Mass balance of the Antarctic ice sheet.

Abstract

The Antarctic contribution to sea-level rise has long been uncertain. While regional variability in ice dynamics has been revealed, a picture of mass changes throughout the continental ice sheet is lacking. Here, we use satellite radar altimetry to measure the elevation change of 72% of the grounded ice sheet during the period 1992-2003. Depending on the density of the snow giving rise to the observed elevation fluctuations, the ice sheet mass trend falls in the range -5-+85Gtyr-1. We find that data from climate model reanalyses are not able to characterise the contemporary snowfall fluctuation with useful accuracy and our best estimate of the overall mass trend-growth of 27+/-29Gtyr-1-is based on an assessment of the expected snowfall variability. Mass gains from accumulating snow, particularly on the Antarctic Peninsula and within East Antarctica, exceed the ice dynamic mass loss from West Antarctica. The result exacerbates the difficulty of explaining twentieth century sea-level rise.

Full text

Page 1

Mass balance of the Antarctic ice sheet
BY D. J. WINGHAM1,*, A. SHEPHERD2, A. MUIR1AND G. J. MARSHALL3
1Centre for Polar Observation and Modelling, University College London,
Gower Street, London WC1E 6BT, UK
2Centre for Polar Observation and Modelling, Scott Polar Research Institute,
University of Cambridge, Lensfield Road, Cambridge CB2 1ER, UK
3British Antarctic Survey, High Cross, Madingley Road, Cambridge
CB3 0ET, UK
The Antarctic contribution to sea-level rise has long been uncertain. While regional
variability in ice dynamics has been revealed, a picture of mass changes throughout the
continental ice sheet is lacking. Here, we use satellite radar altimetry to measure the
elevation change of 72% of the grounded ice sheet during the period 1992–2003.
Depending on the density of the snow giving rise to the observed elevation fluctuations,
the ice sheet mass trend falls in the range K5–C85 Gt yrK1. We find that data from
climate model reanalyses are not able to characterise the contemporary snowfall
fluctuation with useful accuracy and our best estimate of the overall mass trend—growth
of 27G29 Gt yrK1—is based on an assessment of the expected snowfall variability. Mass
gains from accumulating snow, particularly on the Antarctic Peninsula and within East
Antarctica, exceed the ice dynamic mass loss from West Antarctica. The result
exacerbates the difficulty of explaining twentieth century sea-level rise.
Keywords: Antarctica; sea level; mass balance; altimetry
1. Introduction
Duringthetwentiethcentury,therateofmeanglobalsea-levelrisewas1.8 mm yrK1
(Church & Gregory 2001). Remote satellite platforms offer the only prospect
for estimating the sea level contribution due to Antarctica. This may be achieved
through measurements of volume change (Wingham et al. 1998), of mass discharge
(Rignot&Thomas2002)andofgravitationalperturbations(Bentley&Wahr1998).
Today, there are limitations in both the scope and accuracy of each approach.
The rate of volume change is known for ca 70% of the grounded ice (Wingham et al.
1998), but the density at which that fluctuation has occurred is certain over a still
smaller region (Shepherd et al. 2002; Davis et al. 2005). The rate of glacier mass
discharge is known for ca 60% of the grounded ice (Rignot & Thomas 2002), but the
accuracy to which the atmospheric mass supply can be determined is limited by
decadal fluctuations in snow accumulation (Wingham et al. 1998). The change in
gravitationalattractioncanberesolvedforregionsoccupyingca10%ofthegrounded
Phil. Trans. R. Soc. A (2006) 364, 1627–1635
doi:10.1098/rsta.2006.1792
Published online 25 May 2006
One contribution of 14 to a Discussion Meeting Issue ‘Evolution of the Antarctic Ice Sheet: new
understanding and challenges’.
*Author for correspondence (duncan.wingham@cpom.ucl.ac.uk).
1627
q 2006 The Royal Society

Page 2

ice area (Wahr et al. 1998), but, while data on Greenland are available (Velicogna
etal. 2005), a comprehensivesurveyofperturbationsnearAntarctica isstill lacking.
Based on some of these methods, recent estimates of the Antarctic ice sheet
mass balance have placed it as a 60G76 Gt yrK1source (Wingham et al. 1998), a
26G37 Gt yrK1source(fromthemassbudgetdataofRignot&Thomas(2002))and
(for East Antarctica only) a 45G7 Gt yrK1sink (Davis et al. 2005) of ocean mass.
Together, these values provide Antarctic sea level contributions in the range
K0.12–C0.17 mm yrK1and improvement in certainty requires measurements with
increased scope or accuracy.
2. Methodology
We analysed 1.2!108European remote sensing (ERS) satellite altimeter echoes
to determine the change in volume of the Antarctic ice sheet from 1992 to 2003. By
using multiple orbit reference cycles (Zwally et al. 2002), we extend an earlier
survey (Wingham et al. 1998) in space to within, on average, 26 km of the ice sheet
margin, and in time to encompass 11 years of continuous measurement. For this
study, we used ERS-1 and ERS-2 WAP v. 3 altimeter data with DGME04 delft
precise orbits from October 1992 to February 2003. The data were separated into
orbit cycles of 35 days. Five ERS-1 orbits repeats and 16 ERS-2 orbit repeats were
selected as reference cycles. For each satellite and each reference cycle, dual cycle
cross-overs of elevation and power were formed and placed in 100 km2bins. The
elevation changes were corrected for covariance of trends in power and elevation
and the two satellites cross-calibrated following the method of (Wingham et al.
1998). We also investigated, separately, the trends of the atmospheric corrections:
none of these were significant. To edit the data, individual orbits or repeats with
gross errors were removed. We did not use the conventional ‘3-sigma’ edit on the
variance of elevation time series, for fear of removing the larger signals. Instead,
we used an edit on the magnitude and seasonality of elevation trends; time-series
with trends greater than 2 and 4 m yrK1were excluded in East and West
Antarctica, respectively, and all time-series with seasonal-cycle amplitudes over
1.2 m were removed. In addition, time-series with fewer than 20% of the possible
number of cross-overs in a 100 km2bin were also removed. Our survey includes
72% of the grounded ice sheet (8.5!106km2), omitting just 6% of coastal sectors
(0.8!106km2) where data are lost due to steep slopes, and 22% of the interior
(2.6!106km2), which lies beyond the latitudinal limit (81.68S) of the satellite
ground track.
Wefittedatrendandannualcycletotheelevationtimeseriesateach100 km2bin
to characterize their variance; an interpolation of the trend is shown in figure 1. To
determinetherateofelevationchangeofindividualicedrainagebasins(table1)and
thetrendoftheentireregionofcoverage(figure2),weaveragedthetime-seriesover
theirrespectiveareas.Indeterminingbasin-widetrends,wedidnotuseERS-1ifits
coverage was less than 85% of that of ERS-2 for fear of biasing the result by
relatively few ERS-1 observations. This principally affected basin H–J0. To correct
for the isostatic rebound of the continent we used a value (Nakada et al. 2000) of
1.7 mm yrK1. Our survey covers 85% of the East Antarctic ice sheet and 51% of
the West Antarctic ice sheet and includes basins missing from mass budget
compilations (Rignot & Thomas 2002).
D. J. Wingham and others
1628
Phil. Trans. R. Soc. A (2006)

Page 3

3. Results and discussion
Although our altimeter data are derived from the same source as those of Davis
et al. (2005), our analysis is at a finer resolution and our interpretation of snow
accumulation records is altogether different. By making improvements on the
spatial and temporal coverage of past surveys (Wingham et al. 1998; Davis et al.
2005), our survey reveals a clearer picture of changes of the Antarctic ice sheet.
In particular, the fine (10 km) spatial resolution is sufficient to distinguish
changes associated with distinct glacial systems. The draw down of the Pine
island, Thwaites and Smith glaciers in the Amundsen Sea sector (basin G–H) of
West Antarctica are prominent, as is the thickening of the Kamb ice stream
(basin E0–E00) at the Siple coast. These changes have been previously identified
(Anandakrishnan & Alley 1997; Shepherd et al. 2002), and their origin is related
to known ice dynamic disequilibria. Flow-related thinning in the coastal sections
K'
A'
A"
B
C
90˚
C'
D
D'
F'
F
E
D"
E"
E'
G
H
–270˚E
J
J'
J"
K
80˚S
70˚S
180˚E
150–150
Elevation rate
(mm yr–1)
A
0˚E
Figure 1. Rate of elevation change of the Antarctic ice sheet, 1992–2003, interpolated using a
Gaussian filter of radius 50 km.
1629
Mass balance of the Antarctic ice sheet
Phil. Trans. R. Soc. A (2006)

Page 4

Table 1. Antarctic drainage basin area, 1992–2003 elevation rate, 1979–2001 mean accumulation
rate (MAR) and 1992–2001 accumulation rate anomaly with respect to the MAR.
basin
area
(106km2)
observed area
(106km2)
elevation rate
(mm yrK1)
mean accumulation
rate (mm yrK1)
mean accumulation
rate anomaly
(mm yrK1)
K–K0
J00–K
J0–J00
J–J0
H–J
G–H
F0–G
F–F0
E00–F
E0–E00
E–E0
D00–E
D0–D00
D–D0
C0–D
C–C0
B–C
A00–B
A0–A00
A–A0
K0–A
WAIS
EAIS
AIS
0.24
1.59
0.8
0.24
0.28
0.43
0.13
0.06
0.19
0.49
1.55
0.28
0.13
0.74
1.15
0.7
1.29
0.22
0.42
0.59
0.19
4.16
7.54
11.7
0.22
0.97
0.07
0.19
0.12
0.4
0.11
0.04
0.19
0.18
0.8
0.26
0.06
0.67
1.08
0.63
1.27
0.14
0.37
0.55
0.16
2.09
6.4
8.49
23G3
5G1
24G4
91G4
164G8
K68G3
39G6
K58G7
K52G3
K11G3
0G1
1G2
K3G5
5G2
K1G3
47G4
10G1
17G4
K11G2
6G1
37G3
K7G1
7G1
5G1
444
156
494
915
1481
924
744
669
307
370
150
210
401
428
495
503
160
365
308
290
375
529
322
373
18
K1
K36
K37
K34
K19
26
K19
–4
–3
2
11
11
K20
K32
K16
3
1
K17
K9
23
K9
K8
K9
0.20
0.15
0.10
0.05
–0.05
–0.10
–0.15
–0.00
1992199419961998
year
200020022004
elevation change (m)
Figure 2. Elevation change of the Antarctic ice sheet, 1992–2003.
D. J. Wingham and others
1630
Phil. Trans. R. Soc. A (2006)

Page 5

of the Cook (basin D–D0) and Totten (basin C0–D) glaciers is also apparent. In
addition to these ice dynamic fluctuations, there are regions of thickening whose
patterns are correlated with that of mean accumulation (Vaughan et al. 1999).
The most striking examples include the east–west gradient across the Antarctic
Peninsula (basins J–J0and H–J0), the increase north of the coastal mountains of
Dronning Maud Land (basin K0–A0) and the increase coastward in Wilkes Land
(C–C0). Because these changes occur over slow-moving ice, we attribute them to
a contemporary snowfall fluctuation—accumulation higher than the long-term
discharge through flow. Overall, the data, corrected for isostatic rebound, show
the ice sheet growing at 5G1 mm yrK1.
To determine the change in mass requires knowledge of the density at which
the volume changes (figure 1) have occurred. However, of the 21 Antarctic
drainage basins included in our survey, we can confidently attribute the
fluctuation to changes in ice or snow at only four: basins G–H and E0–E00have,
predominantly, lost and gained ice, respectively, and basins J–J0and H–J have,
predominantly, gained snow. These fluctuations are each supported by a range of
either glaciological or meteorological observations. Elsewhere, signals of
thickening or thinning are correlated with flow, accumulation or neither, both
within and across basin boundaries. To convert the volume changes of such
basins to changes in mass requires either other data on, for instance, the
contemporary snowfall fluctuation, or a method by which the uncertainty may be
reasonably bound.
We considered the contemporary fluctuation in snow accumulation. We used a
21 year subset of data from the European Centre for Medium-range Weather
Forecasting (ECMWF) climate model reanalyses (ERA-40) to estimate changes
in net snow accumulation (precipitation minus evaporation) for the period
1979–2001. Prior to this epoch, the ERA-40 data is known to be less certain
(Marshall 2003). From the subset, we calculated the longest-term mean
accumulation rate (MAR) across the entire Antarctic ice sheet. As a check, we
compared the MAR to a map of net snow accumulation (NSA) computed from an
interpolation of in situ records (Vaughan et al. 1999). The MAR for Antarctica
was 373 mm snow yrK1and the root mean square departure of the MAR of the 21
separate drainage basins from the NSA record was 110 mm yrK1of snow . It is
important to note that, since the NSA record incorporates data representative of
fluctuations over a range of timescales, there is no reason it should match the
ERA-40 MAR, directly. Because contemporary fluctuations in accumulation will
affect a change in ice sheet volume only if they depart from the long-term mean
(Van der Veen 1993), we differenced the average ERA-40 accumulation rate over
the period of our satellite survey (1992–2001) from the MAR to estimate the
component of Antarctic elevation change due to snowfall (figure 3 and table 1).
This comparison differs from that of (Davis et al. 2005); that survey failed to
account for the long-term MAR.
The ERA-40 snowfall departure (figure 3) matches poorly the elevation change
recorded over the same period (figure 1). While it is possible that none of the
elevation change is due to a contemporary snowfall fluctuation, there is good
evidence to suppose that, for instance, growth of Dyer Plateau at the Antarctic
Peninsula is through precisely that mechanism (Thompson et al. 1994). In fact,
the sharp boundary in elevation change across Dyer plateau (figure 1) falls on the
drainage divide between the east and west coasts of the peninsula, where
1631
Mass balance of the Antarctic ice sheet
Phil. Trans. R. Soc. A (2006)