© 2008 Nature Publishing Group
Recent Antarctic ice mass loss from
radar interferometry and regional
ERIC RIGNOT1,2,3*, JONATHAN L. BAMBER4, MICHIEL R. VAN DEN BROEKE5, CURT DAVIS6,
YONGHONG LI6, WILLEM JAN VAN DE BERG5AND ERIK VAN MEIJGAARD7
1University of California Irvine, Earth System Science, Irvine, California 92697, USA
2Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California 91109, USA
3Centro de Estudios Cientiﬁcos, Arturo Prat 514, Valdivia, Chile
4University of Bristol, Bristol BS8 1SS, UK
5Institute for Marine and Atmospheric Research (IMAU), Utrecht University, 3584 CC Utrecht, The Netherlands
6University of Missouri-Columbia, Columbia, Missouri 65211, USA
7Royal Netherlands Meteorological Institute (KNMI), 3732 GK De Bilt, The Netherlands
Published online: 13 January 2008; doi:10.1038/ngeo102
Large uncertainties remain in the current and future
contribution to sea level rise from Antarctica. Climate warming
may increase snowfall in the continent’s interior1–3 , but enhance
glacier discharge at the coast where warmer air and ocean
temperatures erode the buttressing ice shelves4–11. Here, we use
satellite interferometric synthetic-aperture radar observations
from 1992 to 2006 covering 85% of Antarctica’s coastline to
estimate the total mass ﬂux into the ocean. We compare the
mass ﬂuxes from large drainage basin units with interior snow
accumulation calculated from a regional atmospheric climate
model for 1980 to 2004. In East Antarctica, small glacier losses in
Wilkes Land and glacier gains at the mouths of the Filchner and
Ross ice shelves combine to a near-zero loss of 4 ±61 Gt yr−1. In
West Antarctica, widespread losses along the Bellingshausen and
Amundsen seas increased the ice sheet loss by 59% in 10 years to
reach 132 ±60 Gt yr−1in 2006. In the Peninsula, losses increased
by 140% to reach 60±46 Gt yr−1in 2006. Losses are concentrated
along narrow channels occupied by outlet glaciers and are caused
by ongoing and past glacier acceleration. Changes in glacier ﬂow
therefore have a signiﬁcant, if not dominant impact on ice sheet
The mass balance of Antarctica is determined from the
diﬀerence between two competing processes of ice discharge into
the ocean by glaciers and ice streams and accumulation of snowfall
in the vast interior, which are two large numbers aﬀected by
signiﬁcant uncertainties2,12. Estimates of ice discharge have been
sporadic in nature owing to the limited availability of ice velocity
and thickness data at the grounding line of Antarctica, as well
as precise knowledge of the grounding-line positions. Similarly,
estimates of snowfall have been aﬀected by uncertainties associated
with the interpolation of sparse in situ data of varying quality and
temporal coverage over the entire continent.
Here, we present a nearly complete map of surface velocities
along the periphery of Antarctica (Fig. 1) obtained from
interferometric synthetic-aperture radar (InSAR) data collected
between 1992 and 2006 by the European Earth Remote Sensing
(ERS-1 and 2), the Canadian Radarsat-1 and the Japanese Advanced
Land Observing satellites. Our map covers all major outlet glaciers,
ice streams and tributaries of importance for mass ﬂux calculation,
with ice velocity ranging from 100 to 3,500 m yr−1, at a precision
of 5 to 50 m yr−1(see the Methods section). Short-time variations
in velocity, for example, due to ocean tides, are averaged out over
the 24 to 46 day repeat period of our measurements. Velocities
at the grounding line of fast-moving glaciers are assumed to be
depth independent, which introduces errors of much less than
1% (ref. 3).
Using double-diﬀerence interferometry, we mapped glacier
grounding lines with a precision of 100 m all around Antarctica,
except for eight glaciers south of 81◦South where we used
the Moderate Resolution Imaging Spectroradiometer (MODIS)
mosaic13 with a precision of 1 km. Grounding-line thickness is
derived from surface elevation assuming ice to be in hydrostatic
equilibrium with sea water (see the Methods section). In selected
parts of West Antarctica, we have direct measurements of ice
thickness with a precision of 10 m instead (see Supplementary
Information, Table S1). For surface elevation, we use a new digital
elevation model (DEM) combining precise laser altimeter data
from the Ice Cloud and land Elevation Satellite from 2003–2004,
ERS-1/2 radar altimeter data from 1994 corrected for temporal
changes in between1,14 and the new GGM02 geoid15. Comparison
of the DEM with independent laser altimeter data at the grounding
line of West Antarctica indicates a vertical precision in elevation
of 0.15 ±4 m. Surface elevation above mean sea level is then
converted into solid-ice surface elevation after applying a ﬁrn depth
correction16. We estimate the random error in inferred thickness
to range from 80 to 120 m when accounting for uncertainties in
grounding-line position, surface elevation, ﬁrn depth correction
and geoid height. For veriﬁcation, at the grounding line of Pine
Island Bay glaciers, our thickness values are within 14 ±60 m
of direct thickness measurements10 ranging from 420 to 1,460 m.
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© 2008 Nature Publishing Group
+10 Gt yr–1
–10 Gt yr–1
0 0.01 0.1 1 2 3
Figure 1 Ice velocity of Antarctica colour coded on a logarithmic scale and overlaid on a MODIS mosaic13.Circles denote mass loss (red) or gain (blue) of large basins
in gigatonnes per year. Drainage basins are black lines extending from the grounding-line ﬂux gates. Letters A–K0indicate large basins20. Ice velocities for Siple Coast ice
streams and Ronne Ice Shelf are from refs 22,23. See Supplementary Information for acronyms and the Methods section for velocity precision.
Solid-ice ﬂuxes are then calculated combining vector ice velocity
and ice thickness, with a precision that is glacier dependent and
ranges from 2 to 15% (see the Supplementary Information). The
end points of the selected ﬂux gates deﬁne the extent of the glacier
drainage basins determined from the DEM. Individual drainage
basins are grouped into large units labelled A to K0.
Snowfall accumulation is from the RACMO2/ANT regional
atmospheric climate model, at 55 km resolution, averaged for
1980–2004 (refs 17–19). Lateral forcings are taken from European
Center for Medium-Range Weather Forecasting reanalyses
(ERA-40) for the period 1980–2002, supplemented with European
Center for Medium-Range Weather Forecasting operational
analyses after August 2002. Comparisons with 1,900 independent
ﬁeld data show excellent agreement (R =0.82) with the model18 .
The model predicts higher coastal precipitation and wetter
conditions in West Antarctica and the western Peninsula17 than
older maps obtained by interpolating limited ﬁeld data using
meteorological variables20 or satellite passive microwave data21 .
Few reliable in situ coastal accumulation data exist for comparison,
but in the high-accumulation sector of the Getz Ice Shelf (basin
F0G), the model predicts precipitation levels consistent with a
2,030 mm yr−1record at Russkaya station (74◦460S, 136◦520W)
for 1981–1989. Older maps yield accumulation levels 3 times lower,
which imply a local mass balance 20 times more negative and high
rates of glacier thinning that are not observed2. The RACMO2/ANT
accumulation values yield comparable losses for Pine Island and
Thwaites glaciers, which is consistent with the similarity of their
thinning rates2; other maps yield twice more thinning for Thwaites.
Finally, the model does not mix data from diﬀerent time periods
and fully incorporates temporal changes in snowfall between 1980
and 2004. A statistical analysis of absolute errors (see the Methods
section) yields an uncertainty in accumulation varying from 10%
in dry, large basins to 30% in wet, small coastal basins.
Ice ﬂux and snowfall are compared for each glacier, for large
basins A–K0, and for the Peninsula, East and West Antarctica. To
include non-surveyed areas, we apply a scaling factor on the mass
ﬂuxes of each large basin A–K0based on the percentage surveyed
area versus total area to cover 100% of Antarctica (Table 1). In East
Antarctica, we obtain a near-zero mass balance of −4±61 Gt yr−1.
The J00K Filchner22 and E0E Ross sectors are gaining mass, but this
is compensated by the mass loss in Wilkes Land (basin CE) from
the Philippi, Denman, Totten, Moscow University Ice Shelf, Cook
Ice Shelf and David glaciers. Interestingly, all of these glaciers are
marine based, that is, grounded well below sea level2, and therefore
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© 2008 Nature Publishing Group
Table 1 Mass balance of Antarctica in gigatonnes (1012 kg) per year by sector for the year 2000. Area: area surveyed. Input: snow accumulation ±σof surveyed area.
Outﬂow: grounding-line ice ﬂux ±σof surveyed area. Net: mass balance calculated as Input minus Outﬂow, ±σ. Net+: mass balance scaled on the basis of total area
(Area+) versus area surveyed (Area), except for basin II00 where we use refs 8,9. Input+: total snowfall in Area+ ±σ. Mass losses for 1996 and 2006 differ from those in
the year 2000 in basins GH and II00 (see Table 2).
Sector Area Input Outﬂow Net Net+Area+Input+
(103km2) (Gt yr−1) (Gt yr−1) (Gt yr−1) (Gt yr−1) (103km2) (Gt yr−1)
J00K Filchner 1,698 93 ±8 75±4 18±9 19 ±10 1,780 100±9
KK0Riiser Larsen 218 42 ±8 45±4−3±9−3±11 246 50±10
K0A Jutulstraumen 159 26 ±7 28±2−1±8−1±9 178 32±9
AA0Queen Maud Land 615 60 ±9 60±7 0±11 0 ±12 622 62±9
A0B Enderby Land 354 39 ±5 40±2−1±5−1±9 645 115±14
BC Lambert 1,197 73 ±10 77±4−4±11 −4±12 1,332 87±12
CC0Philippi, Denman 434 81 ±13 87±7−7±15 −11±24 702 137 ±22
C0D Totten, Frost 1,053 198 ±37 207±13 −8±39 −9±43 1,162 261±49
DD0Cook, Mertz, Ninnis 563 92 ±14 94±6−2±16 −2±19 691 136 ±21
D0E Victoria Land 267 20 ±1 22±3−2±4−3±6 450 62±4
EE0TransAntarctic 1,441 61±10 49±4 11±11 13 ±13 1,639 89 ±15
East Antarctica 2000 7,998 786±48 785 ±20 1 ±52 −4±61 9,447 1,131±69
E0F0Siple Coast 751 110 ±7 80±2 31±7 34 ±8 845 130±8
F0G Getz, Hull, Land 119 108 ±28 128±18 −19±33 −23 ±39 140 128±33
GH Pine Is., Thwaites 393 177±25 237±4−61 ±26 −64 ±27 417 196±28
HH0Ferrigno, Abbot 55 51 ±16 86±10 −35 ±19 −49 ±27 78 71 ±22
JJ00 Ronne 933 142±11 145±7−4±13 −4±14 1,028 165 ±13
West Antarctica 2000 2,251 588 ±49 676±22 −88 ±54 −106 ±60 2,508 690±57
H0I English Coast 92 71 ±21 78±7−7±23 −7±24 98 77 ±23
II00 Graham Land 13 15 ±5 20±3−5±6−15±8 78 125±46
I00J East Palmer Land 11 8±4 9 ±2−1±4−6±18 52 32 ±14
Antarctic Peninsula 2000 116 94 ±21 107±8−13±23 −28 ±45 228 234±53
Antarctica 2000 10,365 1,469±87 1,568±31 −100±78 −138 ±92 12,183 2,055 ±122
Table 2 Mass balance in gigatonnes (1012 kg) per year for 1996 and 2006 of basins
II00 and G H, West Antarctica, the Peninsula and the entire Antarctic ice sheet.
Sector Outﬂow Net Net+
(Gt yr−1) (Gt yr−1) (Gt yr−1)
GH Pine Is. Thwaites 1996 215±3−39±25 −41 ±27
GH Pine Is. Thwaites 2006 261±4−85±26 −90 ±27
West Antarctica 1996 654±22 −66 ±53 −83 ±59
West Antarctica 2006 700±23 −112 ±54 −132 ±60
II00 Graham Land 1996 20±3−5±6−12±7
II00 Graham Land 2006 49±3−34±6−47 ±9
Peninsula 1996 107 ±8−13±23 −25±45
Peninsula 2006 136 ±10 −42±24 −60±46
Antarctica 1996 1,546 ±30 −78±78 −112 ±91
Antarctica 2006 1,621 ±32 −153±78 −196 ±92
more prone to instabilities. In West Antarctica, the well-known
mass gain of the E0F0Siple Coast basin23 is small compared with
the combined mass loss from the F0G, GH and HH0basins, which
include the entire Amundsen and Bellingshausen sea coasts, and
not just Pine Island Bay. The mass loss inferred from F0H0is much
larger than in a previous survey12 that did not include many high-
loss, small glaciers in the GF0and HH0basins and ongoing glacier
acceleration in basin GH. Overall, the West Antarctic ice sheet lost
106±60 Gt yr−1in the year 2000.
In the Antarctic Peninsula, the H0I and I00J basins of Palmer
Land are near balance, despite a reported increase in snowfall17,
but basin II00 of Graham Land is out of balance. On the east coast,
the Larsen A and B glaciers experienced an abrupt acceleration
(300% on average) in 2002, which increased their mass loss from
3±1 in 1996 and 2000, to 31 ±9 Gt yr−1in 2006 (ref. 11). Farther
south, airborne laser altimetry data suggest that the Larsen C
glaciers are close to balance6. But on the west coast, the glaciers
have experienced widespread ice-front retreat, enhanced melt
and continuous speed up9. We have no thickness data for these
glaciers, and there is no ﬂoating section. A 12% speed up in
10 years, enhanced melt and a net accumulation of 42 ±14 Gt yr−1
suggest a loss of 7 ±4 Gt yr−1in 1996, 10 ±5 Gt yr−1in 2000 and
13 ±7 Gt yr−1in 2006. The combined loss for the Peninsula then
becomes 25 ±45 Gt yr−1in 1996, increasing by 140% in 2006 to
60±46 Gt yr−1(Table 2).
Changes in surface elevation in basin F0H0for 1995–2005
(Fig. 2) reveal broad-scale, centimetre-level variations in snowfall
in the interior (wetter conditions in H0H, and drier in F0E0(ref. 17)),
but pronounced, metre-scale thinning concentrated in narrow
channels occupied by outlet glaciers and extending in the ﬂow
direction across the entire coastal range. The strong, widespread
correlation between ice thinning and ice velocity (>50 m yr−1), for
example, on the Berg, Ferrigno, Venable, Pine Island, Thwaites,
Smith and Getz glaciers, indicates that thinning is caused by the
velocity of glaciers being well above that required to maintain
mass balance, that is, ice stretches longitudinally, which causes
it to thin vertically. In basin GH, we ﬁnd that Pine Island
Glacier accelerated 34% in 1996–2006, Smith 75%, Pope 20%,
Haynes 27% and Thwaites is widening11. The mass ﬂux from
basin GH thereby increased 21% since 1996 and the mass loss
doubled from 41 ±27 Gt yr−1in 1996 to 64 ±27 Gt yr−1in 2000
and 90 ±27 Gt yr−1in 2006 (Table 2). This is the largest loss in
Antarctica. In contrast, we detect no glacier acceleration in basins
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50 m yr–1
–50 – 20 –10 –3 3 10 20 50
–100 – 30 –15 –6 0 6 15 30 100
Figure 2 Changes in surface elevation (centimetres per year) for basin F0H0.
Values were derived from ERS-2 and Envisat radar altimeter data for 1995–2005
and colour coded from red (thinning) to blue (thickening), overlaid on 50 myr−1
velocity contours in green. Areas of fast ﬂow in F0H0correspond to areas of
concentrated thinning, in contrast with other glaciers.
HH0and GF0in 1992–2006, which implies that these glaciers
must have accelerated out of equilibrium well before 1992 and
maintained high speeds since then. This is exactly what happened
to Fleming Glacier following the demise of Wordie Ice Shelf8.
Similarly, in basin CE00 in East Antarctica, ice thinning is detected
along the trenches of the David, Cook, Frost, Moscow University,
Totten and Denman glaciers2, yet we ﬁnd no change in speed of
these glaciers between 1996 and 2006, and not even a change in
speed since 1957 on Denman Glacier11. Glacier acceleration out of
equilibrium must have preceded our period of observation there
as well, and the glaciers must have been steadily out of balance for
many decades, not just the recent past.
Glaciers that ﬂow into large ice shelves (basins JK, F0E, BC)
are near balance or thickening. This is consistent with their
stabilization by buttressing and their distance to ocean heat sources
associated with the Antarctic Circumpolar Current22. Mass losses
in the Amundsen Sea and the northern Peninsula are caused by
ongoing acceleration, not by a change in snowfall because snowfall
increased in 1980–2004, especially in the Peninsula17. Fast ﬂow is
explained by the ungrounding of glaciers owing to the thinning
or collapse of their buttressing ice shelves6or to a reduction in
backforce resistance at the ice front as glacier fronts thin because of
warmer air or warmer ocean temperatures4,9. In the Amundsen Sea
and the western Peninsula, ice-shelf melting is fuelled by intrusions
of warm circumpolar deep water (CDW) onto the continental
shelf down deep troughs carved into the sea ﬂoor during past ice
ages24,25. In East Antarctica, there is no report of CDW intrusion in
Wilkes Land. A southward migration of the Antarctic Circumpolar
Current26 caused by an increasingly positive southern annular
mode may have, in favourable conditions24 , entrained overspills of
CDW onto the continental shelf and trigger glacier acceleration, but
this hypothesis cannot be conﬁrmed at present.
Our results provide a nearly complete assessment of the spatial
pattern in mass ﬂux and mass change along the coast of Antarctica,
glacier by glacier, with lower error bounds than in previous
incomplete surveys, and a delineation of areas of changes versus
areas of near stability. Over the time period of our survey, the
ice sheet as a whole was certainly losing mass, and the mass
loss increased by 75% in 10 years. Most of the mass loss is
from Pine Island Bay sector of West Antarctica and the northern
tip of the Peninsula where it is driven by ongoing, pronounced
glacier acceleration. In East Antarctica, the loss is near zero, but
the thinning of its potentially unstable marine sectors calls for
attention. In contrast to major increases in ice discharge, snowfall
integrated over Antarctica did not change in 1980–2004 (ref. 27)
and even slightly increased in areas of large loss17. We conclude that
the Antarctic ice sheet mass budget is more complex than indicated
by the temporal evolution of its surface mass balance. Changes in
glacier dynamics are signiﬁcant and may in fact dominate the ice
sheet mass budget.
FIRN DEPTH CORRECTION
Ice thickness, H, is deduced from surface elevation above mean sea level with
reference to the GGM02 geoid15,h, as H=(h−1H)ρsea /(ρsea −ρice ), where
the density of sea water, ρsea =1,028 kg m−3(at 34 p.s.u. salinity, 1 km depth),
the density of solid ice, ρice =917 kg m−3and 1His the ﬁrn depth correction.
For H=1 km, a 4 m uncertainty in 1Hintroduces a 4% uncertainty in
thickness and ﬂux. Earlier work assumed a constant ﬁrn depth correction. We
calculate 1Hfrom a ﬁrn densiﬁcation model16 driven by surface density using
25-year-average air temperature, snow accumulation and wind speed from
RACMO2/ANT. 1Hvaries from 0 to 20 m. Its precision is 2–3m on the basis of
a comparison with ﬁrn core data at the critical densities of 550 and 880 kgm−3.
SNOW ACCUMULATION ERROR
Snow accumulation is the arithmetic average of the values given in refs 18,19.
We use 1,900 in situ independent observations, SMBo, to calculate absolute
errors. The error for the observations is modelled as Eo=5+0.15 SMBoin
kg m−2yr−1where the second term accounts for the uncertainty associated
with spatial variability. The error for the modelled values, SMBm, is modelled
as Em=9+0.10 SMBm+0.00033 SMB2
min kg m−2yr−1. This representation
reﬂects that the model is well calibrated with many good observations for low
and medium values, but that the relative and absolute errors increase for high
values where few reliable observations exist. The relative error is maximized at
30% for SMBm>557 kg m−2yr−1. Coeﬃcients for the modelling of Emwere
optimally chosen by examining the distribution of diﬀerences, SMBm−SMBo,
normalized by the total error margin, that is, the squared sum of Eoand Em.
With our selection of coeﬃcients, we obtain a normal distribution with σ=1,
which provides strong statistical support for the error analysis. To calculate
accumulation uncertainty at the basin scale, we also account for the spatial
autocorrelation of errors. The correlation length of (SMBm−SMBo) varies
from 161 km below 2,000 m elevation to 300 km above 2,000m. Combining
these correlation lengths with the error modelling, we obtain total errors in
AK0basins (Table 1) ranging from 10% in large, dry basins to 30% in wet
and smaller coastal basins. These errors represent our most likely estimate of
absolute errors, not the 95% conﬁdence interval. Previous attempts at deﬁning
accumulation errors only addressed interpolation errors.
VELOCITY AND MASS FLUX ERRORS
Ice velocity is measured with speckle tracking on Radarsat-1 24 day, Japanese
Advanced Land Observing PALSAR 46day (basin GF0) and ERS-1 9 day (basin
H0I) repeats, and interferometrically using ascending/descending ERS-1/2
tandem pairs (basin HG) with an ERS-1/2 precision of 2–5 m yr−1; and with
a combination of interferometric phase and speckle tracking (basin D0C0),
with a precision of 20–50 m yr−1. Systematic errors are negligible compared
with random errors because we use stagnant areas for calibration and combine
multiple tracks with diﬀerent look directions. The unknown positive bias
between surface and vertically integrated velocity is much less than 1%.
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Systematic errors in thickness are less than 1%, whereas random errors range
from 10 to 120 m (see Supplementary Information, Table S1). The percentage
error in mass ﬂux is calculated as the sum of the percentage error in velocity and
the percentage error in thickness. This is appropriate for plug ﬂow or U-shaped
velocity proﬁles, which is the case for most large Antarctic glaciers. For glaciers
that approach a V-shaped velocity proﬁle, our errors may be underestimated
by a factor of 2. Errors in Table 1 and Supplementary Information, Table S1 are
only random errors. Systematic errors are not known but small, so that actual
errors may be slightly higher. Decadal changes in velocity were only available
for glaciers mentioned in the text, ref. 11 or Table 2, and were assumed to be
Received 29 August 2007; accepted 27 November 2007; published 13 January 2008.
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We thank R. Arthern for discussions. This work was carried out at Caltech’s Jet Propulsion Laboratory,
the University of California Irvine and the University of Missouri, Columbia, under a contract with
NASA’s Cryospheric Science Program. J.L.B. was supported by NERC grant NE/E004032/1. SAR data
were provided by the European Space Agency VECTRA project, the Canadian Space Agency, the
Japanese Space Agency, and the Alaska Satellite Facility. ERS-2 radar altimeter data were provided by
Correspondence and requests for materials should be addressed to E.R.
Supplementary Information accompanies this paper on www.nature.com/naturegeoscience.
All authors discussed the results and commented on the manuscript. E.R. led the remote sensing
analysis, development of the paper and integration of the results, J.L.B. provided a digital elevation
model and analysed its accuracy, M.R.B., W.J.B. and E.M. contributed calculations of snow
accumulation, ﬁrn depth correction and associated errors and C.D. and Y.L. analysed elevation changes
from satellite radar altimeter data.
Reprints and permission information is available online at http://npg.nature.com/reprintsandpermissions/
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