect from Terra
Nova Bay to Dome C. In their cores, the period 1966–1998
shows a 14 to 55 % higher accumulation rate than the period
1815–1998. Stenni et al. (2002) found that the accumulation
rate at Talos Dome had increased by 11 % during the 20th
century in comparison to the 800 yr mean. However, Frezzotti et al. (2007) reported no significant increase in the accumulation rate over the last two centuries near Talos Dome.
Yet Urbini et al. (2008) found significantly lower accumulation rates in the southwest of Talos Dome during the period
1835–1920 when compared with the period 1920–2001.
However, contrasting results have also been presented.
Karlöf et al. (2005) investigated accumulation rates around
“site M” (75.0◦ S, 15.0◦ E, see Fig. 1) in DML using firn
cores and pit studies. They reported that the accumulation
rate in the area has been stable over the last 200 yr. Isaksson
et al. (1996) observed an accumulation rate decrease over
the period 1932–1991 from a coastal core in DML and reported no change in accumulation rate for the period 1865–
1991, based on another core from the plateau (75◦ S, 2◦ E,
2900 m a.s.l.). In addition, Isaksson et al. (1999) found that a
general increase in accumulation rate, particularly in the latter part of the 20th century, was not necessarily the case for
the whole polar plateau of DML. More recently, Anschütz
et al. (2011) presented results from the Norwegian-USA scientific traverse. They reported that the largest changes seem
to have occurred in the most recent decades with accumulation rates over the period 1963–2007/08 being up to 25 %
different from the long-term record. They reported that there
was no clear overall trend; some sites showed an increase in
accumulation rate over the period 1963 to present while others showed a decrease. The data from almost all sites that
are 3200 m or more above sea level suggested a decrease
www.the-cryosphere.net/5/1057/2011/
°S
E
Plateau Station
NUS07-5
Fuji
3500
RT459
RT188
RT155
NUS07-3
RT103
DK190
3500
MP
DM
L-
2000
D
A38
2500
DM
L-
Mizuho
1000 km
A35
NUS07-2
A37
3000
E
°E
50
70
°S
M
FB0603
A28
DML-A
Nansenisen
NUS07-1
EPICA
DML
n
fro
H
la
el
tfj
Svea
e
m
ei
Wasa
°E
500
B
LDM
Syowa
Sør Rondane
Mountains
DML-C
1000
75 °S
Site 1
FB0601
A23
L
1500
S16
3000
NUS07-4
RT313
3700
MD550
MD364
30
°
°S
Route along the ice divide
Route south of the ice divide
Across-ice-divide survey
A part of JASE route
Dome
Major sites
Norweigian-USA 2007/2008
°E
80
°E
40
75
50
1059
20 °
E
S. Fujita et al.: Snow accumulation in Dronning Maud Land, East Antarctica
40
Troll
70 °S
0°
10 °E
E
20 °
30
°E
500 km
Fig. 1. Routes of the JASE traverse shown on a map of Antarctica. Surface elevation contour lines have a spacing of 500 m below 2000 m
and of 100 m above 2000 m. The underlying satellite image is the MODIS mosaic of Antarctica (Haran et al., 2005). The red trace shows
the route between S16 and Wasa. The blue trace shows the south routes (see text). Major sites are indicated by circular symbols (see also
Table 1). Sites for pit studies and firn core studies are indicated by red letters. The orange line at MP is the trace of the cross-ice divide
survey (see text). The black thick trace is also a part of the JASE traverse. The green dotted trace is the route of the Norwegian-USA traverse
in the same 2007/2008 season (Anschütz et al., 2011). Site names related to it are indicated with green letters. Light blue thin traces indicate
ice divides on the ice sheet surface. For convenience, we labelled the ice divides DML-A to DML-E.
in accumulation rate. Clearly, there are sites that showed no
particular trend at all, and we note that many of these sites are
located along the legs from Troll Station toward Plateau Station through site M, that is, along the route of the NorwegianUSA traverse.
1.3
Processes related to SMB
To form a better understanding of the SMB, we need to improve our knowledge on processes related to it, that is, the
components that affect it, and their nature, character and
amount. Until recently, it has always been assumed that precipitation on the Antarctic Plateau is almost entirely in the
form of diamond dust, which is produced by in situ nucleation of ice crystals in extremely cold air without any synoptic dynamical forcing (e.g., Bromwich, 1988; King and
Turner, 1997; Roe, 2005). However, both recent observawww.the-cryosphere.net/5/1057/2011/
tions (e.g., Reijmer and Van den Broeke, 2003; Fujita and
Abe, 2006) and model studies (e.g., Noone and Simmonds,
1998; Noone et al., 1999; Braaten, 2000; Schlosser et al.,
2008) have shown that the interior plateau is influenced by
the synoptic conditions in the coastal areas more strongly
than previously thought. The investigations indicated above
commonly show that several precipitation events occur per
year that are responsible for a large part (more than 50 %)
of the total annual precipitation on the inland plateau sites
of DML, based on automatic weather station (AWS) observations, overwintering observations and/or model investigations. Reijmer and Van den Broeke (2003), for example, indicated that several precipitation events occur per year that
can bring more than 50 % of the total annual precipitation
near EPICA DML. Fujita and Abe (2006) created a data set
of daily precipitation measurements at Dome Fuji for the
year 2003. They observed precipitation almost daily, with
The Cryosphere, 5, 1057–1081, 2011
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S. Fujita et al.: Snow accumulation in Dronning Maud Land, East Antarctica
Table 1. Major sites along the JASE traverse and related sites.
Site name
Lat. ◦ S
Long. ◦ a
Elevation(m)
H (m)b
S16
Mizuho
MD364
MD550
DF
69.030
70.697
74.008
75.676
77.317
40.052
44.274
42.996
41.539
39.703
589
2250
3347
3663
3800
350
2060
2716
2472
3028
DK190
MP
76.794
75.888
31.900
25.834
3741
3661
2919
2820
A38
A28
RT459
RT313
RT188
RT155
RT103
A35
75.287
74.862
77.376
77.961
77.161
76.869
76.762
76.066
18.421
14.742
37.932
32.624
29.426
29.270
27.248
22.459
3543
3466
3780
3620
3678
3701
3653
3586
2706
–
3333
3550
2574
2702
3019
–
A37
FB0603
75.654
75.117
19.240
9.724
3544
3300
–
–
A23
FB0601
75.168
75.247
6.493
4.844
3174
3090
–
–
EPICA DML
75.002
0.068
2890
2774
Wasa Station
Svea Station
IPY Site1
Site M
73.053
74.571
75.001
75.000
–13.374
–11.170
–10.121
15.000
292
1313
2528
3457
383
715
1603
–
Site L
NUS07-1
74.647
73.717
12.790
7.983
3420
3174
–
–
NUS07-2
NUS07-3
NUS07-4
NUS07-5
76.067
77.000
78.217
78.650
22.467
26.050
32.850
35.633
3582
3589
3595
3619
–
–
–
–
Note
Base of the Japanese team near the coast.
Mid-point between Mizuho and Dome Fuji
Dome Fuji Station: deep ice coring site (Watanabe et
al., 2003)
Science stop for installing an automatic weather station
Meeting point of the two teams. AWS JASE2007 was
installed.
Junction of the Swedish inbound and return trips
Junction of the Swedish inbound and return trips
Subglacial Lake Point
Southernmost point of the JASE traverse.
One of the junctions between the JASE traverse and the
Norwegian-USA traverse
Same as above
Firn coring site by the Alfred Wegener Institute, Germany in 2006
Junction of the Swedish inbound and outbound trips
Firn coring site by the Alfred Wegener Institute, Germany in 2006
2774-m long ice coring site (EPICA Community Members, 2006)
Base of the Swedish team
Swedish station
Science site
Science sites in Hofstede et al. (2004) and Isaksson et
al. (1996)
Junction with the Norwegian-USA traverse
Science sites in Anschütz et al. (2009, 2011) and Müller
et al. (2010)
Same as above. Location is close to A35 within 300 m.
Same as above
Same as above
Same as above
a Positive and negative longitude number mean East and West, respectively.
b H: ice thickness (m).
only 18 days of non-diamond-dust precipitation during an
observation period of 349 days. They found that half of the
annual precipitation was accumulated episodically by only
11 events during these 18 days. Noone et al. (1999) carried out a comprehensive study of DML precipitation using
ECMWF re-analysis data. They also found that a few synoptically induced precipitation events per year can yield a
large part of the total annual accumulation. More recently,
Schlosser et al. (2010) investigated high-precipitation events
at EPICA DML, during the period 2001–2006 using Antarctic Mesoscale Prediction System (AMPS) archive data. The
The Cryosphere, 5, 1057–1081, 2011
precipitation was found to be highly episodic, with, on average, approximately eight high-precipitation events per year
that are responsible for more than half of the amount of the
total annual accumulation. The duration of the events varied
from 1 day to about 1 week. On most the remaining days
in the year, however, the daily precipitation was about one
order of magnitude lower than that for the high-precipitation
events. The synoptic weather patterns causing these events
were directly associated with frontal cyclones systems in
only 20 % of the 51 cases investigated. The majority of the
events occurred in association with (blocking) anticyclones
www.the-cryosphere.net/5/1057/2011/
S. Fujita et al.: Snow accumulation in Dronning Maud Land, East Antarctica
and correspondingly amplified Rossby waves, which lead to
advection of warm, moist air from relatively low latitudes.
Therefore, these high-precipitation events appear to be one
of the keys for better understanding the SMB. In an earlier
study, the precipitation regime of DML was investigated by
Schlosser et al. (2008) using AMPS archive data. They investigated the temporal and spatial distribution of precipitation and compared the results to a mass balance map produced from glaciological data of western DML by Rotschky
et al. (2007). Schlosser et al. (2008) suggested that the mass
balance map and the AMPS mean annual precipitation field
showed similar patterns, which are mostly related to topography and prevailing wind systems. Precipitation is found
to generally decrease from the coast to the inland plateau.
Along the escarpment between the low-altitude coastal areas
and the interior plateau, local minima and maxima in precipitation correspond to the leeward and windward sides of
topographical ridges.
It has been recognized that precipitation has a major influence on the SMB, and that sublimation and redistribution
of snow by wind can create large differences between precipitation and mass balance. Sublimation can amount to up
to about 40 % of precipitation, especially in coastal areas
(Bromwich et al., 2004). Frezzotti et al. (2004) suggested
that wind-driven sublimation processes, controlled by the
surface slope in the wind direction, have a huge impact (up
to 85 % of snow precipitation) on the SMB. Redistribution of
snow after a snowfall is also an important factor in mass balance estimates, since it can mean either positive or negative
contributions to the mass balance of a given area. Therefore,
the role of wind is also one of the keys to better understand
the SMB. Earlier studies have shown that episodic precipitation events very often occur together with increases in wind
speed and temperature (e.g., Birnbaum et al., 2010; Fujita
and Abe, 2006; Schlosser et al., 2008, 2010). Birnbaum et
al. (2010) showed in Fig. 6 of their paper a time series of
daily precipitation rates from AMPS forecasts for 2002, together with periods identified as strong-wind events on the
basis of the 2 hour mean values of wind speed measured at
the AWS at EPICA DML. They stated that “not all strongwind events are associated with high daily precipitation rates
and vice versa”. Nevertheless, their Fig. 6 shows that many
strong-wind events are in fact associated with high daily precipitation. These earlier studies motivated us to search for a
link between the SMB and strong-wind events.
1.4
JASE traverse
To better understand the spatio-temporal variability of the
glaciological environment in DML, East Antarctica, a 2800km-long traverse was carried out by the Japanese Swedish
Antarctic Expedition (henceforth, JASE traverse) across
DML in austral summer 2007/2008 (Holmlund and Fujita,
2009). The SMB was one of the main scientific goals
and is discussed in the present paper in terms of spawww.the-cryosphere.net/5/1057/2011/
1061
tial distribution, temporal variation and related precipitation
regimes/processes. The routes included two major ice-coring
sites at Dome Fuji (Watanabe et al., 2003; Kawamura et al.,
2010) and at EPICA DML (Oerter et al., 2004; EPICA Community Members, 2006), and the major ice divide as well
as the branches of this ice divide between these two sites.
For a correct climatic interpretation of deep ice cores, better
understanding of the precipitation regimes/processes is very
important. In addition, dome summits and ice divides are often chosen as sites for ice coring. Thus, these ice-coring sites
were connected by the scientific traverse. The entire route
covered areas in both the Antarctic Southern Atlantic Ocean
sector and the Antarctic Indian Ocean sector, with a longitudinal coverage between ∼13◦ W and ∼42◦ E. We carried out
thorough investigations of the ice-sheet environment including the SMB, surface elevation, surface slope, AWS-based
wind field, surface snow reliefs, passive microwave remote
sensing data and radar-based ice thickness. For the SMB investigation, we analyzed the age and water equivalent depth
of isochrones based on data sets from snow pits, firn cores,
and radars.
2
2.1
Traverse route and methods of investigation
Traverse route
Figure 1 shows a map of DML with the traverse routes indicated. The names of important sites on the map are listed
in Table 1. The tracked-vehicle-based expedition used two
starting points, the S16 site near the Japanese Syowa Station
for the Japanese team and the Swedish Wasa Station for the
Swedish team. The JASE traverse was along the trace connecting several Antarctic stations, Syowa-Dome Fuji-EPICA
DML (Kohnen)-Wasa. The expedition began on 14 November 2007, for the Japanese team and on 5 December 2007, for
the Swedish team, with a plan to meet at the meeting point
(MP) on the polar plateau in late December, for joint scientific studies and exchange of crew members and scientific
instruments such as radars, microwave radiometers and GPS
receivers. Many of these scientific instruments were mounted
on the vehicles, and were operated continuously along the
traverse route. In addition, a new Argos-type AWS was installed at MP (Keller et al., 2010). The two teams met on 27
December at MP and began the return trip to their home stations, Syowa and Wasa, along routes partially different from
the incoming ones (blue traces in Fig. 1) for both scientific
and logistical reasons. The scientific reason was to investigate regions not only along the exact ice divides but also regions away from them. The logistical reason was that some
of the fuel depots were located away from exact ice divides.
The JASE traverse route between S16 and Dome Fuji is
located in the Shirase Glacier Drainage basin in the leg. We
refer to this leg as the Dome Fuji route, which has been used
since 1992 (e.g., Furukawa et al., 1996) for management of
deep ice coring at Dome Fuji. In the leg between Dome Fuji
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S. Fujita et al.: Snow accumulation in Dronning Maud Land, East Antarctica
MD550
4000
Dome
Fuji
Elevation (m)
MD364
3000
Ice divide
“DML-A”
Main ice divide
Dome Fuji route
(a)
DK190
MP
(b)
FB
A38 A28 FB
0601
0603
A23
EPICA
DML
South route
Dome
Fuji
RT RT RT
313 155 103 MP
A35
A37
A38
Site1
Mizuho
2000
Svea
S16
Wasa
1000
Bed elevation
Surface Elevation
7.9 kyr BP Layer
Sites for pit studies
Sites for firn core sampling
0
0
500
1000
1500
2000
500
2500
0
Distance from MP (km)
Distance from S16 (km)
Fig. 2. Cross section of the ice sheet along the JASE traverse routes. (a) The main ice divide route (see red trace in Fig. 1). (b) The south
routes (see blue traces in Fig. 1). Abscissas show (a) distance along the traverse from S16 toward Wasa Station and (b) distance from MP
along the south routes. The vertical exaggeration is 200 times. Vertical dashed lines show the location of major sites. Surface elevation
data (blue curves) are based on the digital elevation model of Bamber et al. (2006). A shallow isochrone within the ice sheet is shown as a
red profile based on analysis of the radar sounding data. It is dated as the 7.9 ± 0.5 kyr BP layer (see text). Bed elevation was derived from
the radar sounding data. For some locations where the bed signal was undetected in the JASE traverse, ice thickness data from an earlier
airborne radar sounding (Huybrechts et al., 2009) is shown as a thin dotted profile. Sites with symbols indicate sites of pit studies and/or firn
core sampling (see text).
and A28 (Fig. 1), the traverse is along the main ice divide.
In the leg between the A28 site and EPICA DML, the traverse route runs along one of three branches of the ice divide
originating at A28. For convenience, in the present paper, we
label the ice divides DML-A to DML-E, as shown in Fig. 1.
Among the three branches of the ice divides labeled DMLA, DML-B, and DML-C, DML-A is located at the southernmost, interior side of the Antarctic continent. Along the
main ice divide, the wind direction for strong-wind events is
between NE and ENE, as we will discuss later in this paper.
Thus, the NNE and SSW sides of the main ice divide often
represent the upwind and leeward sides, respectively, which
influences the depositional environment. For convenience,
we refer to the route between Dome Fuji and A28 along the
ice divide as the “main ice divide route” in this paper. We
refer to the blue trace in Fig. 1 as the “south route”, which
represents a depositional environment different from that of
the main ice divide. The south route is located in the area between the main ice divide and the Norwegian-USA traverse
2007/2008 (green dashed trace in Fig. 1). Figure 2 shows a
cross section of the ice sheet along the main ice divide route
and the south route, which gives a large-scale view of surface
and bedrock elevation along the traverses.
In addition to these long traverses, we created a survey
route orthogonal to the ice divide from a point 60 km NNE
of MP to a point 20 km SSW of MP. This was carried out to
obtain information on the environmental gradient across the
ice divide. In the present paper, we present data for a 40-km
long section of this “cross-ice divide” survey centred on MP
(orange trace in Fig. 1).
The Cryosphere, 5, 1057–1081, 2011
2.2
Methods of investigation of accumulation rate
Accumulation rate measurements were carried out using several ground-based methods such as snow pit studies, firn core
studies and analysis of isochronous events in radar signals.
This combination of methods, with supporting information
from the two deep ice-coring sites, provided datasets for the
accumulation rate along the traverse averaged over various
time scales. We note that a review by Eisen et al. (2008) provides an overview of the various techniques used to measure
the SMB as well as related difficulties and the limitations of
data interpretation.
2.2.1
Snow pit studies
Two 4-m deep pits were dug at a site near Dome Fuji and
at MP. In addition, a 2-m deep pit was dug at the DK190
site (Fig. 1 and Table 1). The pit near Dome Fuji was located at 77.298◦ S and 39.786◦ E, about 3 km from the station in the northeast direction, and was upwind of the prevailing wind direction to avoid possible chemical contamination from the station. Chemical constituents were analyzed with a depth resolution of 2 cm at the National Institute of Polar Research, Japan. By analysis of the major ions
such as non-sea-salt sulphate (henceforth, nss-sulphate), we
identified nss-sulphate peaks originating from the Agung (Indonesia) 1963 eruption (e.g., Pruett et al., 2004) and/or the
Pinatubo (Philippines) 1991 eruption (e.g., Legrand and Wagenbach, 1999) in order to estimate the average accumulation rates since deposition of related aerosols in Antarctica.
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S. Fujita et al.: Snow accumulation in Dronning Maud Land, East Antarctica
The Agung eruption occurred in March 1963, and subsequent deposition of nss-sulphate in Antarctica began with a
6 month time lag (e.g., Göktas et al., 2002; Traufetter et al.,
2004). Thus, we use the nss-sulphate peak for the Agung
1963 eruption as a time marker for the year 1964. Similarly, the deposit associated with the Pinatubo 1991 eruption
occurred in 1992–1994 (Cole-Dai et al., 1997). The deposition of the Pinatubo sulphate aerosol was delayed due to
the long transport route to high southern latitudes and its initial existence at high altitudes in the Antarctic atmosphere
(Cole-Dai et al., 1997). Therefore, this was used as a time
marker for the year 1993. Tritium peaks and physical stratification were also used to determine the depth/age relation.
Snow density was measured from the wall of the pit with
a depth resolution of 3 cm, which gave an estimate of the
water equivalent depth. Water equivalent depths for the nsssulphate peaks were used to derive accumulation rates averaged over 44 yr (1964–2007/2008) for the Agung 1963 eruption and over 15 yr (1993–2007/2008) for the Pinatubo 1991
eruption. We estimated that the major source of errors was
the spatially inhomogeneous deposition (e.g., Kameda et al.,
2008), which can affect the depth determination of a target
layer as thick as one year’s deposition. Naturally, errors for
averages over 44 yr for the Agung 1963 eruption are much
smaller than those for averages over 15 yr for the Pinatubo
1991 eruption.
2.2.2
Firn core studies
Firn cores with lengths of ∼10 m were sampled at the MP,
A35 and A28 sites during the 2007/2008 season by the
JASE traverse team (Figs. 1 and 2, and Table 1). In addition, data from 14-m-deep firn cores sampled at FB0603,
FB0601 and EPICA DML (Figs. 1 and 2, and Table 1) in
the 2004/2005 and 2005/2006 seasons by the Alfred Wegener Institute (AWI), Germany, were used in this study.
For these firn cores, dielectric profiling measurements (DEP)
(Moore et al., 1989; Wilhelms et al., 1998) were carried out
at the AWI to derive depth profiles of the high-frequencylimit electrical conductivity and density with a depth resolution of 5 mm. For all 6 firn cores, the depth corresponding
to the Agung 1963 eruption was determined from the electrical conductivity peak that is known to be correlated with
the nss-sulphate concentration (e.g., Wilhelms, 2005). For
some cores, the deeper signal associated with the Krakatau
1883/1884 eruption was used as a reference. For these firn
cores, the Pinatubo 1991 signal was not used because the firn
cores were too brittle in the shallowest few meters to maintain their shape for the DEP measurements. The accumulation rates as well as their errors were determined in a similar
way to those in the pit studies. Water equivalent depths were
first derived using the firn core density. These were then divided by the age of the sulphuric acid deposit produced following the eruption.
www.the-cryosphere.net/5/1057/2011/
2.2.3
1063
Radars
Three different types of radars were used for investigating
the accumulation rate. Table 2 gives a summary of the major
isochrones used in this study, the three types of radars, and
their spatial coverages. For convenience, we refer to the three
types of radars as (i) the Japanese GPR (ground penetrating
radar), (ii) Swedish GPR and (iii) POL179 radar.
The Japanese GPR is a short pulse radar. It was used along
the traverse routes between the S16 and MP sites. The antenna was suspended on the side of the tracked vehicle so
that it was always around 20 cm above the snow surface. In
this study, we analyzed a horizon dated as 1286±3 AD. It
was selected from many isochronous features for preliminary
analysis because it was one of the shallowest traceable layers that existed over long distances. The analytical procedure
was as follows. First, a data set for the two-way travel time
(TWT) of the electromagnetic waves was compiled. TWT to
depth conversion was carried out using the depth-density relation determined at the Dome Fuji coring site (Watanabe et
al., 1997). The wave velocity along the propagation path was
determined using the empirical relation between density and
wave velocity (Fujita et al., 2000; Kovacs et al., 1995). This
procedure enabled us to determine the depth of an observed
internal layer at the Dome Fuji coring site (Table 2). The
corresponding age of the layer was then assigned based on
dating of firn cores at Dome Fuji (Igarashi et al., 2011). Water equivalent depths for the layers were determined assuming the same density profile as that measured for the Dome
Fuji ice core, which was further cross-checked by the density
profile of the Dome Fuji pit obtained in the present study. Finally, the water equivalent depths were divided by the age of
the isochrone to derive the annual accumulation rate. In reality, depth-density profiles should have local variations, which
must be taken into account during calculation of the accumulation rate. However, we estimated that the error caused by
the local variability of the depth-density relations in traces
from the plateau near Dome Fuji is a few % at most. This
estimation is based on comparison between the water equivalent depth profile at Dome Fuji and EPICA DML (Ruth et al.,
2007). The difference was found to be at most ∼6 %, despite
a difference in elevation of ∼900 m. In addition, many pits
in the JASE traverse and surface snow measurements (Fujita
et al., 2008) showed little local variability.
The Swedish GPR is a step frequency continuous wave
radar that detects conditions at shallow (<74 m) depths.
Again, for preliminary analysis, we selected a single layer
from the many traceable layers at each location. A prominent
internal layer at a depth of 7.09 m at MP was first selected.
The average snow density from the MP firn core to this depth
(∼450 kg m−3 ) was used to calculate the depth of the layer
based on a wave propagation speed of ∼ 2.35 × 108 m s−1 .
The layer was dated to 79.3 yr old by scaling (in water equivalent depth) the Agung 1963 eruption signal found at 4.6 m
depth in the firn core to a depth of 7.09 m. This scaling
The Cryosphere, 5, 1057–1081, 2011
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S. Fujita et al.: Snow accumulation in Dronning Maud Land, East Antarctica
Table 2. A summary of the three major isochrones used in this study and the three types of radars.
Date of three major
isochrones
1286 ± 3 AD
79.3 ± 3 yr old before 2008
AD
7.9 ± 0.5 kyr before 2008 AD
Depth at major sites
Name of the radar used
in this paper
Type of radar
37.3 m at DF, 46.6 m at MP
Japanese GPR
7.9 m at MP
Swedish GPR
242 m at DF, 319 m at MP
POL179 radar
Short pulse radar
Pulse modulated radar
Specifications, manufacturer/model and/or
reference papers
Geophysical Survey Systems Inc. model GSSI SIR3000 with 270-MHz antenna
Resolution
Investigation depth
Scan rate
Samples per trace
Spatial coverage
0.4 m
74 m
5 Hz
2048
All legs between S16 and
MP including both the main
ice divide route and the
south route
Step frequency continuous
wave radar
Frequency: 0.1–3.0 GHz,
Band width:
600 MHz,
References: Hamran and
Aarholt (1993); Hamran et
al. (1995); Richardson et al.
(1997)
0.19 m
50 m
0.5–2 Hz
201
Legs from MP to Wasa
procedure means that we cannot compare values of the accumulation rate before and after the Agung 1963 eruption.
This 79.3 yr old layer was traced to a point at a longitude of
7.00◦ E which is close to the A23 site (Fig. 1 and Table 1).
In the leg with a longitudinal coverage between 7.00◦ E and
2.10◦ E, the same 79.3 yr old layer was not traceable. Instead,
a deeper layer dated tentatively to 95.5 yr was traced. Also,
in the leg with a longitudinal coverage between 2.10◦ E and
0◦ , a shallower layer dated tentatively to 57 yr was traced.
Dating of these layers was achieved by linear scaling of the
first isochrone of the 79.3 yr old layer at MP. Because of the
date scaling at MP, detailed discussion of the absolute values
of the accumulation rate is not possible. Instead, we use the
accumulation rate values of the firn cores and an earlier compilation of accumulation rate data (Rotschky et al., 2007) in
the same DML region as references, and adjusted the accumulation rate values to these. Overall, we use the Swedish
GPR data only for discussion of variability and not for absolute values or their temporal changes.
POL179 radar is a 179-MHz pulse-modulated radar to observe deeper into the interior of the ice sheet. It detects phase
and polarization both along and across the track. A 60 ns
pulse was used to detect internal layers, and a 500 ns pulse
to measure the thickness of the ice sheet. This radar was
operated continuously along the traverse route. Prominent
and persistent internal layers were traced. We used a layer
dated at 7.9 ± 0.5 kyr BP, based on the Dome Fuji ice core,
for analysis of the accumulation rate. This layer is deeper
than ∼200 m, but it is the shallowest layer that was traceable
The Cryosphere, 5, 1057–1081, 2011
Frequency: 179 MHz, Band
width: 14 MHz, Pulse width:
60 ns, Manufacturer: Sankosha Inc. Japan, Model: SKI05053
1.76 m
3500 m
1 Hz
6000
Legs between MD364 and
MP including both the main
ice divide route and the south
route
at most sites including Dome Fuji. For the pulse-modulated
radar, the receiver was switched off during pulse transmission in order to protect it from direct transmission. The
depth of this layer was 242 m at Dome Fuji and 319 m at MP.
Though there were many older and deeper prominent internal layers, we analyzed only this shallow layer because the
effect of vertical strain is more difficult to take into account
in deeper parts of the ice sheet. The 7.9 ± 0.5 kyr BP layer is
located at depths shallower than 10 % of the water equivalent
total thickness. Thus, the effect of strain is just a few percent when determining the accumulation rates from the water
equivalent depths of the layer. The analytical procedure was
as follows. First, a data set for the TWT of the electromagnetic waves was created. The depth of the internal layer was
accurately determined using a set of calibration data from a
down-hole radar target experiment at Dome Fuji (S. Fujita et
al., unpublished data, 1997). We used the TWT for a radar
target (ice coring drill) placed at accurately known depths in
the ice coring hole. In order to calibrate the TWT data, we
used electrical conductivity profile data from the Dome Fuji
Station ice core (Fujita et al., 2002a) to identify the depths of
major reflection horizons within the ice sheet. The calibrated
TWT allowed us to identify the depths of the reflecting horizons. The age of the layer was then determined using existing
dating data for the Dome Fuji ice core (Parrenin et al., 2007).
By dividing the water equivalent depth by the age and correcting for vertical strain, the average annual accumulation
rate was derived. To correct for the effect of vertical strain on
the water equivalent thickness, we used a thinning function
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S. Fujita et al.: Snow accumulation in Dronning Maud Land, East Antarctica
based on a 1-D ice flow model at Dome Fuji (Parrenin et al.,
2007). The model was designed specifically for ice coring
sites such as Dome Fuji and Dome C, and has the advantage
of being highly tuneable using information from ice cores.
Ruth et al. (2007) showed that a 1-D glaciological ice flow
model cannot be employed to determine a realistic chronology at the EPICA DML coring site for an ice time scale of up
to 105 yr, because of the complex history of ice flow and accumulation along the flow path upstream of EPICA DML. In
the present case, our analysis is limited to the summit region
between MD550 and MP (Figs. 1 and 2) and to the shallow
7.9 kyr BP layer. Because the horizontal ice flow velocity is
very small (<1 m s−1 ) (e.g., Motoyama et al., 1995; Huybrechts et al., 2009), we assume that a 1-D glaciological ice
flow model is still practical as long as we are willing to accept a small additional uncertainty. For example, the ratios
of the water equivalent depth for the 7.9 kyr BP layer to the
entire thickness at Dome Fuji and MP were 6.4 % and 9.3 %,
respectively. Considering the effect of vertical compression
(Fig. 5 in Parrenin et al., 2007), we applied a 3.5 % correction
for the entire leg to account for vertical strain. We estimate
that the error related to this thinning correction is at most
±1.0 %.
2.3
Methods of investigation of the wind field
The wind field along the JASE traverse routes was investigated in two ways. Strong winds over the Antarctic ice sheet
engrave the snow surface resulting in various types of reliefs, whose orientations can be used as proxy data for the
traces of strong wind events. Sastrugi are classified as erosional structures with sharp ridges. Large dunes with heights
of more than about 20 ∼ 30 cm and with smooth surfaces
are depositional structures produced by very strong winds in
the presence of snowfall. For both of these structures, the
long axis indicates the wind direction. Earlier data for Eastern DML and Enderby Land were compiled as a folio by
Kikuchi (1997). Birnbaum et al. (2010) investigated strongwind events and their influence on the formation of snow
dunes at EPICA DML. They reported that the formation of
snow dunes only occurred for wind speeds of >10 m s−1 at a
height of 2 m caused by a low-pressure system. In the discussion section of this paper, we will discuss how the orientation
of surface reliefs is related to strong-wind events and highprecipitation events. In this study, the orientation of the surface reliefs was measured using GPS compasses and/or magnetic compasses. The measurements were typically carried
out every 10 km. To maintain homogeneous data quality, the
same observer performed the measurements over a distance
as long as possible.
The wind conditions were further analyzed using meteorological data recorded by an AWS installed by the JASE
traverse team at MP. This is the only AWS providing data for
the inland plateau of DML between Dome Fuji and EPICA
DML. The AWS was set up by the Antarctic Meteorologiwww.the-cryosphere.net/5/1057/2011/
1065
cal Research Center and Automatic Weather Stations Project,
Space Science and Engineering Center, University of Wisconsin, Madison. The station name “JASE2007” was allocated to MP (Keller et al., 2010). The JASE2007 AWS has
been operational since January 2008, and the data are available online (http://amrc.ssec.wisc.edu/). The observational
items are temperature, air pressure, wind speed and wind direction. From these, we used wind speed and wind direction
to investigate the relation between them. In addition, earlier
AWS data at Dome Fuji, at MD364 (Takahashi et al., 2004)
and at EPICA DML (Birnbaum et al., 2010; Reijmer and Van
den Broeke, 2003) were also used to investigate the relation
between wind speed and direction.
2.4
Polarization ratio of satellite-based microwave
emissivity data at 6.9 GHz
Previous studies have shown that the polarization ratio of the
microwave brightness temperature is linked to snow layering (Surdyk and Fily, 1993, 1995). The passive microwave
data used in the present study were obtained from the Advanced Microwave Scanning Radiometer for EOS (AMSRE), which was developed by JAXA for use on board the EOS
satellite that has been in operation since 2002. The AMSRE sensor measures both vertical and horizontal polarizations
at 6.9, 10.65, 18.7, 23.8, 36.5 and 89.0 GHz. For the data
used in the present study, the incident angle was approximately 55◦ from the zenith. The spatial resolution varied
from 43 km at 6.9 GHz to 3.5 km at 89.0 GHz. The monthly
mean brightness-temperature data for June 2003 were used.
The polarization ratio, PR, is defined as follows:
PR =
TBv − TBh
TBv + TBh
(1)
where TBv and TBh are the vertical and horizontal components of the brightness temperature, respectively. We refer to
the polarization ratio at 6.9 GHz as PR6.9. Surdyk and Fily
(1993, 1995) found that the PR at frequencies below 10 GHz
is a good indicator of the amount of stratification in the snow
cover: the higher the PR, the larger the number of strata per
unit depth, which correlates with a lower accumulation rate.
We also note that microwave brightness temperature has little (less than a few kelvin) seasonal variability at frequencies
near 6.9 GHz (e.g., Surdyk, 2002). Thus, the spatial distribution of the PR6.9 from the monthly mean data for June 2003
represents data for a much longer time span.
2.5
Ice thickness and surface slope measurements
Ice thickness and surface slope data are used for analysis of
the conditions that influence snow accumulation. In addition to the POL179 radar, two more pulse-modulated radars
were used to observe ice thickness along the traverse. They
are a 179-MHz pulse-modulated radar (henceforth, VHF179
radar) and a 60-MHz pulse modulated radar (henceforth,
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S. Fujita et al.: Snow accumulation in Dronning Maud Land, East Antarctica
VHF60 radar) (Fujita et al., 1999; Matsuoka et al., 2002).
All three radars had a peak power of 1 kW and three-element
Yagi antennae, and used 500 ns or 1000 ns pulses. The
POL179 radar was used in the legs between S16 and MP,
including both the main ice divide route and the south route
(see Fig. 1). The VHF179 radar was used in the legs between
Wasa and MP. The VHF60 radar was used between EPICA
DML and Dome Fuji.
The surface slopes were determined using the digital elevation model (DEM) (Bamber et al., 2006) and are shown in
Figs. 3b, 4b and 9c. The surface slope is known to strongly
influence the spatial distribution of the accumulation rate at
various locations on the polar plateau (e.g., the Syowa-South
Pole traverse – Endo and Fujiwara, 1973, the Dome FujiSyowa route – Fujita et al., 2002b; Furukawa et al., 1996,
the DML-South Pole traverse – Anschütz et al., 2009, 2011;
Müller et al., 2010 and near Dome C and Talos Dome – Frezzotti et al., 2005, 2007) because the combination of the prevailing wind, the steepness of the slope and the local surface
topography determines the depositional environment.
3
3.1
Results
Accumulation rate
Annual accumulation rates averaged over periods after the
Agung 1963 eruption and the Pinatubo 1991 eruption are
listed in Table 3a and 3b. They are also displayed as symbols in Figs. 3a and 4a, which show data along the main ice
divide route and the south route, respectively. We note that
the value at FB0603 is lower than the surrounding firn core
data points by ∼10 kg m−2 or ∼20 %.
The blue traces in Figs. 3a and 4a show the annual accumulation rate determined using the Japanese GPR. They
show values averaged over 722 yr (1286–2008) along the ice
divide and the southern route. Several features can be identified in the data: (i) generally, the Dome Fuji area exhibits
low values; (ii) along the main ice divide route, the annual accumulation rate values are smoother and larger than for the
south route; (iii) there are large fluctuations of up to ∼20 %
along the south route and along the Dome Fuji route close to
MD550; (iv) values are generally lower along the south route
than along the main ice divide route.
The green traces in Figs. 3a and 4a show the accumulation rates determined using the Swedish GPR. As described
in Sect. 2.2.3, averaging was performed over a variable time
span of 57–95.5 yr. At the MP site, the radar result is identical to the 44 a average because the Agung 1963 layer was
used as a scaling reference for the dating procedure.
Figure 2a and b show the 7.9 ka BP layer and the elevation
of the bed in the cross section of the ice sheet. Despite the
large variation of ice thickness from ∼2500 to ∼3400 m in
the plateau region, the 7.9 ka BP layer is much smoother than
the bedrock elevation. The accumulation rates averaged over
The Cryosphere, 5, 1057–1081, 2011
7.9 ka were determined and are plotted in Figs. 3a and 4a. We
find that the values and variability of the 7.9 ka average are
very similar to those of the 722 a average, despite a difference
in age span of more than 10 times.
We compare the accumulation rate data from the present
study with data presented in earlier publications for the purpose of cross-checking. The full set of data used for comparison is listed in Table 3a. At Dome Fuji, using 36
bamboo stakes, Kameda et al. (2008) estimated the mean
accumulation rate over the period from 1995 to 2006 as
27.3 ± 0.4 kg m−2 a−1 . Figure 7 in Kameda et al. (2008)
shows this error, which is the standard error of the mean annual SMB for multi-year averages. This result is also plotted in Figs. 3a and 4a, and is close to the average accumulation rates after 1964 AD (the Agung 1963 eruption). Furthermore, Igarashi et al. (2011) estimated the average accumulation rates from AD 1888 to 1993, and from AD 1993
to 2001 to be 28.3 ± 0.4 and 29.5 ± 5.2 kg m−2 a−1 , respectively. These values are close to those obtained in the present
study for the average accumulation rates after 1964 AD (the
Agung 1963 eruption), after 1993 (the Pinatubo 1991 eruption), and the value for 1995–2006 from the bamboo stake
measurements (Kameda et al., 2008). In this way, the new
data from the JASE traverse are consistent with earlier studies at Dome Fuji on different time scales.
3.2
Wind field
Figure 5 shows the dominant orientation of surface snow reliefs between MD364 and Wasa. The orientations are plotted
as short thin lines with different colours on the map. At some
sites, two or more orientations were observed, in particular at
sites between A28 and A23 along the ice divide DML-A. In
the field, the most dominant orientation was determined first,
with secondary or less dominant orientations recorded when
necessary.
Figure 6a shows meteorological data from the JASE2007
AWS at MP for the year 2009. Wind speed is plotted versus wind direction at intervals of three hours. Wind speeds
above 10 m s−1 were only observed in 6 % of cases, with an
average wind direction of 70 ± 24◦ . Wind speeds between 5
and 10 m s−1 were observed in 36 % of cases, with an average wind direction of 76 ± 35◦ . About 58 % of wind speeds
were less than 5 m s−1 with an average wind direction of
97 ± 58◦ . The average wind-vector direction was also calculated from the meteorological data and was found to be 82◦
by an yellow arrow in Fig. 5. Near MP, the dominant orientation of surface snow reliefs (Fig. 5) was 70 ± 10◦ , which is
in agreement with the wind direction for strong-wind events
(>10 m s−1 ).
In addition to the meteorological data recorded at MP, we
examined meteorological data from the Dome Fuji, MD364
and EPICA DML sites using the data source described in
Sect. 2.3. Figure 6b shows data from the CMOS-type AWS at
Dome Fuji for the period between 1994 and 2001. Figure 6c
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S. Fujita et al.: Snow accumulation in Dronning Maud Land, East Antarctica
1067
Table 3a. Annual accumulation rates derived for Dome Fuji, DK190 and MP.
Period (AD)
1993–2008
1995–2006
1994–2001
1964–2008
1286–2008
1260–2001
–2008
Time span
15
11
7
44
722
741
7.9 ± 0.5 k
Site name
Data source
Dome Fuji
DK190
MP
25.6 ± 1.7 (kg m−2 a−1 )
27.3 ± 0.4
29.5 ± 4.2
28.8 ± 0.7
24.5 ± 0.7
25.5 ± 0.3
25.0 ± 1.3
34.1 ± 2.3
–
–
–
28. 7 ± 0.9
–
28.7 ± 1.5
41.9 ± 2.8
–
–
38.7 ± 0.9
33.1 ± 1.0
–
33.9 ± 1.7
Error
Pit studies (JASE 2007/08)a
Snow stake farm (Kameda et al., 2008)
Analysis of firn core (Igarashi et al., 2011)
Firn core and pit studies (JASE 2007/08)
Japanese GPR (JASE 2007/08)
Analysis of firn core (Igarashi et al., 2011)
Radar (JASE 2007/08) and Dome Fuji core
b
c
b
b
d
e
d
a Pit is located at 77.298◦ S and 39.786◦ E, and is ∼3 km from the Dome Fuji Station.
b Error range was assumed to be equivalent to 1 yr accumulation, with a confidence level of ∼83 %.
c Error is the standard deviation of the mean, with a confidence level of ∼68 %.
d Major source of error was assumed to be caused by 3 % of the density estimation within firn.
e Major source of error was assumed to be caused by 1 % of the density estimation within firn.
Table 3b. Annual accumulation rates derived from firn core studies at sites between A35 and EPICA DML.
Period(AD)
1964–2008
Time span
44
Site name
A35
A28
FB0603
FB0601
EPICA DML
39.2 ± 0.9
44.5 ± 1.0
38.0 ± 0.9
51.6 ± 1.2
73.1 ± 1.7
Data source is firn cores (JASE 2007/08, AWI 2003/04 and 05/06).
Error type is b.
shows data from the Argos-type AWS at MD364 for the period between 2001 and 2003. Table 4 shows a comparison
between the dominant orientations of surface snow reliefs
and the analyzed wind directions. The reliefs tend to be
aligned with the wind direction for strong-wind events, rather
than the average wind-vector direction.
3.3
PR6.9, which suggests a smaller number of strata per
unit depth, possibly linked to a higher accumulation
rate. The leeward side of the ice divide branches have
higher PR6.9, possibly linked to a lower accumulation
rate.
v. The route of the Norwegian-USA traverse(Anschütz et
al., 2011) is located almost entirely in a region with relatively high PR6.9 values, which should be taken into
consideration when attempting to determine the SMB.
Polarization ratio of satellite-based microwave
emissivity data at 6.9 GHz
Figure 7 displays the PR6.9 distribution, and its most important features can be listed as follows.
i. In general, the NE region exhibits lower PR6.9 values
than the SW region.
ii. In the area between Dome Fuji and MP, a steep PR6.9
gradient occurs across the ice divide, with the NE side
of MP having particularly low PR6.9 values. This suggests a rapid change in the stratification across the ice
divide at MP.
iii. The leg between A28 and EPICA DML and the SW side
of A28 are within the high PR6.9 zone, which suggests
a higher number of strata per unit depth, possibly linked
to a lower accumulation rate.
iv. There are several ice divide branches (DML-A to DMLE,). The NE side of the ice divide branches have lower
www.the-cryosphere.net/5/1057/2011/
The insights provided by the PR6.9 map into the distribution of the accumulation rate in this area will be discussed in
the Sect. 4.
4
Discussion
4.1
4.1.1
Spatial distribution of SMB at and around the ice
divides
Large-scale trend based on ground-based data
The accumulation rate is basically dependent on the elevation, continentality and geographical location of the sites
relative to the the ice divides in DML, which we will now
demonstrate using data. The elevation dependence is shown
in Fig. 8 both for the main ice divide route and for the south
route. It can be seen that the accumulation rate is lower at
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S. Fujita et al.: Snow accumulation in Dronning Maud Land, East Antarctica
Table 3c. Annual accumulation rates at several sites of the Norwegian-USA (NUS) traverse (Anschütz et al., 2011) in the vicinity of the
JASE traverse.
Period(AD)
1963a –2008
1259–2008
Time span
45
749
Site name
NUS07-1
NUS07-2
NUS07-3
NUS07-4
NUS07-5
55.9 ± 3.9
–
28.0 ± 2.0b
23.7 ± 1.7
–
17.5 ± 1.2
–
20.7 ± 1.4
26.0 ± 0.9
33.3 ± 1.2
a Anschütz et al. (2011) used 1963 as date of deposition for the Agung eruption. Thus the NUS accumulation rate data should be ∼2 % lower than the JASE data.
b Some doubt about peak identification.
Table 4. Comparison between orientation of surface snow features and wind field
Site
Orientation of
surface snow
features
(this work)a
Average direction
of wind vector
calculated from
meteorological data
Wind direction
for strong-wind
events
Station ID of AWS
or data source
Year of the
observational
data
EPICA DML
45◦ (this work)
57◦b
45◦
Utrecht University/ IMAU AWS9
1998–2000, 2002–05
MP
70◦
82◦
70 ±24◦c
ARGOS AWS No. 30305 (JASE2007)
2009
Dome Fuji
50◦
100◦
53 ±48◦d
CMOS AWS at Dome Fuji Station
1994–2001
MD364
102◦
119◦
120 ±22◦e
ARGOS AWS No. 8198
2002
Reference
Birnbaum et al. (2010),
Reijmer and Van den
Broeke (2003)
Keller et al. (2010)
Takahashi et al. (2004)
Keller et al. (2010)
a Mean value in the vicinity of each site, with errors of ±10◦ .
b Value at EPICA DML is cited from Birnbaum et al. (2010).
c An average wind direction for wind speeds above 10 m s−1 observed in ∼6 % of cases.
d An average wind direction for wind speeds above 8 m s−1 observed in ∼1 % of cases.
e An average wind direction for wind speeds above 10 m s−1 observed in ∼14 % of cases.
Table 5. Components of surface mass balance.
Surface accumulation
or surface ablation
Sub components
Surface accumulation
Precipitation due to highprecipitation eventsa
Precipitation due to diamond dust
Deposition of hoar frost
Deposition of drifted snow
Sublimation
Erosion due to snow drift
Surface ablation
a Major (50–80 %) component of precipitation in polar plateau of DML.
higher elevation. Another important trend is that the accumulation rate is lower for the south route than for the main ice
divide route. This situation can be clearly seen by comparing
Figs. 3a and 4a. Also, in Fig. 8a, the data along the main
ice divide and along the south route are clearly distributed at
different levels. The data from the Norwegian-USA travese
(Anschütz et al., 2011) are also listed in Table 3c for comparison. The values for sites NUS07-2 to NUS07-5 are almost as
low as those for the south route, confirming the continentality
trend. In addition, the data along the main ice divide is stable
The Cryosphere, 5, 1057–1081, 2011
and smooth (Figs. 3a and 8a) whereas that along the south
route is subject to large fluctuations (Figs. 4a and 8a). The
main ice divide and dome have singular features corresponding to unique ice sheet glaciological conditions (ice flow, surface topography etc.), so it seems quite natural that smoother
SMB results would be found compared to the sloped ice sheet
surface of the south traverse. Another large-scale trend is that
along the ice divide branch between the A28 site and EPICA
DML, the accumulation rate fluctuates. Such a pattern is also
visible on the accumulation rate map compiled by Rotschky
et al. (2004, 2007). We also note that in the leg between A28
and A23, the accumulation rate is lower than that obtained
by a linear interpolation between the accumulation rates on
the main ice divide route and near EPICA DML (see Figs. 3a
and 8a).
The gradient of the accumulation rate versus distance
along the main ice divide is −0.02 (kg m−2 a−1 ) km−1 (decreasing toward higher elevation) for the leg between Dome
Fuji and MP in Fig. 3a. Also, the gradient of the accumulation rate versus elevation along the main ice divide is −0.04
(kg m−2 a−1 ) m−1 (decreasing toward higher elevation). To
better understand the gradient of accumulation rate across the
ice divide, data from the cross-ice divide survey at MP was
analyzed. The accumulation rate along a 40-km leg is shown
in Fig. 9a, together with information on surface elevation,
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S. Fujita et al.: Snow accumulation in Dronning Maud Land, East Antarctica
1069
Longitude (º E)
39.7
35
30
25
20
15
10
5
0
100
(a) Annual accumulation rate (left axis)
-2
-1
Accumulation rate (kg m a )
80
(i) Recent data measured from pits, cores or snow stakes
Average over 11a (1996-2006) at DF 36 snowstake farm (Kameda et al. 2008)
Average over 15a (from Pinatubo 1991 eruption to 2008)
Average over 44a, 42a or 40a (from Agung 1963 eruption to 2008, 2006 or 2004)
(ii) Radars
Average over 57 ~ 95.5a from the Swedish GPR (see text)
Average over 722a (1286-2008) from the Japanese GPR
Average over 7.9 (±0.5) ka from the POL179 radar
60
40
Dome Fuji route
4
Along the ice divide
DML-A
Along the main ice divide
20
3
(b) Surface slope (right axis)
2
2000
0
(c) Bed elevation (left axis) DK190
-3
Elevation (m)
1
0
Surface slope (10 )
No data for
internal layers
along this leg
A23
MP
A38
1500
A28
FB
0603
1000
FB
0601
EPICA
DML
500
0
MD550
800
Dome Fuji
1000
1200
1400
1800
1600
2000
2200
Distance from S16 (km)
Fig. 3. Annual accumulation rates over various time scales are shown with indicators of the depositional environment along the main route
of the traverse. The abscissa represents distance from S16 along the traverse route. Details are as follows. (a) Annual accumulation rate
averaged over various time scales. Pit studies and firn core studies provided accumulation rates averaged over 44 yr and/or 15 yr (see text).
Also shown is the annual accumulation rate averaged over 11 yr from 1996 to 2006 (Kameda et al., 2008) from a stake farm with 36 stakes at
Dome Fuji. Subsurface radars provide annual accumulation rates averaged over 57–96 yr, ∼722 yr and 7.9 k yr. Details are given in the text.
(b) Surface slope at each point along the route was calculated using the digital elevation model of Bamber et al. (2006). (c) Bed elevation
derived from radar sounding.
surface slope and bed elevation (Fig. 9b, c and d, respectively). The accumulation rate data were again derived from
the Japanese GPR and the POL179 radar data that give a 722
a average and a 7.9 ka average, respectively. The gradients
across the ice divide are steep, −0.30 (kg m−2 a−1 ) km−1
(decreasing toward the inland part of the ice sheet) for the
722 a average and −0.18 (kg m−2 a−1 ) km−1 for the 7.9 ka
average. To further clarify these results, a contour map was
made using data for the annual accumulation rate averaged
over 722 a for an area between Dome Fuji and MP, including the cross-ice divide survey at MP, and this is shown in
Fig. 10. Because our purpose was to visualize large-scale
trends in the gradient, for most of the traverse routes the original data was smoothed over a 40-km distance to reduce fluctuations. For the 40-km-long cross-ice divide traverse at MP,
a regression line was used. It can be seen that the gradient in
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the vicinity of MP is much steeper than that in the vicinity of
Dome Fuji. The reason for this will be discussed in the next
section.
4.1.2
Large-scale trend inferred from passive
microwave data
To further clarify the large-scale trend in the accumulation
rate, data from the passive microwave measurements are useful. The data features itemized in Sect. 3.3 will now be addressed individually.
i. In general, the NE region exhibits higher PR6.9 values
than the SW region.
ii. In the area between Dome Fuji and MP, a PR6.9 gradient occurs across the ice divide. In fact, the PR6.9
The Cryosphere, 5, 1057–1081, 2011
1070
S. Fujita et al.: Snow accumulation in Dronning Maud Land, East Antarctica
Longitude (º E)
30
-1
25
20
-2
(a) Annual accumulation rate (left axis)
Dome
Fuji
RT313
RT188
RT103
MP
A35
A37 A38
40
20
3
(b) Surface slope (right axis)
2
1
0
0
(c) Bed elevation (left axis)
-3
2000
Surface slope (10 )
Elevation (m) Accumulation rate (kg m a )
35
1500
1000
500
and 8a). Moreover, we found that the received radar
signals from within the shallow (∼200 m) part of the
ice sheet were weaker by 5–10 dB than those along the
main ice divide (data not shown). These data imply that
the effect of wind on the surface snow strata causes a
reduction in TBh . This hypothesis also explains why
PR6.9 is very high in the SE of EPICA DML where the
downslope katabatic wind is expected to be stronger. To
further examine this possibility, we need to compare the
number of buried strata in different regions.
iv. The eastern and north-eastern sides of the ice divide
branches (from DML-A to DML-E) tend to have higher
accumulation rates, whereas the opposite sides tend to
have lower accumulation rates.
0
400
200
0
200
Distance from MP (km)
Fig. 4. Annual accumulation rate over various time scales are
shown with indicators of the depositional environment along the
south route. Again, surface slopes and bed elevation are shown as
in Fig. 3. The abscissa indicates distance from MP along the traverse route. All other items and symbols are the same as in Fig. 3.
Fluctuations of the accumulation rate and surface slope are much
larger than those along the route in the main ice divide.
distribution agrees well with the distribution of the accumulation rate shown in Fig. 10, suggesting that PR6.9
is well correlated with the accumulation rate in this region, at least qualitatively. At MP, the steep PR6.9 gradient across the ice divide agrees well with that of the
accumulation rate, as seen in Figs. 9 and 10. These
facts suggest that the main ice divide in DML is a location where a rapid change in the SMB occurs.
v. The route of the Norwegian-USA traverse is almost entirely on the side with relatively high PR6.9 values.
This means that the data from this traverse reflect a depositional environment characterized by relatively high
PR6.9 values and hence relatively low accumulation
rates.
In summary, the PR6.9 map provides insights into the distribution of snow strata in this area and its association with
the accumulation rate and presumably dune formation. Qualitatively, the PR6.9 distribution agrees well with the accumulation rate data in the vicinity of the main ice divide. In the
vicinity of EPICA DML, PR6.9 is likely to be affected by an
increased roughness and/or increased number of strata due
to the higher frequency of dunes per unit thickness of firn.
Further work should include an analysis of local variability, quantitative analysis, and the development of theoretical
models and algorithms to derive the accumulation rate from
the PR data.
4.1.3
iii. The leg between A28 and EPICA DML is within the
high PR6.9 zone, which is possibly linked to a lower
accumulation rate. However, Fig. 3 shows that the accumulation rate in this area is higher than that along
the main ice divide. Since the PR at frequencies below
10 GHz has been found to be a good indicator of the
number of strata in the snow cover (Surdyk and Fily,
1993, 1995), this implies that there must be some other
factors causing the large number of strata in this area. A
plausible explanation is the frequent occurrence of dune
formation events. Birnbaum et al. (2010) investigated
dune layers from past formation events in nine 5-mlong firn cores adjacent to EPICA DML. They identified 6–12 buried snow-dune layers per core, suggesting
an unexpectedly large stratification. Indeed, snow stratification is more disturbed by wind in this area than it is
in the main ice divide. As can be seen in Fig. 5, multiple
orientations of snow surface reliefs are present. In addition, the accumulation rate is highly variable (Figs. 3a
The Cryosphere, 5, 1057–1081, 2011
Local-scale variability
We next examine local variability of the annual accumulation
rate. In addition to the large-scale trend discussed above, local topography has a strong influence on local variability. On
this scale, we find that there is an anticorrelation between the
accumulation rate and the surface slope along the JASE traverse (Figs. 3, 4, 8 and 9). This suggests that snow is more
easily deposited on a relatively flat surface, particularly if it
is somewhat concave (see locations at −12 km and +10 km
in Fig. 9a, b for example). We suggest that one of the major
controlling factors of local variability is the surface slope, as
pointed out in earlier studies. In addition, surface slope is
highly correlated to bedrock topography, as can be seen from
Figs. 3, 4 and 9. Thus, local variations in the accumulation
rate are naturally preserved over time. That is, locally high
or low accumulation sites tend to remain so over long time
scales. In this study, we observed that the spatial variabilities
of the 722 a and 7.9 ka average accumulation rates are very
similar, both along the main ice divide (Fig. 3a) and along the
www.the-cryosphere.net/5/1057/2011/
20 °
E
E
30
°
°E
40
3700
°E
MD550
MD364
W
50
Dominant orientation for
surface snow reliefs
such as sastrugis and/or dunes
2nd dominant orientation
3rd or 4th dominant orientation
Suggested windfield
which engraved surface snow
Long-term average of wind
direction calculated from
the meteorological data
3500
Dome Fuji
0°
20 °
°E
10 °W
°S
75
50
1071
10 °E
S. Fujita et al.: Snow accumulation in Dronning Maud Land, East Antarctica
DK190
80
°S
Ice divides
3500
3000
A35
MP
A37
3000
2500
A38
E
M
L-
DM
2500
LD
°E
EPICA
DML
LDM
fje
nt
fro
Svea
e
im
He
B
Sør Rondane
Mountains
500
DML-C
40
1500
1000
lla
A23
L
Nansenisen
S
75 °
Site 1
A28
DM
2000
DML-A
Wasa
500 km
10 °E
20 °
E
30
°S
0°
10 °W
°E
Troll
70
Fig. 5. Dominant orientation of surface snow reliefs such as sastrugis and dunes observed along the traverse routes between MD364 and
Wasa. Orientations are plotted as thin lines on the map. At some sites, two or more orientations were observed, in particular at sites between
A28 and A23. The dominant orientation is shown as red symbol markers. The second and lesser orientations are shown as green and blue
markers, respectively. Thick black arrows are the suggested directions of the strong winds (>∼10 m s−1 ) that caused the surface snow reliefs.
Yellow arrows represent the orientation of the average wind field at MD364, DF, MP and EPICA DML, calculated from the meteorological
data. For MD364, DF and MP, the yellow arrows show the directions of the average wind vectors. Details are given in Table 4. At EPICA
DML, the yellow arrow represents the long-term average wind direction (Birnbaum et al., 2010; Reijmer and Van den Broeke, 2003). Bold
blue dashed curves indicate ice divides.
south route (Fig. 4a). This is basically due to preservation of
the accumulation pattern over these time scales. To determine the depositional history in more detail would require a
knowledge of the ice-flow trajectory in these regions.
4.2
4.2.1
Influence of strong-wind events on spatial
distribution of SMB
Reasons to expect a link between SMB and
strong-wind events
We next discuss the relation between strong-wind events observed in the data (both AWS and snow surface reliefs) and
snow accumulation. Earlier papers by Schlosser et al. (2008,
2010) provided useful summaries of the current understanding of the relation between precipitation and SMB in DML.
Table 5 gives a summary of the SMB components in Antarctica, based on the results of earlier studies (e.g., Bromwich,
1988; Bromwich et al., 2004; Schlosser et al., 2008, 2010).
Generally, on the Antarctic ice sheet, the SMB is the differwww.the-cryosphere.net/5/1057/2011/
ence between the amount of surface accumulation and ablation. Accumulation mechanisms include precipitation, hoarfrost deposition, and deposition of snow due to snowdrift,
whereas ablation mechanisms include sublimation and wind
erosion due to snowdrift. Sublimation can occur both during
and after snowfall and snowdrift. Among the many factors
influencing the SMB of the Antarctic ice sheet, precipitation
is recognised as the most important component.
As summarized above and in the introduction, the SMB
is not simple to determine because the roles of its components can vary both spatially and temporally. Nevertheless,
it should be emphasized that episodic precipitation events
are in many cases associated with increased wind speed and
temperature (e.g., Birnbaum et al., 2010; Fujita and Abe,
2006; Schlosser et al., 2008, 2010; Hirasawa, 2010), implying synoptic-scale advection of air masses from lower latitudes. Fujita and Abe (2006) presented time-series data
for precipitation events at Dome Fuji for 2003. We compared their data with meteorological data (Japan Meteorological Agency, 2005) obtained at Dome Fuji during the
The Cryosphere, 5, 1057–1081, 2011
1072
S. Fujita et al.: Snow accumulation in Dronning Maud Land, East Antarctica
(b)
(a)
(c)
Site: Dome Fuji
Year: 1994-2001
Height at 2 m
Site: MP
Year: 2009
Height at 3 m
Site: MD364
Year: 2001-2003
Height at 3 m
Wind speed (m s-1 )
20
15
10
5
0
270
0
90
180
270 270
0
90
180
270 270
0
90
180
270
Wind direction (º)
Fig. 6. Relationship between wind speed and direction at the three AWS sites along the JASE traverse. (a) Data at MP during the year 2009.
The observational data is from the AWS JASE2007. Data selected at three hourly intervals were used. Of the measured events, 6 % have
wind speeds of more than 10 m s−1 , with an average wind direction of 70◦ (±24◦ , standard deviation). (b) Data at Dome Fuji during the years
from 1994 to 2001 (Takahashi et al., 2004). Data at hourly intervals were used. Of the measured events, 1 % has wind speeds of more than
8 m s−1 , with an average wind direction of 53◦ (±48◦ ). (c) Data at MD364 during the years from 2001 to 2003 (Keller et al., 2010). Data at
three hourly intervals were used. Of the measured events, 14 % have wind speeds of more than 10 m s−1 , with an average wind direction of
120◦ (±22◦ ).
same time period and the results are shown in Fig. 11.
Daily (more accurately, 24 h) precipitation (Fujita and Abe,
2006) is plotted versus wind speed (Fig. 11a) and direction
(Fig. 11b). Figure 11a shows that high-precipitation events
are associated with strong-wind events in most cases. Most
high-precipitation events occurred with a limited range of
near-surface wind direction centered on 55◦ (±25◦ ). This direction is the same as that of the strongest winds observed
in meteorological data over a much longer time span from
1994 to 2001 (see Fig. 6b and Table 4). This implies that
in many cases strong winds directly distribute the precipitation during high-precipitation events. In addition, highprecipitation/strong-wind events are characterized by advection of maritime air masses from relatively lower latitudes
(e.g., Birnbaum et al., 2010; Schlosser et al., 2010; Hirasawa
et al., 2000). Thus, these events are keys for understanding
the distribution of maritime moisture onto the ice sheet surface. Although in some cases, strong-wind events are not directly accompanied by snow precipitation, strong winds can
redistribute snow soon after it is deposited. Therefore, we
consider strong-wind events to have an important influence
on the SMB distribution. In lower-elevation regions further
from the ice divides, katabatic winds become progressively
stronger and thus have a larger influence on the depositional
environment, particularly in terms of the redistribution of
The Cryosphere, 5, 1057–1081, 2011
drifted snow. These effects have been discussed in detail in
earlier papers (e.g., Frezzotti et al., 2005, 2007; Urbini et al.,
2008).
4.2.2
Interpretation of surface snow reliefs
We now examine the relationship between the wind field associated with strong-wind events and the spatial distribution
of the SMB. A question arises as to how the dominant orientations of the surface snow reliefs reflect the wind field.
Although the orientation of surface relief may not necessarily represent the persistent prevailing wind direction, we
contend that it is not simply associated with the most recent
storm. This is supported by the fact that the azimuthal dependence of AMSR-E microwave emissivity exhibits little seasonality (S. Surdyk, unpublished work). However, since the
observational data used in the present study were obtained
within a limited time period during an inland traverse, a more
comprehensive analysis of satellite remote sensing data is required to address this question. In this regard, useful information can be found in the AWS data shown in Fig. 6. There
is a sharp peak in the wind speed - direction plot, suggesting
that the relief orientations are persistent. The wind direction during stronger wind events should have a larger effect.
Less strong winds with directions deviating from those of
www.the-cryosphere.net/5/1057/2011/
20 °
E
E
°E
40
30
°
Polarization ratio at 6.9 GHz
3500
500 km
MP
3000
E
A35
A37
DM
L-
3000
A38
2500
M
DML-A
EPICA
DML
D
L-
Nansenisen
1500
fj
nt
ro
Svea
He
B
LDM
DML-C
Sør Rondane
Mountains
1000
ef
im
S
la
el
A23
L
75 °
Site 1
A28
DM
2500
2000
°E
Long-term average of wind
direction calculated from
the meteorological data
DK190
MD364
40
Windfield suggested in
Figure 5
3700
°E
S
°
80
3500
MD550
50
W
Dome
Fuji
0°
20 °
°S
Plateau Station
1073
10 °W
75
°E
50
10 °E
S. Fujita et al.: Snow accumulation in Dronning Maud Land, East Antarctica
Wasa
500
10 °E
E
20 °
30
°
°S
0°
10 °W
E
Troll
70
Fig. 7. Distribution of the polarization ratio of passive microwave data at 6.9 GHz. Data were obtained from the Advanced Microwave
Scanning Radiometer for EOS (AMSR-E), which was developed by JAXA for use on board the EOS satellite that has been operating since
2002. Previous studies (Surdyk and Fily, 1993, 1995) suggested that the polarization ratio at frequencies lower than 10 GHz is an indicator
of the number of layers per unit depth of strata to a depth of ∼2 m. Lower/higher values mean fewer/more layers in the strata, which would
qualitatively suggest that the accumulation rate is higher/lower. In the area between Dome Fuji and MP, the distribution of the polarization
ratio closely resembles that of the accumulation rate shown in Fig. 10. The ice divide branch DML-A between site A28 and EPICA DML is
within an area of higher polarization ratio. In addition, the legs of the Norwegian-USA traverse from Troll Station to Plateau Station is also
within an area of higher polarization ratio.
the strongest winds can still redistribute snow but have less
ability to engrave the snow surface. Therefore, we assume
that the dominant orientations of the surface snow reliefs
“most probably” represent the wind field associated with the
strongest winds, as seen in Fig. 6.
4.2.3
Direction of the wind field that engraved the snow
surface
Based on the surface snow reliefs, we deduced the directions of the wind fields that engraved the snow surface, and
these are shown as thick black arrows in Fig. 5. Near ice divides, the directions are around ENE, so that the wind clearly
crosses the ice divides. Along the route between A28 and
A23, snow reliefs with multiple different orientations were
observed. This suggests that the wind in this area was variable, at least for some period before the observations were
carried out. Since all of the observations in this area were
performed by the same individual, fluctuations in the data
quality are unlikely to be a factor here. As was pointed out in
Sect 4.1.2(iii), the strata in this area exhibited different characteristics to those along the main ice divide. Thus, we hywww.the-cryosphere.net/5/1057/2011/
pothesize that the multiple orientations of the surface reliefs
are typical features of the snow surface in this area.
At MP, Dome Fuji and EPICA DML, the directions of the
strongest near-surface winds agree well with the dominant
orientations of the surface snow reliefs. They deviate from
the average wind vectors indicated by yellow arrows in Fig. 5
toward the northeast or even further northwards. At MD364,
the observed orientation of surface snow features is ∼102◦
which is within the range of variation of the wind direction
for strong-wind events, 120◦ ± 22◦ (see Table 4). We note
that this site is strongly influenced by katabatic winds.
Finally, the thick black arrows in Fig. 5 represent the most
probable directions of the strongest wind at each site, are
also consistent with the AWS data. Most high-precipitation
events occur when the wind has these directions, at least at
Dome Fuji and presumably at other sites. The SMB in DML
is highly influenced by these near-surface wind directions, as
will be further discussed below.
The Cryosphere, 5, 1057–1081, 2011
1074
S. Fujita et al.: Snow accumulation in Dronning Maud Land, East Antarctica
Cross-ice-divide survey
(a)
Accumulation rate
(kg m -2 a-1)
-1
-2
40
44 a average
7.9 ka average
722 a average
(a)
38
36
34
32
30
40
3660
(b)
3655
(b)
A23
3650
-3
FB0601
FB0603
A28
A38
A35
MP
EPICA DML
Along the ice divide
DML-A
the tes
ng
u
Alo th ro
u
so
DK190
0
2.5
Dome Fuji
20
Surface slope (10 )
-3
the ivide
ng
Alo n ice d
i
ma
42
Along the ice divides
Along the south routes
2.0
3645
1.0
(c)
0.5
0.0
1500
(d)
1000
1.5
1.0
500
0.5
-20
NNE direction
0.0
3800
3600
3400
3200
3000
-10
0
10
MP
20
Bed elevation (m)
Surface slope (10 )
60
76.034º S
25.391º E
75.888º S
25.834º E
75.740º S
26.268º E
Surface elevation (m)
Accumulation rate (kg m a )
80
Latitude and Longitude
Measurements from pits and cores
44-40 a average since Agung 1963
15 a average since Pinatubo 1991
Along the ice divides
722 a average from GPR
57 – 96 a average from GPR
Along the south routes
722 a average from GPR
57 – 96 a average from GPR
SSW direction
Distance from MP (km)
Elevation (m)
Fig. 8. Values of accumulation rate are shown versus site elevation.
Panel (a) shows data selected from Figs. 3a and 4a. The group in
the upper left is data from sites along the main ice divide between
Dome Fuji and A28. The group at the lower left side is data from
sites along the south route between Dome Fuji and A38. The group
on the right side is data from sites along the ice divide branch DMLA between A28 and EPICA DML. Panel (b) shows surface slope.
4.2.4
Widespread strong upslope winds in DML during
strong-wind events
Earlier studies have also shown that strong-wind events are
often associated with wind directions between north and east.
Watanabe (1978) identified two different wind systems using
data for 1977 at Mizuho Plateau in DML: one is almost always directed approximately 60-90◦ counterclockwise from
the downslope direction, while the other has a larger counterclockwise tilt, even pointing upslope in the dome area at
high latitudes. Watanabe (1978) suggested that the former
represents the katabatic wind which prevails over the gently sloping (2 ∼ 3 × 10−3 ) plateau area, while the other is
caused by severe snowstorms characterized by strong winds.
In addition, Kikuchi (1997) found that the wind fields during blizzards had upslope components and were widely observed in an area between 30◦ E and 50◦ E in DML. Birnbaum et al. (2010) suggested that all strong-wind and, hence,
The Cryosphere, 5, 1057–1081, 2011
Fig. 9. Annual accumulation rate for the 40-km-long cross-ice divide survey at MP. (a) Annual accumulation rates averaged over
7.9 ka (red trace) and 722 a (blue trace) are determined from subsurface radar data. They are compared with the average over 44 a
at MP. Also shown are (b) surface elevation, (c) surface slope, and
(d) bed elevation. Decrease in accumulation rate from the northern coastal side of the ice divide toward the southern interior side.
The annual accumulation rate is locally higher at locations with flat
or concave surface topography, as indicated by thin vertical dashed
lines. Similarly, the annual accumulation rate is locally lower at
locations with steep surfaces or a convex surface topography.
all barchan-type dune formation events at EPICA DML identified in a 7 yr period were caused by the influence of a
low-pressure system. They also found that in the majority
of strong-wind and dune formation events, the near-surface
wind turned counterclockwise. Birnbaum et al. (2010) further suggested that enhanced katabatic flow is not the reason
for the unusually high near-surface wind speeds at EPICA
DML, which is in accordance with the findings by Van As et
al. (2007) that the largest near-surface wind speeds at EPICA
DML are caused by strong large-scale forcing. These earlier
studies and the thick black arrows in Fig. 5 suggest that the
northeastern sides of the ice divides are the windward sides
during strong-wind events, where upslope wind often occurs.
The strong winds cross the ice divides and blow down their
southern and southwestern slopes.
www.the-cryosphere.net/5/1057/2011/
40
35
°E
°E
S. Fujita et al.: Snow accumulation in Dronning Maud Land, East Antarctica
30
26
28
28 RT
103
°E
40
32
3500
34
3400
28
36
30
38
E
MP
30
°
35
°
E
100 km
008
7/2
RT
188
28
30
°S
200
US
26
3700
3600
75
°E
RT
24 26 313
way
Nor
28
30
32
3600
3700
30
28
Dome Fuji
24
26
75
°S
Fig. 10. Map of annual accumulation rate averaged over 722 a, derived from the GPR data. Colour scale image with bold red contours and red letters shows the distribution of the accumulation rate
in kg m−2 a−1 . Surface elevation of the ice sheet is also shown by
thin gray contour lines. The purpose of this map is to visualize the
large-scale spatial distribution of the accumulation rate in this area.
For this purpose, the original data was smoothed over a distance of
40 km to reduce fluctuations. Annual accumulation rates averaged
over 749 a at the NUS07-2 and NUS07-5 sites are listed in Table 3c
for comparison.
4.2.5
Large-scale distribution of SMB at and around ice
divides
We hypothesize that many of the features of the SMB and
PR6.9 distributions are explainable primarily by strong-wind
and high-precipitation events. These events are often associated with advection of air masses from relatively low latitudes inland across the ice divides. Because of the upslope
direction of the near-surface winds, such air masses release
most of their moisture due to orographic lift on the windward sides of the ice divides. After the winds cross the ice
divides, the leeward side basically corresponds to the rain
shadow; subsequent adiabatic warming of dry air can occur for downslope winds in the leeward area. Multiple ice
divides along paths of strong winds can make the air mass
progressively drier. The relatively low accumulation rate in
the leg between A28 and A23 (Figs. 3a and 8a) can be understood in terms of the geographical location of the sites in
DML. The ice divide branch DML-A is located on the leewww.the-cryosphere.net/5/1057/2011/
1075
ward side of the two ice divides DML-C and DML-B, and is
thus in their rain shadow. It seems likely that the snow reliefs
with multiple orientations along this leg are caused by the
complex wind field on the lee of these multiple ice divides.
The escarpment between the low-altitude coastal areas and
the interior plateau causes local minima and maxima in precipitation, which correspond to the leeward and windward
sides of topographical ridges. This situation was also studied by Schlosser et al. (2008) based on Antarctic Mesoscale
Prediction System (AMPS) archive data. An interesting feature is the strong PR6.9 contrast along the Heimefrontfjella
(Fig. 7). It implies that there is a high-accumulation-rate
corridor at the foot of the Heimefrontfjella, with the interior of the plateau having a lower accumulation rate. Indeed,
the Heimefrontfjella follows the strong wind direction. The
SMB at the foot of the polar plateau is high (∼200 ±60
kg m−2 a−1 ) whereas that on the polar plateau is low (∼60
±20 kg m−2 a−1 ) near Site 1, (Richardson et al., 1997).
Apart from precipitation due to high-precipitation events,
several other components in Table 5 contribute to the SMB.
Some of these have a larger effect further from the ice divides
at lower elevations on the polar plateau. For example, several papers have pointed out that wind-driven ablation is determined by the surface slope along the wind direction (e.g.,
Frezzotti et al., 2004). Frezzotti et al. (2004) investigated
the SMB along a transect from Terra Nova Bay to Dome C
in East Antarctica. They found that the measured maximum
snow accumulation rate is well correlated to firn temperature.
They suggested that wind-driven sublimation processes, controlled by the surface slope in the wind direction, have a huge
impact (up to 85 % of snow precipitation) on the SMB. They
further suggested that the snow redistribution process is local and has a strong impact on the annual variability of accumulation rate. Analogous phenomena would be expected
to occur in DML. Determining the role of wind-driven sublimation processes in DML requires an analysis of the wind
system (e.g., Van den Broeke and Van Lipzig, 2003), including both strong-wind events and katabatic winds, the local topography of the ice sheet surface and the orientation of snow
surface reliefs.
4.3
Increase in accumulation rate during the 20th
century
Figures 3a, 4a and 9a show a comparison of the annual accumulation rate over different periods of time within the
late Holocene. We find that in the ∼500-km-long leg between Dome Fuji and A35, the average accumulation rates
after 1964 AD (the Agung 1963 eruption) and/or after 1993
(the Pinatubo 1991 eruption) are significantly higher than accumulation rates averaged over longer periods (722 a and
7.9 ka). These data suggest an increase in the accumulation
rate, at least during the second half of the 20th century, in the
sector between 40◦ E and 22.5◦ E.
The Cryosphere, 5, 1057–1081, 2011
1076
S. Fujita et al.: Snow accumulation in Dronning Maud Land, East Antarctica
(b)
24 h mean wind speed (m s-1)
24 h precipitation (mm w.e.)
(a)
2.0
1.5
1.0
0.5
0.0
0
Marker size shows
amount of the 24 h
precipitation (mm w.e.)
12
10
2
4
6
8
10
-1
24 h mean wind speed (m s )
2.0
1.5
0.5
0.1
0.01
8
6
4
2
0
270
0
90
180
24 h mean wind direction (º)
270
Fig. 11. Relation between high-precipitation events and strong-wind events at Dome Fuji Station in a period from February 2003 to January
2004. The amount of precipitation each 24 hours was measured (Fujita and Abe, 2006). Wind speed and direction was measured at a
height of 10 m above the ground (Japan Meteorological Agency, 2005). Each data point represents an average over 24 h. Correlations were
then investigated. (a) Relation between 24-h precipitation (in mm, water equivalent) and 24-h-mean wind speed. High-precipitation events
are associated with strong-wind events in most cases. (b) Relation between 24-h-mean wind speed (same as in (a)) and 24-h-mean wind
direction. Size of the marker represents the amount of precipitation. Most high-precipitation events occured with a limited range of wind
direction centered at 55◦ (±25◦ ). This direction agrees well with the direction of the strongest winds (see Fig. 6b and Table 4).
Contrasting results have been reported for the legs of
the Norwegian-USA scientific traverse in the vicinity of the
JASE traverse routes. Anschütz et al. (2011) investigated
the spatio-temporal accumulation pattern based on volcanic
signatures in ice-core records. They investigated 13 firn
cores from the Norwegian-USA traverse including five sites
(NUS07-1 to 07-5) in Fig. 1. Major volcanic eruptions were
identified and used to assess century-scale accumulation rate
changes. They reported that the largest changes seemed to
occur in the most recent decades with the accumulation rate
in the period 1963–2007/08 being up to 25 % different from
the long-term record. They also reported that there was no
clear overall trend; some sites showed an increase in accumulation rate over the period 1963 to present while others
showed a decrease. The data from almost all sites that are
3200 m or more above sea level suggested a decrease in accumulation rate, including sites NUS07-1 to 07-5. Some of
their data are given in Table 3c for comparison to the data
of the JASE traverse . From the viewpoint of the influence
of strong-wind events on the spatial distribution of the SMB,
we note that all of the sites on the Norwegian-USA traverse
are located on the leeward side of the ice divides.
As described in Sect. 1.2, there have been many regional
studies in Antarctica that reported an increase in the SMB
during the 20th century. In the majority of earlier reports and
also in the present study, a trend towards increasing accumulation rates during the 20th century is commonly found for
the polar plateau, near Dome Fuji, EPICA DML, sites along
the ice divide between them, the South Pole, Dome C and
Talos Dome. However, no significant change was reported
for other sites, mostly along the legs of the Norwegian-USA
The Cryosphere, 5, 1057–1081, 2011
travese connecting Troll Station, A28, Plateau Station and
further inland. Because these sites are all located on the leeward sides of ice divides, we hypothesize that the locations of
these sites possibly mask any increase in accumulation rate.
Even if moisture transport toward the interior increases, it is
plausible that the majority of the moisture is released due to
the windward effect. To further investigate spatially inhomogeneous changes in the SMB, we suggest that cross-ice
divide surveys connecting the windward and leeward sides
would be effective.
5
Concluding remarks
In the JASE traverse, we investigated spatial and temporal
variability of the ice sheet environment in the sparsely explored inland plateau area of East Antarctica. The major
findings of the present study are summarized as follows.
1. On the inland plateau of DML, the prevailing wind direction associated with strong-wind events agreed well
with the orientation of surface snow reliefs. We suggest
that high-precipitation events associated with strongwind events have a major influence on the spatial distribution of the SMB. Strong winds often have upslope
components in DML causing advection of air masses
from relatively low latitudes over DML. It is suggested
that strong winds with upslope components release their
moisture on the windward side of the ice divide and the
leeward side is then exposed to drier air. As a result,
a different SMB is found on the windward and leeward
sides of the ice divides. Although there are several other
www.the-cryosphere.net/5/1057/2011/
S. Fujita et al.: Snow accumulation in Dronning Maud Land, East Antarctica
components comprising the SMB (see Table 5), highprecipitation events with strong winds seem to be the
most influential. The effect of wind-driven ablation is
something that needs to be assessed in the future.
2. In the scenario described above, large-scale variations
in the SMB depend on surface elevation, continentality
and location of sites with respect to the ice divides in
DML.
3. Local variations in the SMB are essentially governed
by the local surface topography, which in turn is influenced by the bedrock topography. Thus, the spatial pattern of the accumulation rate was unchanged over the
investigated periods along the main ice divide route and
the south route. Spatial variability of the accumulation
rate is smaller along the ice divide than in regions away
from the ice divide, suggesting an advantage of using
ice divide areas for studying temporal variations in the
paleoclimatic signals from ice cores.
4. In the eastern part of DML at longitudes from ∼15◦ E to
∼40◦ E, the accumulation rate in the second half of the
20th century is found to be higher by ∼15 % compared
to averages over longer periods of 722 a and 7.9 ka. This
recent increase in accumulation rate is consistent with
reports of studies on many sites in the inland plateau of
East Antarctica. However, some studies have indicated
insignificant increases at sites commonly in the lee of
ice divides. We suggest that the geographical location of
these sites on the leeward side of the ice divide may lead
to any increase in the accumulation rate being masked.
The increase in the accumulation rate in the second half
of the 20th century is a topic that should be examined
by climatologists in the context of climate change and
global warming.
5. In addition to the new SMB data, a new data set for ice
sheet thickness was produced as shown in the figures.
This will be used for a future international compilation
of an ice sheet topography map. Moreover, a new data
set was produced for snow surface reliefs, and meteorological data is available from the JASE2007 AWS at
MP.
6. The polarization ratio at 6.9 GHz derived from the passive microwave data is found to be well correlated with
the accumulation rate data in the vicinity of the main
ice divide, at least from a qualitative point of view. This
provides insights into the large-scale trend of the accumulation rate. However, near EPICA DML, PR6.9 is
likely to be affected by increased roughness and/or increased number of strata due to the higher frequency
of dunes per unit thickness within the firn. Based on
the results of previous studies on the polarization ratio
(Surdyk and Fily, 1993, 1995), PR6.9 is thought to be a
good indicator of stratification in the snow cover.
www.the-cryosphere.net/5/1057/2011/
1077
Acknowledgements. The JASE traverse was organized by several
organizations both in Sweden and Japan. The National Institute
of Polar Research (NIPR), Tokyo and the Swedish Polar Research
Secretariat (SPRS) managed the logistics in Antarctica. Science
management was a collaborative effort of NIPR, Stockholm
University, the Royal Institute of Technology in Stockholm and
individuals from several universities and institutes in Japan. The
JASE traverse is one of the research projects being undertaken by
the Japanese Antarctic Research Expedition “Studies on systems
for climate change and ice sheet change, by introducing new
observational methods and technologies”. This work was carried
out under the umbrella of TASTE-IDEA within the framework of
IPY project 152. This work is also a contribution to ITASE. The
authors appreciate the support of the Automatic Weather Station
Program for the JASE2007 AWS and associated data, NSF grant
number ANT-0944018. Thanks are extended to T. Kameda for
arrangement of the AWS for the JASE team. AMSR-E data was
provided by JAXA/EORC as a part of the GCOM-W project.
The traverse was fully supported by the teams of the 48th and
49th Japanese Antarctic Research Expeditions led by H. Miyaoka
and S. Imura, respectively. Special thanks go to the logistics
members, S. Gunnarsson, H. Kaneko, T. Karlberg, P. Ljusberg and
K. Taniguchi and the medical doctors, S. Eriksson and N. Shiga,
for their very generous support during the traverse. We greatly
appreciate constructive reviews from two anonymous reviewers.
This research was supported by the Swedish Research Council
(VR) and by a Grant-in-Aid for Scientific Research (A) 20241007
from the Japan Society for the Promotion of Science (JSPS).
Edited by: M. Van den Broeke.
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