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A Reconciled Estimate of Ice-Sheet Mass Balance

A Reconciled Estimate of Ice-Sheet Mass Balance UC Irvine UC Irvine Previously Published Works Title Permalink https://escholarship.org/uc/item/0vq404h7 Journal Science (New York, N.Y.), 338(6111) ISSN 0036-8075 Authors Shepherd, Andrew Ivins, Erik R A, Geruo et al. Publication Date 2012-11-01 DOI 10.1126/science.1228102 Supplemental Material https://escholarship.org/uc/item/0vq404h7#supplemental Copyright Information This work is made available under the terms of a Creative Commons Attribution License, availalbe at https://creativecommons.org/licenses/by/4.0/ Peer reviewed eScholarship.org Powered by the California Digital Library University of California REVIEW RESEARCH ARTICLES 15. P. Yin et al., Science 321, 824 (2008). 42. C. E. Castro et al., Nat. Methods 8, 221 (2011). the assembly. However, in practice, low yields 16. E. S. Andersen et al., Nature 459, 73 (2009). 43. Y. Ke, N. V. Voigt, K. V. Gothelf, W. M. Shih, J. Am. were already observed for larger designs (up to 17. Y. Ke et al., Nano Lett. 9, 2445 (2009). Chem. Soc. 134, 1770 (2012). 24,576 nucleotides attempted thus far). Solving 18. S. M. Douglas et al., Nature 459, 414 (2009). 44. R. Schulman, B. Yurke, E. Winfree, Proc. Natl. Acad. this challenge may require improvements in struc- 19. H. Dietz, S. M. Douglas, W. M. Shih, Science 325, 725 Sci. U.S.A. 109, 6405 (2012). (2009). ture and sequence design, enzymatic synthesis for 20. J. Zheng et al., Nature 461, 74 (2009). Acknowledgments: The authors thank M. Dai for technical higher-quality strands, optimized thermal or iso- 21. T. Omabegho, R. Sha, N. C. Seeman, Science 324,67 assistance; E. Winfree, B. Wei, and S. Woo for discussions; and thermal (44) annealing conditions, and a detailed (2009). D. Pastuszak for assistance in draft preparation. This work is understanding and perhaps explicit engineering 22. I. Severcan et al., Nat. Chem. 2, 772 (2010). supported by an Office of Naval Research (ONR) Young of the kinetic assembly pathways (8, 14, 44)of 23. D. Han et al., Science 332, 342 (2011). Investigator Program award N000141110914, an ONR 24. L. Qian, E. Winfree, Science 332, 1196 (2011). grant N000141010827, an Army Research Office grant DNA brick structures. 25. C. J. Delebecque, A. B. Lindner, P. A. Silver, F. A. Aldaye, W911NF1210238, an NSF CAREER award CCF1054898, an The DNA brick structure, with its modular ar- Science 333, 470 (2011). NIH Director’s New Innovator award 1DP2OD007292, and chitecture, sophisticated geometry control, and 26. B. Wei, M. Dai, P. Yin, Nature 485, 623 (2012). a Wyss Institute Faculty Startup Fund to P.Y., and by a Wyss synthetic nature, will further expand the range of 27. C. Lin, Y. Liu, S. Rinker, H. Yan, ChemPhysChem 7, 1641 Institute Faculty Grant, ONR grants N000014091118 and (2006). N000141010241, and an NIH Director’s New Innovator applications and challenges that nucleic acid nano- 28. N. B. Leontis, A. Lescoute, E. Westhof, Curr. Opin. award 1DP2OD004641 to W.M.S.. L.L.O. is supported by an technology has already started to address—for Struct. Biol. 16, 279 (2006). NSF graduate research fellowship. Y.K. conceived the example, to arrange technologically relevant guest 29. W. M. Shih, C. Lin, Curr. Opin. Struct. Biol. 20, 276 project, designed and performed the experiments, analyzed molecules into functional devices (6, 25, 32–34), (2010). the data, and wrote the paper; L.L.O. designed and performed 30. N. C. Seeman, Annu. Rev. Biochem. 79, 65 (2010). the experiments, analyzed the data, and wrote the paper; to serve as programmable molecular probes and 31. D. Y. Zhang, G. Seelig, Nat. Chem. 3, 103 (2011). W.M.S. conceived the project, discussed the results, and instruments for biological studies (33, 34, 36), 32. A. Kuzyk et al., Nature 483, 311 (2012). wrote the paper; P.Y. conceived, designed, and supervised to render spatial control for biosynthesis of use- 33. H. M. T. Choi et al., Nat. Biotechnol. 28, 1208 (2010). the study, interpreted the data, and wrote the paper. The ful products (25), to function as smart drug deliv- 34. C. Lin et al., Nat. Chem. 4, 832 (2012). DNA sequences for the nanostructures can be found in the 35. M. J. Berardi, W. M. Shih, S. C. Harrison, J. J. Chou, supplementary materials. A provisional patent has been ery particles (37), and to enable high-throughput Nature 476, 109 (2011). filed based on this work. nanofabrication of complex inorganic materials 36. N. D. Derr et al., Science 338, 662 (2012). for electronics or photonics applications (6, 32). 37. S. M. Douglas, I. Bachelet, G. M. Church, Science 335, Supplementary Materials The modularity of the brick structure may facil- 831 (2012). www.sciencemag.org/cgi/content/full/338/6111/1177/DC1 itate rapid prototyping of diverse functional nano- 38. P. W. K. Rothemund, E. S. Andersen, Nature 485, 584 Materials and Methods (2012). devices. Its sophisticated and refined geometrical Supplementary Text 39. Materials and methods, supplementary figures and texts, control may enable applications that require high- Figs. S1 to S66 and DNA sequences are available as supplementary Tables S1 to S20 precision arrangements of guest molecules. Be- materials on Science Online. cause the brick structure is composed entirely of 40. S. M. Douglas et al., Nucleic Acids Res. 37, 5001 (2009). 11 July 2012; accepted 16 October 2012 short synthetic strands (no biologically derived 41. Y. Ke et al., J. Am. Chem. Soc. 131, 15903 (2009). 10.1126/science.1227268 scaffold), it is conceivable to make bricks by using synthetic informational polymers other than the natural form of DNA. Such polymers may in- clude L-DNA (26), DNA with chemically modi- A Reconciled Estimate of Ice-Sheet fied backbones or artificial bases, or chemically synthesized or in vitro (or even in vivo) transcribed RNA. This material diversity may potentially Mass Balance produce nanostructures with not only prescribed shapes but also designer chemical (or bio- 1 2 3 4 5 Andrew Shepherd, * Erik R. Ivins, * Geruo A, Valentina R. Barletta, Mike J. Bentley, chemical) properties (such as nuclease resistance 6 1 7 4 8 Srinivas Bettadpur, Kate H. Briggs, David H. Bromwich, René Forsberg, Natalia Galin, or reduced immunogenicity) that would be useful 9 10 11 12,27 13 14 Martin Horwath, Stan Jacobs, Ian Joughin, Matt A. King, Jan T. M. Lenaerts, Jilu Li, for diverse applications requiring the structure to 13 15 16 1 Stefan R. M. Ligtenberg, Adrian Luckman, Scott B. Luthcke, Malcolm McMillan, function robustly in complex environments, 8 17 18 8 7 14 Rakia Meister, Glenn Milne, Jeremie Mouginot, Alan Muir, Julien P. Nicolas, John Paden, such as in living cells or organisms. 19 20 18,2 21 4 Antony J. Payne, Hamish Pritchard, Eric Rignot, Helmut Rott, Louise Sandberg Sørensen, 22 18 23 11 1 Ted A. Scambos, Bernd Scheuchl, Ernst J. O. Schrama, Ben Smith, Aud V. Sundal, 13 13 13 20 References and Notes Jan H. van Angelen, Willem J. van de Berg, Michiel R. van den Broeke, David G. Vaughan, 1. N. C. Seeman, J. Theor. Biol. 99, 237 (1982). 18,2 3 5 8 24 Isabella Velicogna, John Wahr, Pippa L. Whitehouse, Duncan J. Wingham, Donghui Yi, 2. J. H. Chen, N. C. Seeman, Nature 350, 631 (1991). 25 26 Duncan Young, H. Jay Zwally 3. T. J. Fu, N. C. Seeman, Biochemistry 32, 3211 (1993). 4. E. Winfree, F. Liu, L. A. Wenzler, N. C. Seeman, Nature 394, 539 (1998). 5. B. Yurke, A. J. Turberfield, A. P. Mills Jr., F. C. Simmel, We combined an ensemble of satellite altimetry, interferometry, and gravimetry data sets using J. L. Neumann, Nature 406, 605 (2000). common geographical regions, time intervals, and models of surface mass balance and 6. H. Yan, S. H. Park, G. Finkelstein, J. H. Reif, T. H. LaBean, glacial isostatic adjustment to estimate the mass balance of Earth’s polar ice sheets. We find that Science 301, 1882 (2003). there is good agreement between different satellite methods—especially in Greenland and 7. W. B. Sherman, N. C. Seeman, Nano Lett. 4, 1203 West Antarctica—and that combining satellite data sets leads to greater certainty. Between 1992 (2004). 8. P. W. K. Rothemund, N. Papadakis, E. Winfree, PLoS Biol. and 2011, the ice sheets of Greenland, East Antarctica, West Antarctica, and the Antarctic −1 2, e424 (2004). Peninsula changed in mass by –142 T 49, +14 T 43, –65 T 26, and –20 T 14 gigatonnes year , 9. A. Chworos et al., Science 306, 2068 (2004). respectively. Since 1992, the polar ice sheets have contributed, on average, 0.59 T 0.20 millimeter 10. S. H. Park et al., Angew. Chem. Int. Ed. 45, 735 −1 year to the rate of global sea-level rise. (2006). 11. P. W. K. Rothemund, Nature 440, 297 (2006). 12. G. Seelig, D. Soloveichik, D. Y. Zhang, E. Winfree, Science luctuations in the mass of the polar ice a consequence of their internal dynamics and 314, 1585 (2006). sheets are of considerable societal impor- changes in atmospheric and oceanic conditions 13. Y. He et al., Nature 452, 198 (2008). Ftance, because they affect global sea lev- (3–5). Analysis of the geological record sug- 14. P. Yin, H. M. T. Choi, C. R. Calvert, N. A. Pierce, Nature 451, 318 (2008). els (1, 2) and oceanic conditions. They occur as gests that past climatic changes have precipitated www.sciencemag.org SCIENCE VOL 338 30 NOVEMBER 2012 118 REVIEW RESEARCH ARTICLES sustained ice-sheet contributions, in excess of balance of between –676 and +69 gigatonnes al data sets, so we assess the temporal uncertainty −1 −1 10 mm year over millennial time periods (6), (Gt) year , equivalent to a mean global sea-level through comparison with global atmospheric −1 and the prospect of such changes in the future are contribution in the range of +1.9 to–0.2 mm year . reanalyses (16). We also useRACMO2todrive of greatest concern. Even the modest rises in However, much of this spread, which is large in a model of AIS firn densification (29) for the ocean temperature that are predicted over the comparison to other ice-sheet imbalance assess- purpose of converting satellite LA observations coming century (7) could trigger substantial ice- ments (1, 2) and to the estimated rate of global into changes in ice-sheet mass. sheet mass loss through enhanced melting of ice sea-level rise (17), is due to the brevity of many Glacial isostatic adjustment (GIA). GIA of the shelves (8–10) and outlet glaciers (11, 12). How- satellite surveys (4.5 years, on average) relative solid Earth is an important contributor to the ever, these processes were not incorporated into to the rate at which ice-sheet mass fluctuates signals observed by satellite gravimetry and, to a the ice-sheet models that informed the current glob- (5, 18–20). Because the various satellite methods lesser extent, satellite altimetry (30). The GIA al climate projections (13). Until this is achieved, differ in their strengths and weaknesses (14, 15, 21), must therefore be considered when estimating ice- observations of ice-sheet mass imbalance remain careful consideration ought to make them com- sheet mass balance with either technique. In essential in determining their contribution to sea plementary. Here, we compare and combine es- Antarctica, the use of GIA models has in prac- level. timates of ice-sheet mass balance derived from tice introduced considerable uncertainty (up to −1 Satellite geodesy has revolutionized the manner all three satellite geodetic techniques, using com- 130 Gt year ) into ice-sheet mass balance estimates in which ice-sheet mass balance is estimated mon spatial and temporal domains, to investigate derived from satellite gravimetry (31–33). There (14, 15). Since 1998, there have been at least 29 the extent to which the approaches concur and to are a number of contributory factors to this un- ice-sheet mass balance estimates, based variously produce a reconciled estimate of ice-sheet mass certainty, including the scarcity of constraints on on the satellite techniques of altimetry, interfer- balance. the evolution of the ice sheet since the Last ometry, and gravimetry (16). These estimates, and Glacial Maximum (LGM), limited knowledge of Data and Methods their respective uncertainties, allow for a com- Earth mechanical properties, and the scarcity of bined Greenland and Antarctic ice-sheet mass im- In this assessment, we use 19 years of satellite near-field relative sea-level and vertical crustal radar altimeter (RA) data, 5 years of satellite laser motion data with which to evaluate model per- altimeter (LA) data, 19 years of satellite radar formance (34, 35). School of Earth and Environment, University of Leeds, Leeds LS2 9JT, UK. Jet Propulsion Laboratory, M/S 300-233, 4800 interferometer data, 8 years of satellite gravime- Here, we consider variants of six GIA mod- Oak Grove Drive, Pasadena, CA 91109, USA. Department of try data, 32 years of surface mass balance (SMB) els, and we assess their impact on geodetic ice- Physics, University of Colorado, Boulder, CO 80309–0390, model simulations, and estimates from several sheet mass balance estimates. For Greenland, USA. Geodynamics Department, Technical University of Den- glacial isostatic adjustment models, to produce a where the signal of GIA is relatively small and mark, DTU SPACE, National Space Institute, Elektrovej, Build- reconciled estimate of ice-sheet mass balance. The well constrained, we use the Simpson (36), ICE- ing327,DK-2800 Kgs.Lyngby, Denmark. Department of Geography, Durham University, South Road, Durham DH1 3LE, satellite data sets were developed by using in- 5G (37), and ANU (38) models. For Antarctica, UK. Center for Space Research, University of Texas at Austin, dependent methods and, in the case of the LA, we compare the ICE-5G model (39)withtwo 3925 West Braker Lane, Suite 200, Austin, TX 78759–5321, USA. 7 gravimeter, and SMB data sets, through contribu- recent Antarctic GIA models: the W12a model Polar Meteorology Group, Byrd Polar Research Center, and tions from numerous research groups. To enable a (35, 40) and a version (IJ05_R2) of the IJ05 model Atmospheric Sciences Program, Department of Geography, The Ohio State University, 1090 Carmack Road, Columbus, OH 43210, direct comparison, we reprocessed the geodetic (41) updated for this study (16). Both regional USA. Centre for Polar Observation and Modelling, Department data sets with use of common time intervals and GIA models incorporate recently improved con- of Earth Sciences, University College London, London WC1E 9 common definitions of the East Antarctic, West straints on the ice-loading history (42–45)that 6BT, UK. Institut für Astronomische und Physikalische Geodäsie, Antarctic, Antarctic Peninsula, and Greenland ice- suggest that the AIS was thinner at the LGM than Technische Universität München, Arcisstraße 21, 80333 München, Germany. Lamont-Doherty Earth Observatory (LDEO), 205 sheet (EAIS, WAIS, APIS, and GrIS, respectively) previously thought, leading to a lowering of es- Oceanography, 61 Route 9W - Post Office Box 1000, Palisades, boundaries (16). The maximum temporal extent timated ice-sheet mass losses since that time NY 10964, USA. Polar Science Center, Applied Physics Labora- of the satellite data sets spans the period 1992 to (40, 45). Although a consequence of this re- tory, University of Washington, 1013 NE 40th Street, Seattle, WA 2011, and results from all geodetic techniques are vision is a potential discrepancy between far-field 98105–6698, USA. School of Civil Engineering and Geo- sciences, Cassie Building, Newcastle University, Newcastle upon available between January 2003 and December sea-level records and commonly accepted North- Tyne NE1 7RU, UK. Utrecht University, Institute for Marine and 2008. Unless stated otherwise, all results are ern Hemisphere deglaciation models, both of the Atmospheric Research, Princetonplein 5, Utrecht, Netherlands. presented with 1-sigma uncertainty estimates. new regional GIA models perform well when Center for Remote Sensing of Ice Sheets, University of Kansas, Ice-sheet surface mass balance. SMB in- compared with Antarctic Global Positioning Sys- Nichols Hall, 2335 Irving Hill Road, Lawrence, KS 66045, USA. cludes solid and liquid precipitation, surface sub- tem (GPS) observations (34), and we conclude Department of Geography, College of Science, Swansea Uni- versity, Singleton Park, Swansea SA2 8PP, UK. National Aero- limation, drifting snow transport, erosion and that these latest solutions are best suited for esti- nautical and Space Administration (NASA) Goddard Space Flight sublimation, and meltwater formation, refreez- mating AIS mass balance. Center, Planetary Geodynamics Laboratory, Greenbelt, MD 20771, 17 ing, retention, and runoff. Our estimates of the Radar and laser altimetry. RA and LA pro- USA. Department of Earth Sciences, University of Ottawa, Antarctic Ice Sheet (AIS) and the GrIS SMB are vide ice-sheet mass balance estimates through Ottawa, Ontario K1N 6N5, Canada. Department of Earth Sys- tem Science, University of California, 3226 Croul Hall, Irvine, CA derived from reconstructions of the RACMO2 measurements of ice-sheet volume change. The 92697–3100, USA. School of Geographical Sciences, Uni- regional atmospheric climate model (22)over technique has been applied to both Greenland versity of Bristol, Bristol BS8 1SS, UK. British Antarctic Survey, 21 the period 1979 to 2010, with horizontal reso- (46–48) and Antarctica (4, 47, 49) and is unique High Cross, Madingley Road, Cambridge CB3 0ET, UK. Insti- lutions of 27 (AIS) and 11 (GrIS) km. RACMO2 in spatially resolving the detailed pattern of mass tute of Meteorology and Geophysics, University of Innsbruck, Innsbruck, Austria. National Snow and Ice Data Center, Uni- has a multilayer snowpack with drifting snow and imbalance, with monthly temporal sampling. RA versity of Colorado, Boulder, CO 80309, USA. Delft University snow albedo schemes (23) and has been evalu- provides the longest continuous record of all geo- of Technology, Faculty of Aerospace Engineering, Kluyverweg 1, ated against in situ temperature, wind, and surface- detic techniques (50). Altimeter measurements of 2629 HS Delft, Netherlands. SGT Incorporated, NASA Goddard energy balance observations from weather stations elevation change are precise, because they require Space Flight Center, Cryospheric Sciences Laboratory, Code 615 (24–26) as well as satellite-derived estimates of melt only modest adjustments to account for sensor Greenbelt, MD 20771, USA. Institute for Geophysics, University of Texas, Austin, TX 78759, USA. NASA Goddard Space Flight extent, mass changes, and drifting snow (5, 26, 27). drift, changes in the satellite attitude, atmospheric Center, Cryospheric Sciences Laboratory, Code 615 Greenbelt, The spatial uncertainty of the RACMO2 mean attenuation, and movements of Earth’s surface. MD 20771, USA. School of Geography and Environmental SMB has been assessed through comparison with By far the greatest uncertainty lies in the con- Studies, University of Tasmania, Hobart 7001, Australia. 310 (GrIS) and 1850 (AIS) in situ observations version from volume to mass change. In the case *To whom correspondence should be addressed. E-mail: (28). However, temporal fluctuations in snow of LA, this conversion has been performed by [email protected] (A.S.); [email protected] (E.R.I.) accumulation are poorly resolved in observation- using an external model of fluctuations in the firn- 1184 30 NOVEMBER 2012 VOL 338 SCIENCE www.sciencemag.org REVIEW RESEARCH ARTICLES layer thickness (29, 48, 51). In the case of RA, the fluctuations in firn thickness by using models nesses, now encompasses 64, 79, 96, and 93% of conversion to mass has been performed by using driven by either regional climate model predic- the APIS, EAIS, WAIS, and GrIS, respectively; a prescribed density model and by allowing for tions (29) or by remotely sensed estimates of the remainder is assumed to have no loss due to temporal fluctuations in snowfall in the uncer- temperature (48, 51). The error budget was cal- ice dynamics. tainty (52). culated from uncertainties in the corrected height Gravimetry. The Gravity Recovery and Climate We used European Remote-Sensing (ERS-1 measurements, in the correction for change in Experiment (GRACE) satellite mission has and ERS-2) satellite and Envisat 35-day repeat firn thickness, and in the estimated SMB. The allowed fluctuations in ice-sheet mass to be esti- satellite RA observations to determine changes in mass-change estimates reported here are the arith- mated through measurement of their changing the mass of the EAIS and WAIS between May metic average of those obtained by the different gravitational attraction (32, 67–69). Advantages 1992 and September 2010 (16). Time series of sur- groups. of the GRACE method are that it provides face elevation change were developed at 39,375 Input-output method (IOM). The IOM quan- regional averages without the need for interpola- crossing points of the satellite orbit ground tracks tifies the difference between glacier mass gained tion, measures the effect of mass fluctuations by using dual-cycle crossovers (49, 53). In total, through snowfall and lost by sublimation and directly, and permits monthly temporal sampling. 46.5 million measurements were included in this meltwater runoff and the discharge of ice into the However, a key challenge is to discriminate analysis, encompassing 74 and 76% of the EAIS ocean. The approach has the advantage of al- fluctuations in ice-sheet mass from changes in the and WAIS, respectively. The satellites were cross- lowing changes in SMB and ice dynamics to be underlying crust and mantle. This is achieved by calibrated by considering differences between ele- examined separately at the scale of individual using models of GIA, which, in the case of the vation changes occurring during periods of mission glacier drainage basins (5) and has been used in AIS, has led to significant adjustments (70). The overlap. Elevation data were corrected for the lag numerous assessments of AIS and GrIS mass ba- spatial resolution of GRACE observations de- of the leading-edge tracker and for variations lance (18, 55–57). Although earlier IOM studies rived from global spherical harmonic solutions in dry atmospheric mass, water vapor, the iono- used representations of SMB developed from of about 300 km in the polar regions (71)is sphere, solid Earth tides, and surface scattering guided interpolation of sparse ground observations coarse in comparison to that of other geodetic (50). The IJ05_R2 model was used to correct (58–60), regional atmospheric climate models techniques. Hence, a further complicating factor for elevation changes associated with GIA. Mass (5, 61) are now used because they provide sub- is that signals may leak into regional GRACE changes were calculated by using a surface-density daily predictions at high spatial resolution that solutions as a consequence of remote geophysi- −3 model with a nominal density for firn (400 kg m ) are independent of the in situ observations. When cal processes. In circumstances where spatial applied to all regions other than those in which evaluated against such data, SMB model errors relationships between geophysical mass fluxes changes are assumed to occur at the density of ice are found to range between 5 and 20%, depend- can be adequately characterized, application of −3 the mass concentration unit (mascon) method (900 kg m )(52). Rates of mass change were ing on the basin size and location, with propor- computed in regions of interest by interpolating tionately the largest uncertainties occurring in (68, 72, 73) introduces a capacity to study changes measurements derived at satellite-orbit crossing regions of extreme (low or high) precipitation, at smaller scales. points and by extrapolating these results to un- strong melting, or where the model resolution is Data from the GRACE satellite mission were observed area. To estimate the uncertainty of mass too coarse. Quantifying ice-stream discharge re- used to estimate changes in the mass of the AIS trends, we treated the estimated variability of snow- quires measurements of ice velocity and thickness and GrIS between January 2003 and December fall (49) and the elevation trend variability as at the grounding line. Ice-sheet velocity snapshots 2010 (16). Analysis methods varied between the equivalent sources of uncertainty. This approach have been widely measured by using interfero- six groups who contributed these observations; is used because it has not yet proved possible to metric synthetic aperture radar (InSAR) with high some used the mascon approach, whereas others separate, in the observed elevation change, an- (<3%) accuracy (62, 63) and relatively low (an- used spatial-averaging kernels. The GRACE data nual cycles due to density fluctuations from res- nual or longer) frequency. The thickness of many were corrected for the effects of GIA by using the idual variations due to signal penetration into ice streams has been directly measured by using Simpson, ANU, and ICE-5G models in Green- the firn. airborne radar with high (~10 m) accuracy (64). land and the W12a, IJ05_R2, and ICE-5G mod- We used ICESat (Ice, Cloud, and Land Ele- Nonetheless, there are many ice-sheet outlet gla- els in Antarctica. Although we only include vation Satellite) LA observations acquired be- ciers for which such data do not exist; in these results using the W12a and IJ05_R2 models in tween September 2003 and November 2008 (the regions, less accurate methods are used to cal- our reconciled estimates for Antarctica, we also period of optimal instrument calibration) to es- culate thickness with uncertainties in the range of provide separate ice-sheet mass balance estimates timate changes in the mass of the AIS and GrIS 80 to 120 m (18, 55). Lastly, where thinning rates determined by using the ICE-5G GIA model (16). AIS and GrIS elevation rates were com- are large, the temporal evolution of ice thick- solution (16) to allow comparison with previous- puted by four and two different groups, respec- ness should be accounted for (65). ly published estimates; its use leads to more- tively, using methods that compare surface heights We used the IOM to determine mass changes negative estimates of EAIS mass balance. Each measured along repeated ground tracks. This ap- of AIS and GrIS drainage basins between group made its own decisions on processing the proach provides fine along-track resolution with January 1992 and June 2010 (16). These results GRACE data, including how to combine results high precision (54). However, the ground tracks were derived according to the method of (57)and by using different GIA models, handle contam- are widely separated at lower latitudes, and the updated to include more recent data sets. SMB ination from external sources, compute uncer- elevation data are sparsely sampled in time be- estimates for Greenland as reported in (66)were tainties, and compute regional mass trends and cause of the episodic nature of mission cam- extended to the end of 2010. For Antarctica, the time series. Ice-sheet mass time series and trends paigns and the presence of clouds. The elevation SMB estimates of (61) were used, with an up- from all groups were then averaged to obtain the data were corrected for the effects of GIA by dated uncertainty estimate (28). Ice discharge individual GRACE results reported here. For all using the W12a model in Antarctica and a com- rates were updated by using new ice-thickness regions, the mass trends contributed by the in- bination of models in Greenland, and three groups measurements in the Bellingshausen Sea sec- dividual groups agree with the combined GRACE corrected AIS measurements for estimates of the tor, Wilkes Land, and the Amundsen Sea sec- trend to within the estimated uncertainties. systematic bias between mission campaigns (32). tor; at the grounding line of Filchner Ice Shelf; Results and Discussion A variety of approaches were used to isolate ob- and at Byrd and Lambert glaciers. Direct mea- servations affected by clouds and to interpolate surements of ice thickness are now available for We investigated the extent to which the indepen- elevation rates between ground tracks. Elevation nearly all WAIS ice streams. The IOM inven- dent geodetic techniques record similar fluctua- rates were adjusted for the effects of short-term tory, including measured and derived thick- tions in ice-sheet mass. First, we considered mass www.sciencemag.org SCIENCE VOL 338 30 NOVEMBER 2012 1185 REVIEW RESEARCH ARTICLES changes within 52 AIS glacier drainage basins as EAIS and WAIS that were beyond the scope of the resolution of the RA survey, such as the APIS determined by the techniques of satellite RA and IOM survey (55) to assess the extent to which (Fig. 1). IOM (Fig. 1), which are well suited to this task the two methods are complementary (Fig. 1). As a second example, we investigated the (14, 74). In each case, the 19-year average rate of These two areas, which typically fall between extent to which independent geodetic techniques mass loss from RAwas compared with values (55) glacier drainage basins of the IOM survey, have are able to detect fluctuations in SMB. For this −1 developed by using the IOM over a similar period. small imbalances (4.5 T 6.0 and 1.4 T 1.7 Gt year , exercise, we considered an exceptional snowfall The average difference between the estimates of for the EAIS and WAIS respectively), implying event in East Antarctica during the first half of −1 basin mass imbalance was 1.4 T 3.8 Gt year ,and that the region surveyed by the IOM is sufficient 2009 (Fig. 2). A snowfall anomaly that can be there is agreement within 1- and 2-sigma uncer- to capture the vast majority of the present EAIS identified in CloudSat precipitation data (75)here tainty estimates in 42 and 49 of the 52 basins, and WAIS mass imbalance. Furthermore, the is clearly apparent within the RACMO2 (and, respectively. Next, we computed the mass change IOM technique is able to resolve important mass hence, IOM), RA, and GRACE data sets, which as determined by satellite RA within areas of the changes in regions that are beyond the effective record the firn thickness and mass, volume, and WAIS EAIS APIS -20 -40 Fig. 1. Comparison of ice sheet mass balance estimates derived from 52 Antarctic drainage basins (55) and the dislocated regions of East and satellite RA (green) and the IOM (red) over the period 1992 to 2011, with West Antarctica that are omitted from the IOM survey (EAIS_OM and 1-sigma and 2-sigma error bars in dark and light shading, respectively, WAIS_OM, respectively). Basin locations are illustrated in the supplementary and mean values are shown in white. The comparison is performed for materials. A RACMO B RA C GRACE −0.4 −0.2 0.0 0.2 0.4 −0.4 −0.2 0.0 0.2 0.4 −0.2 −0.1 0.0 0.1 0.2 Mass change [m w.e.] Mass change [m w.e.] Mass change [m w.e.] Fig. 2. Estimated anomalies in cumulative ice-sheet firn mass (A), and mass (B and C), derived from the RACMO regional climate model, satellite RA, and GRACE GRACE satellite gravimetry, respectively, over a period of anomalously high Altimetry snowfall in East Antarctica. Anomalies were computed over the period July RACMO ERAI 2009 to July 2010 relative to July 2008 to July 2009. Before that, linear CFSR trends, as fitted to the 2003 to 2008 interval, were removed. The time MERRA evolution of the event, as resolved by these data sets and three additional climate models [ERA-Interim (ERAI), CFSR, and MERRA], is also illustrated (D) as the average anomaly over four drainage basins of Dronning Maud Land in East Antarctica (shaded areas in inset map). Although there are SMB fluctuations elsewhere during the same time interval, the pattern of mass loss in West Antarctica is primarily associated with longer-term ice-dynamical im- balance. Relatively large annual cycles are present within some RA time series, but they do not obscure either short- or long-lived events. m w.e., 2003 2004 2005 2006 2007 2008 2009 2010 2011 meters water equivalent. Calendar year 1186 30 NOVEMBER 2012 VOL 338 SCIENCE www.sciencemag.org Mass Balance (Gt/yr) PIG THW HSK FER ABO GET VEN HUL LAN MAC FOU INS COS INT ORV ECH BIN CAR RUT MOL WAIS OM EVA SUL WHI KAM COO SHI TOT MOS DAV FRO BEA Mass change [Gt] SCY PHI −100 0 100 200 300 AME DEN NIN STA QML RIL JEL MUL COA MER JUT EKS DIB VES BAI REN ROB LAM RAY BUD SUP NIM SLE HOL BYR EAIS OM REC LAB FLE WIL GVI STAN REVIEW RESEARCH ARTICLES mass fluctuations, respectively. The accumula- Input output method tion event affects the coastal region of the ice Radar altimetry Laser altimetry sheet, and, although the spatial pattern is best Gravimetry defined by the RACMO2 and altimeter data sets, it is also apparent in the coarser-resolution GRACE data set. Overall, around 200 Gt of additional snow mass was deposited in Dronning Maud Land during this event, equivalent to the mean annual snow accumulation in this sector of -200 Antarctica. In addition to the snowfall anomaly, the RA and GRACE data sets also include ice- dynamical mass changes that fluctuate over the survey period, such as the accelerated mass -400 losses in the Amundsen Sea sector. In pursuit of a comprehensive methodological intercomparison, we computed changes in the mass of each ice-sheet region between October -600 2003 and December 2008, the period when all Antarctic East West Antarctica & Greenland Antarctica Peninsula Antarctica Antarctica Greenland four satellite geodetic techniques were operat- ing optimally (Fig. 3 and table S2). During this Ice sheet 5-year period, which is short relative to the full Fig. 3. Intercomparison of mass balance estimates of the GrIS, APIS, EAIS, WAIS, AIS, and the AIS plus extent of the geodetic record and in comparison GrIS, derived from the four independent geodetic techniques of RA (cyan), IOM (red), LA (green), and to fluctuations in SMB, the arithmetic means of gravimetry (blue) over the period 2003 to 2008. Also shown is the reconciled result (gray). ice-sheet mass imbalance estimates derived from the available geodetic techniques were –72 T 43 −1 and –232 T 23 Gt year for the AIS and the GrIS, respectively. The technique-specific esti- Greenland West Antarctica mates agree with these mean values to within their respective uncertainties in all four ice-sheet 200 200 regions and for the AIS as a whole. The only exception is the LA estimate of the combined AIS and GrIS mass imbalance, which is, at 140 T 0 −1 133 Gt year , more positive than the mean value and only marginally beyond the 1-sigma uncer- tainty range of the respective values. Although the uncertainties of any one particular method are -200 -200 sometimes large, the combination of methods considerably improves the certainty of ice-sheet Input output method Input output method mass balance estimates. Gravimetry Laser altimetry Gravimetry -400 -400 To produce a reconciled ice-sheet mass ba- Radar altimetry Laser altimetry lance estimate, we computed the average rate of mass change derived from each of the geodetic East Antarctica Antarctic Peninsula techniques within the various regions of interest and over the time periods for which geodetic 200 200 mass rates were derived (Fig. 4). According to these data, ice-sheet mass balance varies cycli- cally and by large amounts over intermediate 0 0 (2- to 4-year) time periods. For example, during the period from 1992 to 2011, the WAIS mass balance fluctuated around a mean value in the −1 range from –50 to –100 Gt year , but there have -200 -200 been episodes of considerably larger growth and loss over shorter intervals. Similar variability is Input output method Input output method apparent in other sectors of the AIS and the GrIS. Gravimetry Gravimetry Laser altimetry -400 -400 We next calculated the linear average of the Laser altimetry Radar altimetry individual estimates of mass balance values to 1995 2000 2005 2010 1995 2000 2005 2010 arrive at reconciled values and integrated these Year Year data to form a time series of cumulative mass change within each of the four ice-sheet regions Fig. 4. Rate of mass change of the four main ice-sheet regions, as derived from the four techniques (Fig. 5). Although there are obvious dependen- of satellite RA (cyan), IOM (red), LA (green), and gravimetry (blue), with uncertainty ranges (light cies between the mass balance estimates produced shading). Rates of mass balance derived from ICESat LA data were computed as constant and time- by using each of the geodetic techniques, in- varying trends in Antarctica and Greenland, respectively. The gravimetry and RA mass trends were cluding, for example, the SMB data sets that computed after applying a 13-month moving average to the relative mass time series. Where temporal variations are resolved, there is often consistency in the interannual variability as determined by the are common to the IOM and LA processing, the independent data sets. GIA data sets that are common to the gravimetry www.sciencemag.org SCIENCE VOL 338 30 NOVEMBER 2012 1187 Mass Balance (Gt/yr) Mass Balance (Gt/yr) Mass Balance (Gt/yr) Mass Balance (Gt/yr) Mass Balance (Gt/yr) Sea level contribution (mm) Sea level contribution (mm) REVIEW RESEARCH ARTICLES and altimetry processing, and the orbital cor- We also computed ice-sheet mass trends over that the rate of mass loss has increased signifi- rections that are common to the LA and RA shorter intervals to examine their variability (Table cantly over time (Table 1). The pattern of WAIS systems, these dependencies are in practice dif- 1). These estimates, along with our integrated time imbalance is dominated by mass losses (Amundsen ficult to characterize. For the purpose of calcu- series (Fig. 5), confirm several known signals of Sea sector) and gains (Kamb Ice Stream) of dy- lating the reconciled ice-sheet mass balance mass imbalance, including increasing mass losses namical origin. Although close to balance during estimate, we considered IOM, gravimetry, and from the WAIS (55, 74–77), the APIS (73, 78–80), the 1990s, there have been significant mass altimetry to be independent geodetic techniques. and the GrIS (5, 81, 82). Although rates of mass losses from the APIS since then because of gla- On the basis of this assumption, we compute loss from the GrIS were modest during the cier acceleration in the wake of ice-shelf col- the standard error of the uncertainty estimates 1990s, they have increased sharply since then lapse (87, 88) and calving-front retreat (77, 89). from independent techniques as a measure of because of episodes of glacier acceleration (18, 83) The APIS now accounts for around 25% of all their collective uncertainty. Over the course of our and decreasing SMB (5, 66). GrIS glacier acceler- mass losses from Antarctic regions that are in a state 19-year survey, the average rates of mass balance ation is, however, neither uniform nor progres- of negative mass balance, despite occupying just of the AIS and the GrIS were –71 T 53 and –152 T sive (65, 84, 85), and the large mass losses in 4% of the continental area. In contrast, the EAIS, −1 49 Gt year , respectively (Table 1). For com- 2010 were in fact driven by anomalously low which occupies over 75% of Antarctica, was in pleteness, we also compute cumulative mass trends snow accumulation and high runoff (86). approximate balance throughout the 1990s. Al- by using the data from each individual geodetic The WAIS has lost mass throughout the entire though the EAIS has experienced mass gains technique (fig. S1). survey period, and our reconciled data set shows during the final years of our survey (Table 1 and Fig. 5), our reconciled data set is too short to determine whether they were caused by natural Fig. 5. Cumulative changes in 1000 fluctuations that are a common feature of Antarctic the mass of (left axis) the EAIS, -2 ice-core records (90) or long-term increases in WAIS, and APIS (top)and GrIS precipitation that are a common feature of global andAIS andthe combined change and regional climate model projections (91–93). of the AIS and GrIS (bottom), Both satellite altimeter data sets highlight the lower determined from a reconciliation reaches of the Cook and Totten Glaciers as re- of measurements acquired by gions of ice dynamical mass loss (15, 77), but satellite RA, the IOM, satellite -500 neither signal is large in comparison with the gravimetry, and satellite LA. Also 2 wider EAIS mass trend. Overall, snowfall-driven shown is the equivalent global -1000 mass gains in East Antarctica, notably the sea-level contribution (right axis), anomalous event in Dronning Maud Land during calculated assuming that 360 Gt East Antarctica 2009 (Fig. 2), have reduced the rate at which -1500 of ice corresponds to 1 mm of sea- West Antarctica Antarctic ice losses have increased over time, but level rise. Temporal variations in Antarctic Peninsula the EAIS record is too short to determine whether -2000 the availability of the various this is a long-term trend. satellite data sets (Fig. 4) means Our reconciliation exercise has highlighted that the reconciled mass balance is weighted toward different tech- several other issues. Assessments of GrIS mass niques during certain periods. balance require more careful consideration than 0 0 was possible here, because the surrounding moun- tain glaciers and ice caps are included in some, but -1000 not all, of our geodetic surveys and because the ice-sheet domains varied in area by 2%. One esti- −1 -2000 mate has put their contribution at ~20 Gt year (94), a value that falls between two we have derived ourselves from ICESat data (10 and 40 Gt -3000 −1 year ). For the EAIS, our mass change estimates Antarctica & Greenland exhibit an unsatisfactory spread, with results from -4000 Antarctica the IOM and LA techniques falling consistently Greenland lower and higher than the mean value we have -5000 derived (table S2). Although the average signal of 1995 2000 2005 2010 EAIS imbalance is relatively small, such a large Year divergence is a matter of concern; improvements of the ancillary data sets that support satellite ob- servations would be of considerable benefit in this Table 1. Reconciled ice-sheet mass balance estimates determined during various epochs, inclusive region. Lastly, the spatial sampling of mass fluc- of all data present during the given dates. The period 1993 to 2003 was used in an earlier tuations at the APIS is at present inadequate, assessment (2). particularly considering that it provides a signifi- cant component of the overall AIS imbalance. 1992–2011 1992–2000 1993–2003 2000–2011 2005–2010 Region Improvements in the spatial and temporal density (Gt/year) (Gt/ year) (Gt/ year) (Gt /year) (Gt/year) of satellite observations of this region are needed. 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UC Irvine UC Irvine Previously Published Works Title Permalink https://escholarship.org/uc/item/0vq404h7 Journal Science (New York, N.Y.), 338(6111) ISSN 0036-8075 Authors Shepherd, Andrew Ivins, Erik R A, Geruo et al. Publication Date 2012-11-01 DOI 10.1126/science.1228102 Supplemental Material https://escholarship.org/uc/item/0vq404h7#supplemental Copyright Information This work is made available under the terms of a Creative Commons Attribution License, availalbe at https://creativecommons.org/licenses/by/4.0/ Peer reviewed eScholarship.org Powered by the California Digital Library University of California REVIEW RESEARCH ARTICLES 15. P. Yin et al., Science 321, 824 (2008). 42. C. E. Castro et al., Nat. Methods 8, 221 (2011). the assembly. However, in practice, low yields 16. E. S. Andersen et al., Nature 459, 73 (2009). 43. Y. Ke, N. V. Voigt, K. V. Gothelf, W. M. Shih, J. Am. were already observed for larger designs (up to 17. Y. Ke et al., Nano Lett. 9, 2445 (2009). Chem. 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L.L.O. is supported by an technology has already started to address—for Struct. Biol. 16, 279 (2006). NSF graduate research fellowship. Y.K. conceived the example, to arrange technologically relevant guest 29. W. M. Shih, C. Lin, Curr. Opin. Struct. Biol. 20, 276 project, designed and performed the experiments, analyzed molecules into functional devices (6, 25, 32–34), (2010). the data, and wrote the paper; L.L.O. designed and performed 30. N. C. Seeman, Annu. Rev. Biochem. 79, 65 (2010). the experiments, analyzed the data, and wrote the paper; to serve as programmable molecular probes and 31. D. Y. Zhang, G. Seelig, Nat. Chem. 3, 103 (2011). W.M.S. conceived the project, discussed the results, and instruments for biological studies (33, 34, 36), 32. A. Kuzyk et al., Nature 483, 311 (2012). wrote the paper; P.Y. conceived, designed, and supervised to render spatial control for biosynthesis of use- 33. H. M. T. Choi et al., Nat. Biotechnol. 28, 1208 (2010). the study, interpreted the data, and wrote the paper. The ful products (25), to function as smart drug deliv- 34. C. Lin et al., Nat. Chem. 4, 832 (2012). DNA sequences for the nanostructures can be found in the 35. M. J. Berardi, W. M. Shih, S. C. Harrison, J. J. Chou, supplementary materials. A provisional patent has been ery particles (37), and to enable high-throughput Nature 476, 109 (2011). filed based on this work. nanofabrication of complex inorganic materials 36. N. D. Derr et al., Science 338, 662 (2012). for electronics or photonics applications (6, 32). 37. S. M. Douglas, I. Bachelet, G. M. Church, Science 335, Supplementary Materials The modularity of the brick structure may facil- 831 (2012). www.sciencemag.org/cgi/content/full/338/6111/1177/DC1 itate rapid prototyping of diverse functional nano- 38. P. W. K. Rothemund, E. S. Andersen, Nature 485, 584 Materials and Methods (2012). devices. Its sophisticated and refined geometrical Supplementary Text 39. Materials and methods, supplementary figures and texts, control may enable applications that require high- Figs. S1 to S66 and DNA sequences are available as supplementary Tables S1 to S20 precision arrangements of guest molecules. Be- materials on Science Online. cause the brick structure is composed entirely of 40. S. M. Douglas et al., Nucleic Acids Res. 37, 5001 (2009). 11 July 2012; accepted 16 October 2012 short synthetic strands (no biologically derived 41. Y. Ke et al., J. Am. Chem. Soc. 131, 15903 (2009). 10.1126/science.1227268 scaffold), it is conceivable to make bricks by using synthetic informational polymers other than the natural form of DNA. Such polymers may in- clude L-DNA (26), DNA with chemically modi- A Reconciled Estimate of Ice-Sheet fied backbones or artificial bases, or chemically synthesized or in vitro (or even in vivo) transcribed RNA. This material diversity may potentially Mass Balance produce nanostructures with not only prescribed shapes but also designer chemical (or bio- 1 2 3 4 5 Andrew Shepherd, * Erik R. Ivins, * Geruo A, Valentina R. Barletta, Mike J. Bentley, chemical) properties (such as nuclease resistance 6 1 7 4 8 Srinivas Bettadpur, Kate H. Briggs, David H. Bromwich, René Forsberg, Natalia Galin, or reduced immunogenicity) that would be useful 9 10 11 12,27 13 14 Martin Horwath, Stan Jacobs, Ian Joughin, Matt A. King, Jan T. M. Lenaerts, Jilu Li, for diverse applications requiring the structure to 13 15 16 1 Stefan R. M. Ligtenberg, Adrian Luckman, Scott B. Luthcke, Malcolm McMillan, function robustly in complex environments, 8 17 18 8 7 14 Rakia Meister, Glenn Milne, Jeremie Mouginot, Alan Muir, Julien P. Nicolas, John Paden, such as in living cells or organisms. 19 20 18,2 21 4 Antony J. Payne, Hamish Pritchard, Eric Rignot, Helmut Rott, Louise Sandberg Sørensen, 22 18 23 11 1 Ted A. Scambos, Bernd Scheuchl, Ernst J. O. Schrama, Ben Smith, Aud V. Sundal, 13 13 13 20 References and Notes Jan H. van Angelen, Willem J. van de Berg, Michiel R. van den Broeke, David G. Vaughan, 1. N. C. Seeman, J. Theor. Biol. 99, 237 (1982). 18,2 3 5 8 24 Isabella Velicogna, John Wahr, Pippa L. Whitehouse, Duncan J. Wingham, Donghui Yi, 2. J. H. Chen, N. C. Seeman, Nature 350, 631 (1991). 25 26 Duncan Young, H. Jay Zwally 3. T. J. Fu, N. C. Seeman, Biochemistry 32, 3211 (1993). 4. E. Winfree, F. Liu, L. A. Wenzler, N. C. Seeman, Nature 394, 539 (1998). 5. B. Yurke, A. J. Turberfield, A. P. Mills Jr., F. C. Simmel, We combined an ensemble of satellite altimetry, interferometry, and gravimetry data sets using J. L. Neumann, Nature 406, 605 (2000). common geographical regions, time intervals, and models of surface mass balance and 6. H. Yan, S. H. Park, G. Finkelstein, J. H. Reif, T. H. LaBean, glacial isostatic adjustment to estimate the mass balance of Earth’s polar ice sheets. We find that Science 301, 1882 (2003). there is good agreement between different satellite methods—especially in Greenland and 7. W. B. Sherman, N. C. Seeman, Nano Lett. 4, 1203 West Antarctica—and that combining satellite data sets leads to greater certainty. Between 1992 (2004). 8. P. W. K. Rothemund, N. Papadakis, E. Winfree, PLoS Biol. and 2011, the ice sheets of Greenland, East Antarctica, West Antarctica, and the Antarctic −1 2, e424 (2004). Peninsula changed in mass by –142 T 49, +14 T 43, –65 T 26, and –20 T 14 gigatonnes year , 9. A. Chworos et al., Science 306, 2068 (2004). respectively. Since 1992, the polar ice sheets have contributed, on average, 0.59 T 0.20 millimeter 10. S. H. Park et al., Angew. Chem. Int. Ed. 45, 735 −1 year to the rate of global sea-level rise. (2006). 11. P. W. K. Rothemund, Nature 440, 297 (2006). 12. G. Seelig, D. Soloveichik, D. Y. Zhang, E. Winfree, Science luctuations in the mass of the polar ice a consequence of their internal dynamics and 314, 1585 (2006). sheets are of considerable societal impor- changes in atmospheric and oceanic conditions 13. Y. He et al., Nature 452, 198 (2008). Ftance, because they affect global sea lev- (3–5). Analysis of the geological record sug- 14. P. Yin, H. M. T. Choi, C. R. Calvert, N. A. Pierce, Nature 451, 318 (2008). els (1, 2) and oceanic conditions. They occur as gests that past climatic changes have precipitated www.sciencemag.org SCIENCE VOL 338 30 NOVEMBER 2012 118 REVIEW RESEARCH ARTICLES sustained ice-sheet contributions, in excess of balance of between –676 and +69 gigatonnes al data sets, so we assess the temporal uncertainty −1 −1 10 mm year over millennial time periods (6), (Gt) year , equivalent to a mean global sea-level through comparison with global atmospheric −1 and the prospect of such changes in the future are contribution in the range of +1.9 to–0.2 mm year . reanalyses (16). We also useRACMO2todrive of greatest concern. Even the modest rises in However, much of this spread, which is large in a model of AIS firn densification (29) for the ocean temperature that are predicted over the comparison to other ice-sheet imbalance assess- purpose of converting satellite LA observations coming century (7) could trigger substantial ice- ments (1, 2) and to the estimated rate of global into changes in ice-sheet mass. sheet mass loss through enhanced melting of ice sea-level rise (17), is due to the brevity of many Glacial isostatic adjustment (GIA). GIA of the shelves (8–10) and outlet glaciers (11, 12). How- satellite surveys (4.5 years, on average) relative solid Earth is an important contributor to the ever, these processes were not incorporated into to the rate at which ice-sheet mass fluctuates signals observed by satellite gravimetry and, to a the ice-sheet models that informed the current glob- (5, 18–20). Because the various satellite methods lesser extent, satellite altimetry (30). The GIA al climate projections (13). Until this is achieved, differ in their strengths and weaknesses (14, 15, 21), must therefore be considered when estimating ice- observations of ice-sheet mass imbalance remain careful consideration ought to make them com- sheet mass balance with either technique. In essential in determining their contribution to sea plementary. Here, we compare and combine es- Antarctica, the use of GIA models has in prac- level. timates of ice-sheet mass balance derived from tice introduced considerable uncertainty (up to −1 Satellite geodesy has revolutionized the manner all three satellite geodetic techniques, using com- 130 Gt year ) into ice-sheet mass balance estimates in which ice-sheet mass balance is estimated mon spatial and temporal domains, to investigate derived from satellite gravimetry (31–33). There (14, 15). Since 1998, there have been at least 29 the extent to which the approaches concur and to are a number of contributory factors to this un- ice-sheet mass balance estimates, based variously produce a reconciled estimate of ice-sheet mass certainty, including the scarcity of constraints on on the satellite techniques of altimetry, interfer- balance. the evolution of the ice sheet since the Last ometry, and gravimetry (16). These estimates, and Glacial Maximum (LGM), limited knowledge of Data and Methods their respective uncertainties, allow for a com- Earth mechanical properties, and the scarcity of bined Greenland and Antarctic ice-sheet mass im- In this assessment, we use 19 years of satellite near-field relative sea-level and vertical crustal radar altimeter (RA) data, 5 years of satellite laser motion data with which to evaluate model per- altimeter (LA) data, 19 years of satellite radar formance (34, 35). School of Earth and Environment, University of Leeds, Leeds LS2 9JT, UK. Jet Propulsion Laboratory, M/S 300-233, 4800 interferometer data, 8 years of satellite gravime- Here, we consider variants of six GIA mod- Oak Grove Drive, Pasadena, CA 91109, USA. Department of try data, 32 years of surface mass balance (SMB) els, and we assess their impact on geodetic ice- Physics, University of Colorado, Boulder, CO 80309–0390, model simulations, and estimates from several sheet mass balance estimates. For Greenland, USA. Geodynamics Department, Technical University of Den- glacial isostatic adjustment models, to produce a where the signal of GIA is relatively small and mark, DTU SPACE, National Space Institute, Elektrovej, Build- reconciled estimate of ice-sheet mass balance. The well constrained, we use the Simpson (36), ICE- ing327,DK-2800 Kgs.Lyngby, Denmark. Department of Geography, Durham University, South Road, Durham DH1 3LE, satellite data sets were developed by using in- 5G (37), and ANU (38) models. For Antarctica, UK. Center for Space Research, University of Texas at Austin, dependent methods and, in the case of the LA, we compare the ICE-5G model (39)withtwo 3925 West Braker Lane, Suite 200, Austin, TX 78759–5321, USA. 7 gravimeter, and SMB data sets, through contribu- recent Antarctic GIA models: the W12a model Polar Meteorology Group, Byrd Polar Research Center, and tions from numerous research groups. To enable a (35, 40) and a version (IJ05_R2) of the IJ05 model Atmospheric Sciences Program, Department of Geography, The Ohio State University, 1090 Carmack Road, Columbus, OH 43210, direct comparison, we reprocessed the geodetic (41) updated for this study (16). Both regional USA. Centre for Polar Observation and Modelling, Department data sets with use of common time intervals and GIA models incorporate recently improved con- of Earth Sciences, University College London, London WC1E 9 common definitions of the East Antarctic, West straints on the ice-loading history (42–45)that 6BT, UK. Institut für Astronomische und Physikalische Geodäsie, Antarctic, Antarctic Peninsula, and Greenland ice- suggest that the AIS was thinner at the LGM than Technische Universität München, Arcisstraße 21, 80333 München, Germany. Lamont-Doherty Earth Observatory (LDEO), 205 sheet (EAIS, WAIS, APIS, and GrIS, respectively) previously thought, leading to a lowering of es- Oceanography, 61 Route 9W - Post Office Box 1000, Palisades, boundaries (16). The maximum temporal extent timated ice-sheet mass losses since that time NY 10964, USA. Polar Science Center, Applied Physics Labora- of the satellite data sets spans the period 1992 to (40, 45). Although a consequence of this re- tory, University of Washington, 1013 NE 40th Street, Seattle, WA 2011, and results from all geodetic techniques are vision is a potential discrepancy between far-field 98105–6698, USA. School of Civil Engineering and Geo- sciences, Cassie Building, Newcastle University, Newcastle upon available between January 2003 and December sea-level records and commonly accepted North- Tyne NE1 7RU, UK. Utrecht University, Institute for Marine and 2008. Unless stated otherwise, all results are ern Hemisphere deglaciation models, both of the Atmospheric Research, Princetonplein 5, Utrecht, Netherlands. presented with 1-sigma uncertainty estimates. new regional GIA models perform well when Center for Remote Sensing of Ice Sheets, University of Kansas, Ice-sheet surface mass balance. SMB in- compared with Antarctic Global Positioning Sys- Nichols Hall, 2335 Irving Hill Road, Lawrence, KS 66045, USA. cludes solid and liquid precipitation, surface sub- tem (GPS) observations (34), and we conclude Department of Geography, College of Science, Swansea Uni- versity, Singleton Park, Swansea SA2 8PP, UK. National Aero- limation, drifting snow transport, erosion and that these latest solutions are best suited for esti- nautical and Space Administration (NASA) Goddard Space Flight sublimation, and meltwater formation, refreez- mating AIS mass balance. Center, Planetary Geodynamics Laboratory, Greenbelt, MD 20771, 17 ing, retention, and runoff. Our estimates of the Radar and laser altimetry. RA and LA pro- USA. Department of Earth Sciences, University of Ottawa, Antarctic Ice Sheet (AIS) and the GrIS SMB are vide ice-sheet mass balance estimates through Ottawa, Ontario K1N 6N5, Canada. Department of Earth Sys- tem Science, University of California, 3226 Croul Hall, Irvine, CA derived from reconstructions of the RACMO2 measurements of ice-sheet volume change. The 92697–3100, USA. School of Geographical Sciences, Uni- regional atmospheric climate model (22)over technique has been applied to both Greenland versity of Bristol, Bristol BS8 1SS, UK. British Antarctic Survey, 21 the period 1979 to 2010, with horizontal reso- (46–48) and Antarctica (4, 47, 49) and is unique High Cross, Madingley Road, Cambridge CB3 0ET, UK. Insti- lutions of 27 (AIS) and 11 (GrIS) km. RACMO2 in spatially resolving the detailed pattern of mass tute of Meteorology and Geophysics, University of Innsbruck, Innsbruck, Austria. National Snow and Ice Data Center, Uni- has a multilayer snowpack with drifting snow and imbalance, with monthly temporal sampling. RA versity of Colorado, Boulder, CO 80309, USA. Delft University snow albedo schemes (23) and has been evalu- provides the longest continuous record of all geo- of Technology, Faculty of Aerospace Engineering, Kluyverweg 1, ated against in situ temperature, wind, and surface- detic techniques (50). Altimeter measurements of 2629 HS Delft, Netherlands. SGT Incorporated, NASA Goddard energy balance observations from weather stations elevation change are precise, because they require Space Flight Center, Cryospheric Sciences Laboratory, Code 615 (24–26) as well as satellite-derived estimates of melt only modest adjustments to account for sensor Greenbelt, MD 20771, USA. Institute for Geophysics, University of Texas, Austin, TX 78759, USA. NASA Goddard Space Flight extent, mass changes, and drifting snow (5, 26, 27). drift, changes in the satellite attitude, atmospheric Center, Cryospheric Sciences Laboratory, Code 615 Greenbelt, The spatial uncertainty of the RACMO2 mean attenuation, and movements of Earth’s surface. MD 20771, USA. School of Geography and Environmental SMB has been assessed through comparison with By far the greatest uncertainty lies in the con- Studies, University of Tasmania, Hobart 7001, Australia. 310 (GrIS) and 1850 (AIS) in situ observations version from volume to mass change. In the case *To whom correspondence should be addressed. E-mail: (28). However, temporal fluctuations in snow of LA, this conversion has been performed by [email protected] (A.S.); [email protected] (E.R.I.) accumulation are poorly resolved in observation- using an external model of fluctuations in the firn- 1184 30 NOVEMBER 2012 VOL 338 SCIENCE www.sciencemag.org REVIEW RESEARCH ARTICLES layer thickness (29, 48, 51). In the case of RA, the fluctuations in firn thickness by using models nesses, now encompasses 64, 79, 96, and 93% of conversion to mass has been performed by using driven by either regional climate model predic- the APIS, EAIS, WAIS, and GrIS, respectively; a prescribed density model and by allowing for tions (29) or by remotely sensed estimates of the remainder is assumed to have no loss due to temporal fluctuations in snowfall in the uncer- temperature (48, 51). The error budget was cal- ice dynamics. tainty (52). culated from uncertainties in the corrected height Gravimetry. The Gravity Recovery and Climate We used European Remote-Sensing (ERS-1 measurements, in the correction for change in Experiment (GRACE) satellite mission has and ERS-2) satellite and Envisat 35-day repeat firn thickness, and in the estimated SMB. The allowed fluctuations in ice-sheet mass to be esti- satellite RA observations to determine changes in mass-change estimates reported here are the arith- mated through measurement of their changing the mass of the EAIS and WAIS between May metic average of those obtained by the different gravitational attraction (32, 67–69). Advantages 1992 and September 2010 (16). Time series of sur- groups. of the GRACE method are that it provides face elevation change were developed at 39,375 Input-output method (IOM). The IOM quan- regional averages without the need for interpola- crossing points of the satellite orbit ground tracks tifies the difference between glacier mass gained tion, measures the effect of mass fluctuations by using dual-cycle crossovers (49, 53). In total, through snowfall and lost by sublimation and directly, and permits monthly temporal sampling. 46.5 million measurements were included in this meltwater runoff and the discharge of ice into the However, a key challenge is to discriminate analysis, encompassing 74 and 76% of the EAIS ocean. The approach has the advantage of al- fluctuations in ice-sheet mass from changes in the and WAIS, respectively. The satellites were cross- lowing changes in SMB and ice dynamics to be underlying crust and mantle. This is achieved by calibrated by considering differences between ele- examined separately at the scale of individual using models of GIA, which, in the case of the vation changes occurring during periods of mission glacier drainage basins (5) and has been used in AIS, has led to significant adjustments (70). The overlap. Elevation data were corrected for the lag numerous assessments of AIS and GrIS mass ba- spatial resolution of GRACE observations de- of the leading-edge tracker and for variations lance (18, 55–57). Although earlier IOM studies rived from global spherical harmonic solutions in dry atmospheric mass, water vapor, the iono- used representations of SMB developed from of about 300 km in the polar regions (71)is sphere, solid Earth tides, and surface scattering guided interpolation of sparse ground observations coarse in comparison to that of other geodetic (50). The IJ05_R2 model was used to correct (58–60), regional atmospheric climate models techniques. Hence, a further complicating factor for elevation changes associated with GIA. Mass (5, 61) are now used because they provide sub- is that signals may leak into regional GRACE changes were calculated by using a surface-density daily predictions at high spatial resolution that solutions as a consequence of remote geophysi- −3 model with a nominal density for firn (400 kg m ) are independent of the in situ observations. When cal processes. In circumstances where spatial applied to all regions other than those in which evaluated against such data, SMB model errors relationships between geophysical mass fluxes changes are assumed to occur at the density of ice are found to range between 5 and 20%, depend- can be adequately characterized, application of −3 the mass concentration unit (mascon) method (900 kg m )(52). Rates of mass change were ing on the basin size and location, with propor- computed in regions of interest by interpolating tionately the largest uncertainties occurring in (68, 72, 73) introduces a capacity to study changes measurements derived at satellite-orbit crossing regions of extreme (low or high) precipitation, at smaller scales. points and by extrapolating these results to un- strong melting, or where the model resolution is Data from the GRACE satellite mission were observed area. To estimate the uncertainty of mass too coarse. Quantifying ice-stream discharge re- used to estimate changes in the mass of the AIS trends, we treated the estimated variability of snow- quires measurements of ice velocity and thickness and GrIS between January 2003 and December fall (49) and the elevation trend variability as at the grounding line. Ice-sheet velocity snapshots 2010 (16). Analysis methods varied between the equivalent sources of uncertainty. This approach have been widely measured by using interfero- six groups who contributed these observations; is used because it has not yet proved possible to metric synthetic aperture radar (InSAR) with high some used the mascon approach, whereas others separate, in the observed elevation change, an- (<3%) accuracy (62, 63) and relatively low (an- used spatial-averaging kernels. The GRACE data nual cycles due to density fluctuations from res- nual or longer) frequency. The thickness of many were corrected for the effects of GIA by using the idual variations due to signal penetration into ice streams has been directly measured by using Simpson, ANU, and ICE-5G models in Green- the firn. airborne radar with high (~10 m) accuracy (64). land and the W12a, IJ05_R2, and ICE-5G mod- We used ICESat (Ice, Cloud, and Land Ele- Nonetheless, there are many ice-sheet outlet gla- els in Antarctica. Although we only include vation Satellite) LA observations acquired be- ciers for which such data do not exist; in these results using the W12a and IJ05_R2 models in tween September 2003 and November 2008 (the regions, less accurate methods are used to cal- our reconciled estimates for Antarctica, we also period of optimal instrument calibration) to es- culate thickness with uncertainties in the range of provide separate ice-sheet mass balance estimates timate changes in the mass of the AIS and GrIS 80 to 120 m (18, 55). Lastly, where thinning rates determined by using the ICE-5G GIA model (16). AIS and GrIS elevation rates were com- are large, the temporal evolution of ice thick- solution (16) to allow comparison with previous- puted by four and two different groups, respec- ness should be accounted for (65). ly published estimates; its use leads to more- tively, using methods that compare surface heights We used the IOM to determine mass changes negative estimates of EAIS mass balance. Each measured along repeated ground tracks. This ap- of AIS and GrIS drainage basins between group made its own decisions on processing the proach provides fine along-track resolution with January 1992 and June 2010 (16). These results GRACE data, including how to combine results high precision (54). However, the ground tracks were derived according to the method of (57)and by using different GIA models, handle contam- are widely separated at lower latitudes, and the updated to include more recent data sets. SMB ination from external sources, compute uncer- elevation data are sparsely sampled in time be- estimates for Greenland as reported in (66)were tainties, and compute regional mass trends and cause of the episodic nature of mission cam- extended to the end of 2010. For Antarctica, the time series. Ice-sheet mass time series and trends paigns and the presence of clouds. The elevation SMB estimates of (61) were used, with an up- from all groups were then averaged to obtain the data were corrected for the effects of GIA by dated uncertainty estimate (28). Ice discharge individual GRACE results reported here. For all using the W12a model in Antarctica and a com- rates were updated by using new ice-thickness regions, the mass trends contributed by the in- bination of models in Greenland, and three groups measurements in the Bellingshausen Sea sec- dividual groups agree with the combined GRACE corrected AIS measurements for estimates of the tor, Wilkes Land, and the Amundsen Sea sec- trend to within the estimated uncertainties. systematic bias between mission campaigns (32). tor; at the grounding line of Filchner Ice Shelf; Results and Discussion A variety of approaches were used to isolate ob- and at Byrd and Lambert glaciers. Direct mea- servations affected by clouds and to interpolate surements of ice thickness are now available for We investigated the extent to which the indepen- elevation rates between ground tracks. Elevation nearly all WAIS ice streams. The IOM inven- dent geodetic techniques record similar fluctua- rates were adjusted for the effects of short-term tory, including measured and derived thick- tions in ice-sheet mass. First, we considered mass www.sciencemag.org SCIENCE VOL 338 30 NOVEMBER 2012 1185 REVIEW RESEARCH ARTICLES changes within 52 AIS glacier drainage basins as EAIS and WAIS that were beyond the scope of the resolution of the RA survey, such as the APIS determined by the techniques of satellite RA and IOM survey (55) to assess the extent to which (Fig. 1). IOM (Fig. 1), which are well suited to this task the two methods are complementary (Fig. 1). As a second example, we investigated the (14, 74). In each case, the 19-year average rate of These two areas, which typically fall between extent to which independent geodetic techniques mass loss from RAwas compared with values (55) glacier drainage basins of the IOM survey, have are able to detect fluctuations in SMB. For this −1 developed by using the IOM over a similar period. small imbalances (4.5 T 6.0 and 1.4 T 1.7 Gt year , exercise, we considered an exceptional snowfall The average difference between the estimates of for the EAIS and WAIS respectively), implying event in East Antarctica during the first half of −1 basin mass imbalance was 1.4 T 3.8 Gt year ,and that the region surveyed by the IOM is sufficient 2009 (Fig. 2). A snowfall anomaly that can be there is agreement within 1- and 2-sigma uncer- to capture the vast majority of the present EAIS identified in CloudSat precipitation data (75)here tainty estimates in 42 and 49 of the 52 basins, and WAIS mass imbalance. Furthermore, the is clearly apparent within the RACMO2 (and, respectively. Next, we computed the mass change IOM technique is able to resolve important mass hence, IOM), RA, and GRACE data sets, which as determined by satellite RA within areas of the changes in regions that are beyond the effective record the firn thickness and mass, volume, and WAIS EAIS APIS -20 -40 Fig. 1. Comparison of ice sheet mass balance estimates derived from 52 Antarctic drainage basins (55) and the dislocated regions of East and satellite RA (green) and the IOM (red) over the period 1992 to 2011, with West Antarctica that are omitted from the IOM survey (EAIS_OM and 1-sigma and 2-sigma error bars in dark and light shading, respectively, WAIS_OM, respectively). Basin locations are illustrated in the supplementary and mean values are shown in white. The comparison is performed for materials. A RACMO B RA C GRACE −0.4 −0.2 0.0 0.2 0.4 −0.4 −0.2 0.0 0.2 0.4 −0.2 −0.1 0.0 0.1 0.2 Mass change [m w.e.] Mass change [m w.e.] Mass change [m w.e.] Fig. 2. Estimated anomalies in cumulative ice-sheet firn mass (A), and mass (B and C), derived from the RACMO regional climate model, satellite RA, and GRACE GRACE satellite gravimetry, respectively, over a period of anomalously high Altimetry snowfall in East Antarctica. Anomalies were computed over the period July RACMO ERAI 2009 to July 2010 relative to July 2008 to July 2009. Before that, linear CFSR trends, as fitted to the 2003 to 2008 interval, were removed. The time MERRA evolution of the event, as resolved by these data sets and three additional climate models [ERA-Interim (ERAI), CFSR, and MERRA], is also illustrated (D) as the average anomaly over four drainage basins of Dronning Maud Land in East Antarctica (shaded areas in inset map). Although there are SMB fluctuations elsewhere during the same time interval, the pattern of mass loss in West Antarctica is primarily associated with longer-term ice-dynamical im- balance. Relatively large annual cycles are present within some RA time series, but they do not obscure either short- or long-lived events. m w.e., 2003 2004 2005 2006 2007 2008 2009 2010 2011 meters water equivalent. Calendar year 1186 30 NOVEMBER 2012 VOL 338 SCIENCE www.sciencemag.org Mass Balance (Gt/yr) PIG THW HSK FER ABO GET VEN HUL LAN MAC FOU INS COS INT ORV ECH BIN CAR RUT MOL WAIS OM EVA SUL WHI KAM COO SHI TOT MOS DAV FRO BEA Mass change [Gt] SCY PHI −100 0 100 200 300 AME DEN NIN STA QML RIL JEL MUL COA MER JUT EKS DIB VES BAI REN ROB LAM RAY BUD SUP NIM SLE HOL BYR EAIS OM REC LAB FLE WIL GVI STAN REVIEW RESEARCH ARTICLES mass fluctuations, respectively. The accumula- Input output method tion event affects the coastal region of the ice Radar altimetry Laser altimetry sheet, and, although the spatial pattern is best Gravimetry defined by the RACMO2 and altimeter data sets, it is also apparent in the coarser-resolution GRACE data set. Overall, around 200 Gt of additional snow mass was deposited in Dronning Maud Land during this event, equivalent to the mean annual snow accumulation in this sector of -200 Antarctica. In addition to the snowfall anomaly, the RA and GRACE data sets also include ice- dynamical mass changes that fluctuate over the survey period, such as the accelerated mass -400 losses in the Amundsen Sea sector. In pursuit of a comprehensive methodological intercomparison, we computed changes in the mass of each ice-sheet region between October -600 2003 and December 2008, the period when all Antarctic East West Antarctica & Greenland Antarctica Peninsula Antarctica Antarctica Greenland four satellite geodetic techniques were operat- ing optimally (Fig. 3 and table S2). During this Ice sheet 5-year period, which is short relative to the full Fig. 3. Intercomparison of mass balance estimates of the GrIS, APIS, EAIS, WAIS, AIS, and the AIS plus extent of the geodetic record and in comparison GrIS, derived from the four independent geodetic techniques of RA (cyan), IOM (red), LA (green), and to fluctuations in SMB, the arithmetic means of gravimetry (blue) over the period 2003 to 2008. Also shown is the reconciled result (gray). ice-sheet mass imbalance estimates derived from the available geodetic techniques were –72 T 43 −1 and –232 T 23 Gt year for the AIS and the GrIS, respectively. The technique-specific esti- Greenland West Antarctica mates agree with these mean values to within their respective uncertainties in all four ice-sheet 200 200 regions and for the AIS as a whole. The only exception is the LA estimate of the combined AIS and GrIS mass imbalance, which is, at 140 T 0 −1 133 Gt year , more positive than the mean value and only marginally beyond the 1-sigma uncer- tainty range of the respective values. Although the uncertainties of any one particular method are -200 -200 sometimes large, the combination of methods considerably improves the certainty of ice-sheet Input output method Input output method mass balance estimates. Gravimetry Laser altimetry Gravimetry -400 -400 To produce a reconciled ice-sheet mass ba- Radar altimetry Laser altimetry lance estimate, we computed the average rate of mass change derived from each of the geodetic East Antarctica Antarctic Peninsula techniques within the various regions of interest and over the time periods for which geodetic 200 200 mass rates were derived (Fig. 4). According to these data, ice-sheet mass balance varies cycli- cally and by large amounts over intermediate 0 0 (2- to 4-year) time periods. For example, during the period from 1992 to 2011, the WAIS mass balance fluctuated around a mean value in the −1 range from –50 to –100 Gt year , but there have -200 -200 been episodes of considerably larger growth and loss over shorter intervals. Similar variability is Input output method Input output method apparent in other sectors of the AIS and the GrIS. Gravimetry Gravimetry Laser altimetry -400 -400 We next calculated the linear average of the Laser altimetry Radar altimetry individual estimates of mass balance values to 1995 2000 2005 2010 1995 2000 2005 2010 arrive at reconciled values and integrated these Year Year data to form a time series of cumulative mass change within each of the four ice-sheet regions Fig. 4. Rate of mass change of the four main ice-sheet regions, as derived from the four techniques (Fig. 5). Although there are obvious dependen- of satellite RA (cyan), IOM (red), LA (green), and gravimetry (blue), with uncertainty ranges (light cies between the mass balance estimates produced shading). Rates of mass balance derived from ICESat LA data were computed as constant and time- by using each of the geodetic techniques, in- varying trends in Antarctica and Greenland, respectively. The gravimetry and RA mass trends were cluding, for example, the SMB data sets that computed after applying a 13-month moving average to the relative mass time series. Where temporal variations are resolved, there is often consistency in the interannual variability as determined by the are common to the IOM and LA processing, the independent data sets. GIA data sets that are common to the gravimetry www.sciencemag.org SCIENCE VOL 338 30 NOVEMBER 2012 1187 Mass Balance (Gt/yr) Mass Balance (Gt/yr) Mass Balance (Gt/yr) Mass Balance (Gt/yr) Mass Balance (Gt/yr) Sea level contribution (mm) Sea level contribution (mm) REVIEW RESEARCH ARTICLES and altimetry processing, and the orbital cor- We also computed ice-sheet mass trends over that the rate of mass loss has increased signifi- rections that are common to the LA and RA shorter intervals to examine their variability (Table cantly over time (Table 1). The pattern of WAIS systems, these dependencies are in practice dif- 1). These estimates, along with our integrated time imbalance is dominated by mass losses (Amundsen ficult to characterize. For the purpose of calcu- series (Fig. 5), confirm several known signals of Sea sector) and gains (Kamb Ice Stream) of dy- lating the reconciled ice-sheet mass balance mass imbalance, including increasing mass losses namical origin. Although close to balance during estimate, we considered IOM, gravimetry, and from the WAIS (55, 74–77), the APIS (73, 78–80), the 1990s, there have been significant mass altimetry to be independent geodetic techniques. and the GrIS (5, 81, 82). Although rates of mass losses from the APIS since then because of gla- On the basis of this assumption, we compute loss from the GrIS were modest during the cier acceleration in the wake of ice-shelf col- the standard error of the uncertainty estimates 1990s, they have increased sharply since then lapse (87, 88) and calving-front retreat (77, 89). from independent techniques as a measure of because of episodes of glacier acceleration (18, 83) The APIS now accounts for around 25% of all their collective uncertainty. Over the course of our and decreasing SMB (5, 66). GrIS glacier acceler- mass losses from Antarctic regions that are in a state 19-year survey, the average rates of mass balance ation is, however, neither uniform nor progres- of negative mass balance, despite occupying just of the AIS and the GrIS were –71 T 53 and –152 T sive (65, 84, 85), and the large mass losses in 4% of the continental area. In contrast, the EAIS, −1 49 Gt year , respectively (Table 1). For com- 2010 were in fact driven by anomalously low which occupies over 75% of Antarctica, was in pleteness, we also compute cumulative mass trends snow accumulation and high runoff (86). approximate balance throughout the 1990s. Al- by using the data from each individual geodetic The WAIS has lost mass throughout the entire though the EAIS has experienced mass gains technique (fig. S1). survey period, and our reconciled data set shows during the final years of our survey (Table 1 and Fig. 5), our reconciled data set is too short to determine whether they were caused by natural Fig. 5. Cumulative changes in 1000 fluctuations that are a common feature of Antarctic the mass of (left axis) the EAIS, -2 ice-core records (90) or long-term increases in WAIS, and APIS (top)and GrIS precipitation that are a common feature of global andAIS andthe combined change and regional climate model projections (91–93). of the AIS and GrIS (bottom), Both satellite altimeter data sets highlight the lower determined from a reconciliation reaches of the Cook and Totten Glaciers as re- of measurements acquired by gions of ice dynamical mass loss (15, 77), but satellite RA, the IOM, satellite -500 neither signal is large in comparison with the gravimetry, and satellite LA. Also 2 wider EAIS mass trend. Overall, snowfall-driven shown is the equivalent global -1000 mass gains in East Antarctica, notably the sea-level contribution (right axis), anomalous event in Dronning Maud Land during calculated assuming that 360 Gt East Antarctica 2009 (Fig. 2), have reduced the rate at which -1500 of ice corresponds to 1 mm of sea- West Antarctica Antarctic ice losses have increased over time, but level rise. Temporal variations in Antarctic Peninsula the EAIS record is too short to determine whether -2000 the availability of the various this is a long-term trend. satellite data sets (Fig. 4) means Our reconciliation exercise has highlighted that the reconciled mass balance is weighted toward different tech- several other issues. Assessments of GrIS mass niques during certain periods. balance require more careful consideration than 0 0 was possible here, because the surrounding moun- tain glaciers and ice caps are included in some, but -1000 not all, of our geodetic surveys and because the ice-sheet domains varied in area by 2%. One esti- −1 -2000 mate has put their contribution at ~20 Gt year (94), a value that falls between two we have derived ourselves from ICESat data (10 and 40 Gt -3000 −1 year ). For the EAIS, our mass change estimates Antarctica & Greenland exhibit an unsatisfactory spread, with results from -4000 Antarctica the IOM and LA techniques falling consistently Greenland lower and higher than the mean value we have -5000 derived (table S2). Although the average signal of 1995 2000 2005 2010 EAIS imbalance is relatively small, such a large Year divergence is a matter of concern; improvements of the ancillary data sets that support satellite ob- servations would be of considerable benefit in this Table 1. Reconciled ice-sheet mass balance estimates determined during various epochs, inclusive region. Lastly, the spatial sampling of mass fluc- of all data present during the given dates. The period 1993 to 2003 was used in an earlier tuations at the APIS is at present inadequate, assessment (2). particularly considering that it provides a signifi- cant component of the overall AIS imbalance. 1992–2011 1992–2000 1993–2003 2000–2011 2005–2010 Region Improvements in the spatial and temporal density (Gt/year) (Gt/ year) (Gt/ year) (Gt /year) (Gt/year) of satellite observations of this region are needed. 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