The Greenland Ice Sheet has been a major contributor to global sea-level rise in recent decades1,2, and it is expected to continue to be so3. Although increases in glacier flow4,5,6 and surface melting7,8,9 have been driven by oceanic10,11,12 and atmospheric13,14 warming, the magnitude and trajectory of the ice sheet’s mass imbalance remain uncertain. Here we compare and combine 26 individual satellite measurements of changes in the ice sheet’s volume, flow and gravitational potential to produce a reconciled estimate of its mass balance. The ice sheet was close to a state of balance in the 1990s, but annual losses have risen since then, peaking at 345 ± 66 billion tonnes per year in 2011. In all, Greenland lost 3,902 ± 342 billion tonnes of ice between 1992 and 2018, causing the mean sea level to rise by 10.8 ± 0.9 millimetres. Using three regional climate models, we show that the reduced surface mass balance has driven 1,964 ± 565 billion tonnes (50.3 per cent) of the ice loss owing to increased meltwater runoff. The remaining 1,938 ± 541 billion tonnes (49.7 per cent) of ice loss was due to increased glacier dynamical imbalance, which rose from 46 ± 37 billion tonnes per year in the 1990s to 87 ± 25 billion tonnes per year since then. The total rate of ice loss slowed to 222 ± 30 billion tonnes per year between 2013 and 2017, on average, as atmospheric circulation favoured cooler conditions15 and ocean temperatures fell at the terminus of Jakobshavn Isbræ16. Cumulative ice losses from Greenland as a whole have been close to the rates predicted by the Intergovernmental Panel on Climate Change for their high-end climate warming scenario17, which forecast an additional 70 to 130 millimetres of global sea-level rise by 2100 compared with their central estimate.
Subscribe to Journal
Get full journal access for 1 year
only $3.90 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
The aggregated Greenland Ice Sheet mass balance data and estimated errors generated in this study are freely available at http://imbie.org and at the NERC Polar Data Centre, https://doi.org/10.5285/8D5FF221-A470-4CC1-B7C4-CBDF383554FC.
The code used to compute and aggregate rates of ice sheet mass change and their estimated errors are freely available at https://github.com/IMBIE.
Shepherd, A. et al. A reconciled estimate of ice-sheet mass balance. Science 338, 1183–1189 (2012).
WCRP Global Sea Level Budget Group. Global sea-level budget 1993–present. Earth Syst. Sci. Data 10, 1551–1590 (2018).
Pattyn, F. et al. The Greenland and Antarctic ice sheets under 1.5 °C global warming. Nat. Clim. Change 8, 1053–1061 (2018).
Moon, T., Joughin, I., Smith, B. & Howat, I. 21st-century evolution of Greenland outlet glacier velocities. Science 336, 576–578 (2012).
Enderlin, E. M. et al. An improved mass budget for the Greenland ice sheet. Geophys. Res. Lett. 41, 866–872 (2014).
Rignot, E. & Kanagaratnam, P. Changes in the velocity structure of the Greenland Ice Sheet. Science 311, 986–990 (2006).
van den Broeke, M. et al. Partitioning recent Greenland mass loss. Science 326, 984–986 (2009).
Trusel, L. D. et al. Nonlinear rise in Greenland runoff in response to post-industrial Arctic warming. Nature 564, 104–108 (2018).
Lucas-Picher, P. et al. Very high resolution regional climate model simulations over Greenland: identifying added value. J. Geophys. Res. D 117, 02108 (2012).
Holland, D. M., Thomas, R. H., de Young, B., Ribergaard, M. H. & Lyberth, B. Acceleration of Jakobshavn Isbræ triggered by warm subsurface ocean waters. Nat. Geosci. 1, 659–664 (2008).
Seale, A., Christoffersen, P., Mugford, R. I. & O’Leary, M. Ocean forcing of the Greenland Ice Sheet: calving fronts and patterns of retreat identified by automatic satellite monitoring of eastern outlet glaciers. J. Geophys. Res. Earth Surf. 116, F03013 (2011).
Straneo, F. & Heimbach, P. North Atlantic warming and the retreat of Greenland’s outlet glaciers. Nature 504, 36–43 (2013).
Hanna, E., Mernild, S. H., Cappelen, J. & Steffen, K. Recent warming in Greenland in a long-term instrumental (1881–2012) climatic context: I. Evaluation of surface air temperature records. Environ. Res. Lett. 7, 045404 (2012).
Fettweis, X. et al. Important role of the mid-tropospheric atmospheric circulation in the recent surface melt increase over the Greenland ice sheet. Cryosphere 7, 241–248 (2013).
Bevis, M. et al. Accelerating changes in ice mass within Greenland, and the ice sheet’s sensitivity to atmospheric forcing. Proc. Natl Acad. Sci. USA 116, 1934–1939 (2019).
Khazendar, A. et al. Interruption of two decades of Jakobshavn Isbrae acceleration and thinning as regional ocean cools. Nat. Geosci. 12, 277–283 (2019); correction 12, 493 (2019).
Church, J. A. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 1137–1216 (IPCC, Cambridge Univ. Press, 2013).
Morlighem, M. et al. BedMachine v3: complete bed topography and ocean bathymetry mapping of Greenland from multibeam echo sounding combined with mass conservation. Geophys. Res. Lett. 44, 11,051–11,061 (2017).
Joughin, I., Smith, B. E., Howat, I. M., Scambos, T. & Moon, T. Greenland flow variability from ice-sheet-wide velocity mapping. J. Glaciol. 56, 415–430 (2010).
Zwally, H. J., Giovinetto, M. B., Beckley, M. A. & Saba, J. L. Antarctic and Greenland Drainage Systems (GSFC Cryospheric Sciences Laboratory, 2012); http://icesat4.gsfc.nasa.gov/cryo_data/ant_grn_drainage_systems.php.
Fettweis, X. et al. Reconstructions of the 1900–2015 Greenland ice sheet surface mass balance using the regional climate MAR model. Cryosphere 11, 1015–1033 (2017).
Hofer, S., Tedstone, A. J., Fettweis, X. & Bamber, J. L. Decreasing cloud cover drives the recent mass loss on the Greenland Ice Sheet. Sci. Adv. 3, e1700584 (2017).
Leeson, A. A. et al. Supraglacial lakes on the Greenland ice sheet advance inland under warming climate. Nat. Clim. Change 5, 51–55 (2015).
Palmer, S., McMillan, M. & Morlighem, M. Subglacial lake drainage detected beneath the Greenland ice sheet. Nat. Commun. 6, 8408 (2015).
Nick, F. M. et al. The response of Petermann Glacier, Greenland, to large calving events, and its future stability in the context of atmospheric and oceanic warming. J. Glaciol. 58, 229–239 (2012).
Joughin, I. et al. Ice-front variation and tidewater behavior on Helheim and Kangerdlugssuaq Glaciers, Greenland. J. Geophys. Res. Earth Surf. 113, F01004 (2008).
Pritchard, H. D., Arthern, R. J., Vaughan, D. G. & Edwards, L. A. Extensive dynamic thinning on the margins of the Greenland and Antarctic ice sheets. Nature 461, 971–975 (2009).
McMillan, M. et al. A high-resolution record of Greenland mass balance. Geophys. Res. Lett. 43, 7002–7010 (2016).
Sandberg Sørensen, L. et al. 25 years of elevation changes of the Greenland Ice Sheet from ERS, Envisat, and CryoSat-2 radar altimetry. Earth Planet. Sci. Lett. 495, 234–241 (2018).
Velicogna, I. & Wahr, J. Greenland mass balance from GRACE. Geophys. Res. Lett. 32, L18505 (2005).
Luthcke, S. B. et al. Recent Greenland ice mass loss by drainage system from satellite gravity observations. Science 314, 1286–1289 (2006).
Zwally, H. J., Bindschadler, R. A., Brenner, A. C., Major, J. A. & Marsh, J. G. Growth of Greenland Ice Sheet: measurement. Science 246, 1587–1589 (1989).
Mouginot, J. et al. Forty-six years of Greenland Ice Sheet mass balance from 1972 to 2018. Proc. Natl Acad. Sci. USA 116, 9239–9244 (2019).
Lecavalier, B. S. et al. A model of Greenland ice sheet deglaciation constrained by observations of relative sea level and ice extent. Quat. Sci. Rev. 102, 54–84 (2014).
King, M. D. et al. Seasonal to decadal variability in ice discharge from the Greenland Ice Sheet. Cryosphere 12, 3813–3825 (2018).
Porter, D. F. et al. Identifying spatial variability in Greenland’s outlet glacier response to ocean heat. Front. Earth Sci. 6, 90 (2018).
Rignot, E. & Mouginot, J. Ice flow in Greenland for the International Polar Year 2008–2009. Geophys. Res. Lett. 39, L11501 (2012).
Sørensen, L. S. et al. Mass balance of the Greenland ice sheet (2003–2008) from ICESat data—the impact of interpolation, sampling and firn density. Cryosphere 5, 173–186 (2011).
Zwally, H. J. et al. Greenland ice sheet mass balance: distribution of increased mass loss with climate warming; 2003–07 versus 1992–2002. J. Glaciol. 57, 88–102 (2011).
Rosenau, R., Scheinert, M. & Dietrich, R. A processing system to monitor Greenland outlet glacier velocity variations at decadal and seasonal time scales utilizing the Landsat imagery. Remote Sens. Environ. 169, 1–19 (2015).
The IMBIE Team. Mass balance of the Antarctic Ice Sheet from 1992 to 2017. Nature 558, 219–222 (2018).
Khan, S. A. et al. Geodetic measurements reveal similarities between post–Last Glacial Maximum and present-day mass loss from the Greenland ice sheet. Sci. Adv. 2, e1600931 (2016).
Ettema, J. et al. Higher surface mass balance of the Greenland ice sheet revealed by high-resolution climate modeling. Geophys. Res. Lett. 36, L12501 (2009).
Bolch, T. et al. Mass loss of Greenland’s glaciers and ice caps 2003–2008 revealed from ICESat laser altimetry data. Geophys. Res. Lett. 40, 875–881 (2013).
Vernon, C. L. et al. Surface mass balance model intercomparison for the Greenland ice sheet. Cryosphere 7, 599–614 (2013).
Noël, B. et al. Modelling the climate and surface mass balance of polar ice sheets using RACMO2—Part 1: Greenland (1958–2016). Cryosphere 12, 811–831 (2018).
Howat, I. M., Joughin, I., Fahnestock, M., Smith, B. E. & Scambos, T. A. Synchronous retreat and acceleration of southeast Greenland outlet glaciers 2000–06: ice dynamics and coupling to climate. J. Glaciol. 54, 646–660 (2008).
Shepherd, A. & Nowicki, S. Improvements in ice-sheet sea-level projections. Nat. Clim. Change 7, 672–674 (2017).
Markus, T. et al. The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2): science requirements, concept, and implementation. Remote Sens. Environ. 190, 260–273 (2017).
Flechtner, F. et al. What can be expected from the GRACE-FO laser ranging interferometer for earth science applications? Surv. Geophys. 37, 453–470 (2016).
Peltier, W. R., Argus, D. F. & Drummond, R. Space geodesy constrains ice age terminal deglaciation: the global ICE-6G_C (VM5a) model. J. Geophys. Res. Solid Earth 120, 450–487 (2015).
Paulson, A., Zhong, S. & Wahr, J. Inference of mantle viscosity from GRACE and relative sea level data. Geophys. J. Int. 171, 497–508 (2007).
Peltier, W. R. Global glacial isostasy and the surface of the Ice-Age Earth: the ICE-5G (VM2) model and GRACE. Annu. Rev. Earth Planet. Sci. 32, 111–149 (2004).
Simpson, M. J. R., Milne, G. A., Huybrechts, P. & Long, A. J. Calibrating a glaciological model of the Greenland ice sheet from the Last Glacial Maximum to present-day using field observations of relative sea level and ice extent. Quat. Sci. Rev. 28, 1631–1657 (2009).
A, G., Wahr, J. & Zhong, S. Computations of the viscoelastic response of a 3-D compressible Earth to surface loading: an application to glacial isostatic adjustment in Antarctica and Canada. Geophys. J. Int. 192, 557–572 (2013).
Schrama, E. J. O., Wouters, B. & Rietbroek, R. A mascon approach to assess ice sheet and glacier mass balances and their uncertainties from GRACE data. J. Geophys. Res. Solid Earth 119, 6048–6066 (2014).
Klemann, V. & Martinec, Z. Contribution of glacial-isostatic adjustment to the geocenter motion. Tectonophysics 511, 99–108 (2011).
Swenson, S., Chambers, D. & Wahr, J. Estimating geocenter variations from a combination of GRACE and ocean model output. J. Geophys. Res. Solid Earth 113, B08410 (2008).
Wouters, B., Bamber, J. L., van den Broeke, M. R., Lenaerts, J. T. M. & Sasgen, I. Limits in detecting acceleration of ice sheet mass loss due to climate variability. Nat. Geosci. 6, 613–616 (2013).
Bonin, J. & Chambers, D. Uncertainty estimates of a GRACE inversion modelling technique over Greenland using a simulation. Geophys. J. Int. 194, 212–229 (2013).
Blazquez, A. et al. Exploring the uncertainty in GRACE estimates of the mass redistributions at the Earth surface: implications for the global water and sea level budgets. Geophys. J. Int. 215, 415–430 (2018).
Forsberg, R., Sørensen, L. & Simonsen, S. Greenland and Antarctica Ice Sheet Mass Changes and Effects on Global Sea Level. Surv. Geophys. 38, 89–104 (2017).
Groh, A. & Horwath, M. The method of tailored sensitivity kernels for GRACE mass change estimates. Geophys. Res. Abstr. 18, 12065 (2016).
Harig, C. & Simons, F. J. Mapping Greenland’s mass loss in space and time. Proc. Natl Acad. Sci. USA 109, 19934–19937 (2012).
Luthcke, S. B. et al. Antarctica, Greenland and Gulf of Alaska land-ice evolution from an iterated GRACE global mascon solution. J. Glaciol. 59, 613–631 (2013).
Andrews, S. B., Moore, P. & King, M. A. Mass change from GRACE: a simulated comparison of Level-1B analysis techniques. Geophys. J. Int. 200, 503–518 (2015).
Save, H., Bettadpur, S. & Tapley, B. D. High-resolution CSR GRACE RL05 mascons. J. Geophys. Res. Solid Earth 121, 7547–7569 (2016).
Seo, K.-W. et al. Surface mass balance contributions to acceleration of Antarctic ice mass loss during 2003–2013. J. Geophys. Res. Solid Earth 120, 3617–3627 (2015).
Velicogna, I., Sutterley, T. C. & van den Broeke, M. R. Regional acceleration in ice mass loss from Greenland and Antarctica using GRACE time-variable gravity data. Geophys. Res. Lett. 41, 8130–8137 (2014).
Vishwakarma, B. D., Horwath, M., Devaraju, B., Groh, A. & Sneeuw, N. A data-driven approach for repairing the hydrological catchment signal damage due to filtering of GRACE products. Wat. Resour. Res. 53, 9824–9844 (2017).
Wiese, D. N., Landerer, F. W. & Watkins, M. M. Quantifying and reducing leakage errors in the JPL RL05M GRACE mascon solution. Wat. Resour. Res. 52, 7490–7502 (2016).
Ivins, E. R. & James, T. S. Antarctic glacial isostatic adjustment: a new assessment. Antarct. Sci. 17, 541–553 (2005).
Ivins, E. R. et al. Antarctic contribution to sea level rise observed by GRACE with improved GIA correction. J. Geophys. Res. Solid Earth 118, 3126–3141 (2013).
Rodell, M. et al. The Global Land Data Assimilation System. Bull. Am. Meteorol. Soc. 85, 381–394 (2004).
Döll, P., Kaspar, F. & Lehner, B. A global hydrological model for deriving water availability indicators: model tuning and validation. J. Hydrol. 270, 105–134 (2003).
Cheng, M., Tapley, B. D. & Ries, J. C. Deceleration in the Earth’s oblateness. J. Geophys. Res. Solid Earth 118, 740–747 (2013).
Balmaseda, M. A., Mogensen, K. & Weaver, A. T. Evaluation of the ECMWF ocean reanalysis system ORAS4. Q. J. R. Meteorol. Soc. 139, 1132–1161 (2013).
Pujol, M.-I. et al. DUACS DT2014: the new multi-mission altimeter data set reprocessed over 20 years. Ocean Sci. 12, 1067–1090 (2016).
Menemenlis, D. et al. ECCO2: High resolution global ocean and sea ice data synthesis. In AGU Fall Meeting Abstracts 2008 OS31C-1292 (AGU, 2008).
Dobslaw, H. et al. Simulating high-frequency atmosphere-ocean mass variability for dealiasing of satellite gravity observations: AOD1B RL05. J. Geophys. Res. Oceans 118, 3704–3711 (2013).
Carrère, L. & Lyard, F. Modeling the barotropic response of the global ocean to atmospheric wind and pressure forcing – comparisons with observations. Geophys. Res. Lett. 30, 1275 (2003).
Csatho, B. M. et al. Laser altimetry reveals complex pattern of Greenland Ice Sheet dynamics. Proc. Natl Acad. Sci. USA 111, 18478–18483 (2014).
Nilsson, J., Gardner, A., Sandberg Sørensen, L. & Forsberg, R. Improved retrieval of land ice topography from CryoSat-2 data and its impact for volume-change estimation of the Greenland Ice Sheet. Cryosphere 10, 2953–2969 (2016).
Gourmelen, N. et al. CryoSat-2 swath interferometric altimetry for mapping ice elevation and elevation change. Adv. Space Res. 62, 1226–1242 (2018).
Gunter, B. C. et al. Empirical estimation of present-day Antarctic glacial isostatic adjustment and ice mass change. Cryosphere 8, 743–760 (2014).
Helm, V., Humbert, A. & Miller, H. Elevation and elevation change of Greenland and Antarctica derived from CryoSat-2. Cryosphere 8, 1539–1559 (2014).
Kjeldsen, K. K. et al. Improved ice loss estimate of the northwestern Greenland ice sheet. J. Geophys. Res. Solid Earth 118, 698–708 (2013).
Felikson, D. et al. Comparison of elevation change detection methods from ICESat altimetry over the Greenland Ice Sheet. IEEE Trans. Geosci. Remote Sens. 55, 5494–5505 (2017).
Andersen, M. L. et al. Basin-scale partitioning of Greenland ice sheet mass balance components (2007–2011). Earth Planet. Sci. Lett. 409, 89–95 (2015).
Colgan, W. et al. Greenland ice sheet mass balance assessed by PROMICE (1995–2015). Geol. Surv. Denmark Greenl. Bull. 43, e2019430201 (2019).
van Wessem, J. M. et al. Updated cloud physics in a regional atmospheric climate model improves the modelled surface energy balance of Antarctica. Cryosphere 8, 125–135 (2014).
Fettweis, X. et al. Estimating the Greenland ice sheet surface mass balance contribution to future sea level rise using the regional atmospheric climate model MAR. Cryosphere 7, 469–489 (2013).
Wahr, J., Wingham, D. & Bentley, C. A method of combining ICESat and GRACE satellite data to constrain Antarctic mass balance. J. Geophys. Res. Solid Earth 105, 16279–16294 (2000).
Lambeck, K., Rouby, H., Purcell, A., Sun, Y. & Sambridge, M. Closing the sea level budget at the Last Glacial Maximum. Proc. Natl Acad. Sci. USA 111, 15861–15862 (2014).
Caron, L., Métivier, L., Greff-Lefftz, M., Fleitout, L. & Rouby, H. Inverting Glacial Isostatic Adjustment signal using Bayesian framework and two linearly relaxing rheologies. Geophys. J. Int. 209, 1126–1147 (2017).
Sun, Y., Riva, R. & Ditmar, P. Optimizing estimates of annual variations and trends in geocenter motion and J2 from a combination of GRACE data and geophysical models. J. Geophys. Res. Solid Earth 121, 8352–8370 (2016).
Nagler, T., Rott, H., Hetzenecker, M., Wuite, J. & Potin, P. The Sentinel-1 Mission: New Opportunities for Ice Sheet Observations. Remote Sens. 7, 9371–9389 (2015).
Mouginot, J., Rignot, E., Scheuchl, B. & Millan, R. Comprehensive annual ice sheet velocity mapping using Landsat-8, Sentinel-1, and RADARSAT-2 data. Remote Sens. 9, 364 (2017).
Joughin, I., Smith, B. E. & Howat, I. Greenland Ice Mapping Project: ice flow velocity variation at sub-monthly to decadal timescales. Cryosphere 12, 2211–2227 (2018).
Lemos, A. et al. Ice velocity of Jakobshavn Isbræ, Petermann Glacier, Nioghalvfjerdsfjorden, and Zachariæ Isstrøm, 2015–2017, from Sentinel 1-a/b SAR imagery. Cryosphere 12, 2087–2097 (2018).
Joughin, I. et al. Continued evolution of Jakobshavn Isbrae following its rapid speedup. J. Geophys. Res. Earth Surf. 113, F04006 (2008).
Joughin, I., Abdalati, W. & Fahnestock, M. Large fluctuations in speed on Greenland’s Jakobshavn Isbræ glacier. Nature 432, 608–610 (2004).
Gogineni, S. et al. Coherent radar ice thickness measurements over the Greenland ice sheet. J. Geophys. Res. D Atmospheres 106, 33761–33772 (2001).
Rignot, E. et al. Recent Antarctic ice mass loss from radar interferometry and regional climate modelling. Nat. Geosci. 1, 106–110 (2008).
Shepherd, A. et al. Trends in Antarctic Ice Sheet elevation and mass. Geophys. Res. Lett. 46, 8174–8183 (2019).
Martinec, Z. & Hagedoorn, J. The rotational feedback on linear-momentum balance in glacial isostatic adjustment. Geophys. J. Int. 199, 1823–1846 (2014).
Fretwell, P. et al. Bedmap2: improved ice bed, surface and thickness datasets for Antarctica. Cryosphere 7, 375–393 (2013).
Rignot, E., Mouginot, J. & Scheuchl, B. Ice flow of the Antarctic Ice Sheet. Science 333, 1427–1430 (2011).
Rignot, E., Mouginot, J. & Scheuchl, B. Antarctic grounding line mapping from differential satellite radar interferometry. Geophys. Res. Lett. 38, L10504 (2011).
Langen, P. L., Fausto, R. S., Vandecrux, B., Mottram, R. H. & Box, J. E. Liquid water flow and retention on the Greenland Ice Sheet in the regional climate model HIRHAM5: local and large-scale impacts. Front. Earth Sci. 4, 110 (2017).
Martinec, Z. Spectral–finite element approach to three-dimensional viscoelastic relaxation in a spherical earth. Geophys. J. Int. 142, 117–141 (2000).
Fleming, K. & Lambeck, K. Constraints on the Greenland Ice Sheet since the Last Glacial Maximum from sea-level observations and glacial-rebound models. Quat. Sci. Rev. 23, 1053–1077 (2004).
King, M. A., Whitehouse, P. L. & van der Wal, W. Incomplete separability of Antarctic plate rotation from glacial isostatic adjustment deformation within geodetic observations. Geophys. J. Int. 204, 324–330 (2016).
Spada, G., Melini, D. & Colleoni, F. SELEN v2.9.12 (Computational Infrastructure for Geodynamics, 2018); https://geodynamics.org/cig/software/selen.
Noël, B. et al. Evaluation of the updated regional climate model RACMO2.3: summer snowfall impact on the Greenland Ice Sheet. Cryosphere 9, 1831–1844 (2015).
Noël, B. et al. A daily, 1 km resolution data set of downscaled Greenland ice sheet surface mass balance (1958–2015). Cryosphere 10, 2361–2377 (2016).
Gelaro, R. et al. The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). J. Clim. 30, 5419–5454 (2017).
Wilton, D. J. et al. High resolution (1 km) positive degree-day modelling of Greenland ice sheet surface mass balance, 1870–2012 using reanalysis data. J. Glaciol. 63, 176–193 (2017).
Mernild, S. H., Liston, G. E., Hiemstra, C. A. & Christensen, J. H. Greenland Ice Sheet surface mass-balance modeling in a 131-yr perspective, 1950–2080. J. Hydrometeorol. 11, 3–25 (2010).
This work is an outcome of the IMBIE supported by the ESA Climate Change Initiative and the NASA Cryosphere Program. A.S. was additionally supported by a Royal Society Wolfson Research Merit Award and the UK Natural Environment Research Council Centre for Polar Observation and Modelling.
The authors declare no competing interests.
Peer review information Nature thanks Christina Hulbe, Andreas Kääb and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data figures and tables
a, Participant datasets used in this study and their main contributors. b, The number of data available in each calendar year. The interval 2003–2010 includes almost all datasets and is selected as the overlap period. Further details of the satellite observations used in this study are provided in Supplementary Table 1. Refs. 28, 33, 38, 56, 59,60,61,62,63,64,65,66,67,68,69,70,71, 82,83,84,85,86,87,88,89,90.
a, b, Bedrock uplift rates in Greenland averaged over the GIA model solutions used in this study (a) and their standard deviation (b). Further details of the GIA models used in this study are provided in Extended Data Table 1. High rates of uplift and subsidence associated with the former Laurentide Ice Sheet are apparent to the southwest of Greenland.
a–c, Individual rates of Greenland Ice Sheet mass balance used in this study as determined from satellite altimetry (a), gravimetry (b) and the input–output method (c). The grey shading shows the estimated 1σ (dark), 2σ (mid-) and 3σ (light) uncertainty relative to the ensemble average. Refs. 28,33,38,56,59,60,61,62,63,64,65,66,67,68,69,70,71,82,83,84,85,86,87,88,89,90.
Rate of Greenland Ice Sheet mass balance as derived from the three techniques: satellite radar and laser altimetry (red), input–output method (blue) and gravimetry (green). Their arithmetic mean is shown in grey. The estimated uncertainty is also shown (shaded envelopes) and is computed as the root mean square of the component time-series errors.
The cumulative surface mass change determined from an average (mean) of the RACMO2.3p246, MARv3.621 and HIRHAM9 regional climate models relative to their 1980–1990 means (see Methods). The estimated uncertainty of the mean change is also shown (shaded area), computed as the average of the uncertainties from each of the three models. RACMO2.3p2 uncertainties are based on a comparison to in situ observations33. MARv3.6 uncertainties are evaluated from the variability due to forcing from climate reanalyses21. HIRHAM uncertainties are estimated on the basis of comparisons to in situ accumulation and ablation data110. Cumulative uncertainties are computed as the root sum square of annual errors, on the assumption that these errors are not correlated over time17.
This file contains: 1.1 Data sets and methods employed by participants of the gravimetry experiment group; 1.2 Data sets and methods employed by participants of the radar and laser altimetry experiment group; 1.3 Data sets and methods employed by participants of the mass budget experiment group; and Supplementary References.
About this article
Cite this article
The IMBIE Team. Mass balance of the Greenland Ice Sheet from 1992 to 2018. Nature 579, 233–239 (2020). https://doi.org/10.1038/s41586-019-1855-2
Nature Climate Change (2021)
Scientific Reports (2021)
Journal of Geodesy (2021)
Science China Earth Sciences (2021)