Government policies currently commit us to surface warming of three to four degrees Celsius above pre-industrial levels by 2100, which will lead to enhanced ice-sheet melt. Ice-sheet discharge was not explicitly included in Coupled Model Intercomparison Project phase 5, so effects on climate from this melt are not currently captured in the simulations most commonly used to inform governmental policy. Here we show, using simulations of the Greenland and Antarctic ice sheets constrained by satellite-based measurements of recent changes in ice mass, that increasing meltwater from Greenland will lead to substantial slowing of the Atlantic overturning circulation, and that meltwater from Antarctica will trap warm water below the sea surface, creating a positive feedback that increases Antarctic ice loss. In our simulations, future ice-sheet melt enhances global temperature variability and contributes up to 25 centimetres to sea level by 2100. However, uncertainties in the way in which future changes in ice dynamics are modelled remain, underlining the need for continued observations and comprehensive multi-model assessments.
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CMIP5 data were downloaded from http://climexp.knmi.nl/. Antarctic bedrock topography and ice thickness data are from the BEDMAP2 compilation, available at https://secure.antarctica.ac.uk/data/bedmap2/. Greenland topography and ice thickness data are from BedMachine v3, available at https://nsidc.org/data/idbmg4. Greenland mass balance and geothermal heat flux data are available from the seaRISE website: http://websrv.cs.umt.edu/isis/index.php/Data. Information on Antarctic surface mass balance data are available at http://www.projects.science.uu.nl/iceclimate/models/antarctica.php#racmo23. Antarctic geothermal heat flux data are available at https://doi.pangaea.de/10.1594/PANGAEA.882503. Drainage basin outlines as shown in Fig. 3 are based on ICESat data96. Antarctic grounding lines and calving lines shown in Fig. 3a are from the MODIS-MOA 2009 dataset97,98. The datasets generated and analysed during this study are also available from the corresponding author on reasonable request.
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The IMBIE team. Mass balance of the Antarctic Ice Sheet from 1992 to 2017. Nature 558, 219–222 (2018).
Forsberg, R., Sørensen, L. & Simonsen, S. Greenland and Antarctic Ice Sheet mass changes and effects on global sea level. Surv. Geophys. 38, 89–104 (2017).
Chen, X. et al. The increasing rate of global mean sea-level rise during 1993–2014. Nat. Clim. Chang. 7, 492–495 (2017).
Huss, M. & Hock, R. A new model for global glacier change and sea-level rise. Front. Earth Sci. 3, 54 (2015).
Bamber, J. L., Westaway, R. M., Marzeion, B. & Wouters, B. The land ice contribution to sea level during the satellite era. Environ. Res. Lett. 13, 063008 (2018).
Dieng, H. B., Cazenave, A., Meyssignac, B. & Ablain, M. New estimate of the current rate of sea level rise from a sea level budget approach. Geophys. Res. Lett. 44, 3744–3751 (2017).
Caesar, L., Rahmstorf, S., Robinson, A., Feulner, G. & Saba, V. Observed fingerprint of a weakening Atlantic Ocean overturning circulation. Nature 556, 191–196 (2018).
Thornalley, D. J. R. et al. Anomalously weak Labrador Sea convection and Atlantic overturning during the past 150 years. Nature 556, 227–230 (2018).
Raftery, A. E., Zimmer, A., Frierson, D. M. W., Startz, R. & Liu, P. Less than 2 °C warming by 2100 unlikely. Nat. Clim. Chang. 7, 637–641 (2017).
Lenton, T. M. et al. Tipping elements in the Earth’s climate system. Proc. Natl Acad. Sci. USA 105, 1786–1793 (2008).
Rignot, E., Mouginot, J., Morlighem, M., Seroussi, H. & Scheuchl, B. Widespread, rapid grounding line retreat of Pine Island, Thwaites, Smith, and Kohler glaciers, West Antarctica, from 1992 to 2011. Geophys. Res. Lett. 41, 3502–3509 (2014).
Joughin, I., Smith, B. E. & Medley, B. Marine ice sheet collapse potentially under way for the Thwaites Glacier basin, West Antarctica. Science 344, 735–738 (2014).
Vitousek, S. et al. Doubling of coastal flooding frequency within decades due to sea-level rise. Sci. Rep. 7, 1399 (2017).
King, A. D. & Harrington, L. J. The inequality of climate change from 1.5 to 2 °C of global warming. Geophys. Res. Lett. 45, 5030–5033 (2018).
Kopp, R. E. et al. Evolving understanding of Antarctic ice-sheet physics and ambiguity in probabilistic sea-level projections. Earths Futur. 5, 1217–1233 (2017).
Jackson, L. P., Grinsted, A. & Jevrejeva, S. 21st century sea-level rise in line with the Paris Accord. Earths Futur. 6, 213–229 (2018).
Ritz, C. et al. Potential sea-level rise from Antarctic ice-sheet instability constrained by observations. Nature 528, 115–118 (2015).
Golledge, N. et al. The multi-millennial Antarctic commitment to future sea-level rise. Nature 526, 421–425 (2015).
Vizcaino, M. et al. Coupled simulations of Greenland Ice Sheet and climate change up to A.D. 2300. Geophys. Res. Lett. 42, 3927–3935 (2015).
DeConto, R. & Pollard, D. Contribution of Antarctica to past and future sea-level rise. Nature 531, 591–597 (2016).
Weaver, A. J. et al. Stability of the Atlantic meridional overturning circulation: a model intercomparison. Geophys. Res. Lett. 39, L20709 (2012).
Collins, M. et al. in Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (eds Stocker, T. et al.) 1029–1136 (Cambridge Univ. Press, Cambridge, 2013).
Bintanja, R., van Oldenborgh, G. J. & Katsman, C. A. The effect of increased fresh water from Antarctic ice shelves on future trends in Antarctic sea ice. Ann. Glaciol. 56, 120–126 (2015).
Bueler, E. & Brown, J. Shallow shelf approximation as a “sliding law” in a thermomechanically coupled ice sheet model. J. Geophys. Res. 114, F03008 (2009).
Bernales, J., Rogozhina, I. & Thomas, M. Melting and freezing under Antarctic ice shelves from a combination of ice-sheet modelling and observations. J. Glaciol. 63, 731–744 (2017).
Golledge, N. et al. Antarctic contribution to meltwater pulse 1A from reduced Southern Ocean overturning. Nat. Commun. 5, 5107 (2014).
Bakker, P., Clark, P. U., Golledge, N. R., Schmittner, A. & Weber, M. E. Centennial-scale Holocene climate variations amplified by Antarctic Ice Sheet discharge. Nature 541, 72–76 (2017).
Menviel, L., Timmermann, A., Timm, O. E. & Mouchet, A. Climate and biogeochemical response to a rapid melting of the West Antarctic Ice Sheet during interglacials and implications for future climate. Paleoceanography 25, PA4231 (2010).
Weber, M. et al. Millennial-scale variability in Antarctic ice-sheet discharge during the last deglaciation. Nature 510, 134–138 (2014).
Bronselaer, B. et al. Change in future climate due to Antarctic meltwater. Nature 564, 53–58 (2018).
Frölicher, T. L., Fischer, E. M. & Gruber, N. Marine heatwaves under global warming. Nature 560, 360–364 (2018).
Ruthrof, K. X. et al. Subcontinental heat wave triggers terrestrial and marine, multi-taxa responses. Sci. Rep. 8, 13094 (2018).
Hutchings, J. K. & Perovich, D. K. Preconditioning of the 2007 sea-ice melt in the eastern Beaufort Sea, Arctic Ocean. Ann. Glaciol. 56, 94–98 (2015).
Rahmstorf, S. Bifurcations of the Atlantic thermohaline circulation in response to changes in the hydrological cycle. Nature 378, 145–149 (1995).
Stommel, H. Thermohaline convection with two stable regimes of flow. Tellus 13, 224–230 (1961).
Bakker, P. et al. Fate of the Atlantic Meridional Overturning Circulation: strong decline under continued warming and Greenland melting. Geophys. Res. Lett. 43, 12252–12260 (2016).
Liu, W., Xie, S.-P., Liu, Z. & Zhu, J. Overlooked possibility of a collapsed Atlantic Meridional Overturning Circulation in warming climate. Sci. Adv. 3, e1601666 (2017).
Rind, D. et al. Multi-century instability of the Atlantic Meridional Circulation in rapid warming simulations with GISS ModelE2. J. Geophys. Res. 123, 6331–6355 (2018).
Edwards, T. L. et al. Revisiting Antarctic ice loss due to marine ice-cliff instability. Nature 566, https://doi.org/10.1038/s41586-019-0901-4 (2019).
Noël, B. et al. A tipping point in refreezing accelerates mass loss of Greenland’s glaciers and ice caps. Nat. Commun. 8, 14730 (2017).
Machguth, H. et al. Greenland meltwater storage in firn limited by near-surface ice formation. Nat. Clim. Chang. 6, 390–393 (2016).
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).
Shannon, S. R. et al. Enhanced basal lubrication and the contribution of the Greenland ice sheet to future sea-level rise. Proc. Natl Acad. Sci. USA 110, 14156–14161 (2013).
Fürst, J. J., Goelzer, H. & Huybrechts, P. Ice-dynamic projections of the Greenland ice sheet in response to atmospheric and oceanic warming. Cryosphere 9, 1039–1062 (2015).
Seroussi, H. et al. Continued retreat of Thwaites Glacier, West Antarctica, controlled by bed topography and ocean circulation. Geophys. Res. Lett. 44, 6191–6199 (2017).
Medley, B. et al. Temperature and snowfall in western Queen Maud Land increasing faster than climate model projections. Geophys. Res. Lett. 45, 1472–1480 (2018).
Phillips, H. A. Surface meltstreams on the Amery ice shelf, East Antarctica. Ann. Glaciol. 27, 177–181 (1998).
Bevan, S. L. et al. Centuries of intense surface melt on Larsen C ice shelf. Cryosphere 11, 2743–2753 (2017).
Trusel, L. D. et al. Divergent trajectories of Antarctic surface melt under two twenty-first-century climate scenarios. Nat. Geosci. 8, 927–932 (2015).
Bell, R. E., Banwell, A., Trusel, L. & Kingslake, J. Antarctic surface hydrology and impacts on ice sheet mass balance. Nat. Clim. Chang. 8, 1044–1052 (2018).
Winkelmann, R. et al. The Potsdam Parallel Ice Sheet Model (PISM-PIK) – part 1: model description. Cryosphere 5, 715–726 (2011).
Aschwanden, A., Bueler, E., Khroulev, C. & Blatter, H. An enthalpy formulation for glaciers and ice sheets. J. Glaciol. 58, 441–457 (2012).
Feldmann, J., Albrecht, T., Khroulev, C., Pattyn, F. & Levermann, A. Resolution-dependent performance of grounding line motion in a shallow model compared to a full-Stokes model according to the MISMIP3d intercomparison. J. Glaciol. 60, 353–360 (2014).
Golledge, N. R. et al. Antarctic climate and ice sheet configuration during a peak-warmth early Pliocene interglacial. Clim. Past 13, 959–975 (2017).
Seroussi, H. & Morlighem, M. Representation of basal melting at the grounding line in ice flow models. Cryosphere 12, 3085–3096 (2018).
Milillo, P. et al. On the short-term grounding zone dynamics of Pine Island Glacier, West Antarctica, observed with COSMO-SkyMed interferometric data. Geophys. Res. Lett. 44, 10436–10444 (2017).
van den Broeke, M., Bus, C., Ettema, J. & Smeets, P. Temperature thresholds for degree-day modelling of Greenland ice sheet melt rates. Geophys. Res. Lett. 37, L18501 (2010).
Hellmer, H. & Olbers, D. A two-dimensional model for the thermohaline circulation under an ice shelf. Antarct. Sci. 1, 325–336 (1989).
Rignot, E. & Jacobs, S. S. Rapid bottom melting widespread near Antarctic Ice Sheet grounding lines. Science 296, 2020–2023 (2002).
Hellmer, H., Kauker, F., Timmermann, R., Determann, J. & Rae, J. Twenty-first-century warming of a large Antarctic ice-shelf cavity by a redirected coastal current. Nature 485, 225–228 (2012).
Levermann, A. et al. Kinematic first-order calving law implies potential for abrupt ice-shelf retreat. Cryosphere 6, 273–286 (2012).
Fretwell, P. et al. Bedmap2: improved ice bed, surface and thickness datasets for Antarctica. Cryosphere 7, 375–393 (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, 11051–11061 (2017).
Van Wessem, J. et al. Improved representation of East Antarctic surface mass balance in a regional atmospheric climate model. J. Glaciol. 60, 761–770 (2014).
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).
Martos, Y. M. et al. Heat flux distribution of Antarctica unveiled. Geophys. Res. Lett. 44, 11417–11426 (2017).
Shapiro, N. & Ritzwoller, M. Inferring surface heat flux distributions guided by a global seismic model: particular application to Antarctica. Earth Planet. Sci. Lett. 223, 213–224 (2004).
Sallée, J.-B. et al. Assessment of Southern Ocean water mass circulation and characteristics in CMIP5 models: historical bias and forcing response. J. Geophys. Res. 118, 1830–1844 (2013).
Turner, J., Bracegirdle, T. J., Phillips, T., Marshall, G. J. & Hosking, J. S. An initial assessment of Antarctic sea ice extent in the CMIP5 models. J. Clim. 26, 1473–1484 (2013).
Bracegirdle, T. J. et al. Assessment of surface winds over the Atlantic, Indian, and Pacific Ocean sectors of the Southern Ocean in CMIP5 models: historical bias, forcing response, and state dependence. J. Geophys. Res. 118, 547–562 (2013).
Naughten, K. A. et al. Future projections of Antarctic ice shelf melting based on CMIP5 scenarios. J. Clim. 31, 5243–5261 (2018).
Goosse, H. et al. Description of the Earth system model of intermediate complexity LOVECLIM version 1.2. Geosci. Model Dev. 3, 603–633 (2010).
Gent, P. R. & McWilliams, J. C. Isopycnal mixing in ocean circulation models. J. Phys. Oceanogr. 20, 150–155 (1990).
Menviel, L., Timmermann, A., Timm, O. E. & Mouchet, A. Deconstructing the Last Glacial termination: the role of millennial and orbital-scale forcings. Quat. Sci. Rev. 30, 1155–1172 (2011).
Abram, N. J. et al. Early onset of industrial-era warming across the oceans and continents. Nature 536, 411–418 (2016).
Menviel, L. et al. Southern Hemisphere westerlies as a driver of the early deglacial atmospheric CO2 rise. Nat. Commun. 9, 2503 (2018).
Randall, D. A. et al. in Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (eds Solomon, S. et al.) 589–662 (Cambridge Univ. Press, Cambridge, 2007).
Gomez, N., Mitrovica, J. X., Huybers, P. & Clark, P. U. Sea level as a stabilizing factor for marine-ice-sheet grounding lines. Nat. Geosci. 3, 850–853 (2010).
Dziewonski, A. M. & Anderson, D. L. Preliminary reference Earth model. Phys. Earth Planet. Inter. 25, 297–356 (1981).
Lambeck, K., Smither, C. & Ekman, M. Tests of glacial rebound models for Fennoscandinavia based on instrumented sea- and lake-level records. Geophys. J. Int. 135, 375–387 (1998).
Mitrovica, J. X. & Forte, A. M. A new inference of mantle viscosity based upon joint inversion of convection and glacial isostatic adjustment data. Earth Planet. Sci. Lett. 225, 177–189 (2004).
Lambeck, K., Rouby, H., Purcell, A., Sun, Y. & Sambridge, M. Sea level and global ice volumes from the Last Glacial Maximum to the Holocene. Proc. Natl Acad. Sci. USA 111, 15296–15303 (2014).
Stuhne, G. & Peltier, W. Reconciling the ICE-6G_C reconstruction of glacial chronology with ice sheet dynamics: the cases of Greenland and Antarctica. J. Geophys. Res. 120, 1841–1865 (2015).
Aschwanden, A., Fahnestock, M. A. & Truffer, M. Complex Greenland outlet glacier flow captured. Nat. Commun. 7, 10524 (2016).
Pauling, A. G., Bitz, C. M., Smith, I. J. & Langhorne, P. J. The response of the Southern Ocean and Antarctic sea ice to freshwater from ice shelves in an Earth system model. J. Clim. 29, 1655–1672 (2016).
Merino, N. et al. Impact of increasing Antarctic glacial freshwater release on regional sea-ice cover in the Southern Ocean. Ocean Model. 121, 76–89 (2018).
Dong, S., Sprintall, J., Gille, S. T. & Talley, L. Southern Ocean mixed-layer depth from Argo float profiles. J. Geophys. Res. 113, C06013 (2008).
Dutrieux, P. et al. Strong sensitivity of Pine Island ice-shelf melting to climatic variability. Science 343, 174–178 (2014).
Webber, B. G. et al. Mechanisms driving variability in the ocean forcing of Pine Island Glacier. Nat. Commun. 8, 14507 (2017).
Thompson, A. F., Heywood, K. J., Schmidtko, S. & Stewart, A. L. Eddy transport as a key component of the Antarctic overturning circulation. Nat. Geosci. 7, 879–884 (2014).
Stewart, A. L. & Thompson, A. F. Eddy-mediated transport of warm Circumpolar Deep Water across the Antarctic Shelf Break. Geophys. Res. Lett. 42, 432–440 (2015).
Naughten, K. A. et al. Intercomparison of Antarctic ice-shelf, ocean, and sea-ice interactions simulated by MetROMS-iceshelf and FESOM 1.4. Geosci. Model Dev. 11, 1257–1292 (2018).
Wessel, P., Smith, W. H., Scharroo, R., Luis, J. & Wobbe, F. Generic mapping tools: improved version released. Eos 94, 409–410 (2013).
Crameri, F. Geodynamic diagnostics, scientific visualisation and StagLab 3.0. Geosci. Model Dev. 11, 2541–2562 (2018).
Kovesi, P. Good colour maps: how to design them. Preprint at https://arxiv.org/abs/1509.03700 (2015).
Zwally, H. J., Giovinetto, M. B., Beckley, M. A. & Saba, J. L. Antarctic and Greenland Drainage Systems. GSFC Cryospheric Sciences Laboratory http://icesat4.gsfc.nasa.gov/cryo_data/ant_grn_drainage_systems.php (2012).
Scambos, T. A., Haran, T. M., Fahnestock, M. A., Painter, T. H. & Bohlander, J. Modis-based Mosaic of Antarctica (MOA) data sets: continent-wide surface morphology and snow grain size. Remote Sens. Environ. 111, 242–257 (2007).
Haran, T., Bohlander, J., Scambos, T., Painter, T., and Fahnestock, M. MODIS Mosaic of Antarctica 2008–2009 (MOA2009) Image Map. National Snow and Ice Data Center https://doi.org/10.7265/N5KP8037 (2014).
Rignot, E., Jacobs, S., Mouginot, J. & Scheuchl, B. Ice-shelf melting around Antarctica. Science 341, 266–270 (2013).
Depoorter, M. A. et al. Calving fluxes and basal melt rates of Antarctic ice shelves. Nature 502, 89–92 (2013).
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).
Rignot, E., Mouginot, J. & Scheuchl, B. Ice flow of the Antarctic Ice Sheet. Science 333, 1427–1430 (2011).
Rignot, E. et al. Recent Antarctic ice mass loss from radar interferometry and regional climate modelling. Nat. Geosci. 1, 106–110 (2008).
King, M. A. et al. Lower satellite-gravimetry estimates of Antarctic sea-level contribution. Nature 491, 586–589 (2012).
Helm, V., Humbert, A. & Miller, H. Elevation and elevation change of Greenland and Antarctica derived from CryoSat-2. Cryosphere 8, 1539–1559 (2014).
Martín-Español, A. et al. Spatial and temporal Antarctic Ice Sheet mass trends, glacio-isostatic adjustment, and surface processes from a joint inversion of satellite altimeter, gravity, and GPS data. J. Geophys. Res. 121, 182–200 (2016).
Gardner, A. S. et al. Increased West Antarctic and unchanged East Antarctic ice discharge over the last 7 years. Cryosphere 12, 521–547 (2018).
McMillan, M. et al. Increased ice losses from Antarctica detected by CryoSat-2. Geophys. Res. Lett. 41, 3899–3905 (2014).
Velicogna, I. & Wahr, J. Time-variable gravity observations of ice sheet mass balance: Precision and limitations of the GRACE satellite data. Geophys. Res. Lett. 40, 3055–3063 (2013).
Lenaerts, J., van den Broeke, M., van de Berg, W., van Meijgaard, E. & Munneke, P. A new, high-resolution surface mass balance map of Antarctica (1979–2010) based on regional atmospheric climate modeling. Geophys. Res. Lett. 39, L04501 (2012).
Turner, J., Connolley, W. M., Leonard, S., Marshall, G. J. & Vaughan, D. G. Spatial and temporal variability of net snow accumulation over the Antarctic from ECMWF re-analysis project data. Int. J. Climatol. 19, 697–724 (1999).
van de Berg, W. J., van den Broeke, M. R., Reijmer, C. H. & van Meijgaard, E. Reassessment of the Antarctic surface mass balance using calibrated output of a regional atmospheric climate model. J. Geophys. Res. 111, D11104 (2006).
Liu, Y. et al. Ocean-driven thinning enhances iceberg calving and retreat of Antarctic ice shelves. Proc. Natl Acad. Sci. USA 112, 3263–3268 (2015).
Rignot, E., Box, J. E., Burgess, E. & Hanna, E. Mass balance of the Greenland ice sheet from 1958 to 2007. Geophys. Res. Lett. 35, L20502 (2008).
Shepherd, A. et al. A reconciled estimate of ice-sheet mass balance. Science 338, 1183–1189 (2012).
Rignot, E. & Kanagaratnam, P. Changes in the velocity structure of the Greenland ice sheet. Science 311, 986–990 (2006).
Sasgen, I. et al. Timing and origin of recent regional ice-mass loss in Greenland. Earth Planet. Sci. Lett. 333–334, 293–303 (2012).
Box, J. E., Bromwich, D. H. & Bai, L. S. Greenland ice sheet surface mass balance 1991–2000: application of polar MM5 mesoscale model and in situ data. J. Geophys. Res. 109, D16105 (2004).
Wilson, N. J., Straneo, F. & Heimbach, P. Satellite-derived submarine melt rates and mass balance (2011–2015) for Greenland’s largest remaining ice tongues. Cryosphere 11, 2773–2782 (2017).
Bigg, G. R. et al. A century of variation in the dependence of Greenland iceberg calving on ice sheet surface mass balance and regional climate change. Proc. R. Soc. Lond. A 470, 20130662 (2014).
We acknowledge K. Buckley (Victoria University high-performance compute cluster), the Parallel Ice Sheet Model groups at University of Alaska, Fairbanks, the Potsdam Institute for Climate Impact Research and the CMIP community for making their data openly available. PISM is supported by NASA grants NNX13AM16G and NNX13AK27G. This work was funded by contract VUW1501 to N.R.G. from the Royal Society Te Aparangi, with support from the Antarctic Research Centre, Victoria University of Wellington, and GNS Science through the Ministry for Business, Innovation and Employment contract CO5X1001. N.G. was supported by the Natural Sciences and Engineering Research Council of Canada and the Canada Research Chairs programme. J.B. was supported by the MAGIC-DML project through DFG SPP 1158 (RO 4262/1-6). L.D.T. acknowledges support from the NSF Antarctic Glaciology Program (award 1643733).
Nature thanks F. Pattyn, H. Seroussi and the other anonymous reviewer(s) for their contribution to the peer review of this work.
Extended data figures and tables
a, b, Air (surface) temperature anomalies at 2100 arising from meltwater perturbations from ice sheets simulated under an RCP8.5 climate scenario. Arctic landmasses experience slight cool or warm anomalies, but temperatures over the Arctic ocean warm substantially in the region to the northeast of Greenland (around Svalbard), as far north as the North Pole (a). In the Southern Hemisphere, cooling of up to 3–4 °C occurs across the Southern Ocean and around the margins of Antarctica (b). Temperature anomalies are 30-year means to avoid aliasing short-term variability. c, d, Sea-level changes in the Southern Ocean and around Antarctica computed from the sea-level model (c), and with the addition of sea surface height changes due to ocean temperature changes (d). The thermosteric anomalies are from a 30-year mean to avoid aliasing short-term variability.
a, b, Surface air (a) and sea surface (b) temperature anomalies at 2100 arising solely from imposed meltwater fluxes, as a percentage of CMIP5 predictions based on emissions forcing but not including meltwater fluxes. c, Zonally and meridionally averaged surface air temperature anomalies for the globe, the Southern Ocean (40–85° S) and over the four largest ice shelves in Antarctica. d, Same as c, but adjusted to give changes relative to 2018.
Shown are results of 5-km-resolution simulations of the Antarctic ice sheet under peak-warmth Pliocene conditions, based on proxy-constrained climate and ocean fields from regional climate modelling54 but using an ice-sheet parameterization identical to that used for the RCP simulations presented in the main paper. The total sea-level-equivalent (SLE) mass loss after 5,000 years is 10.4 m, close to the 11.3 m simulated by a previous study that used ice-shelf hydrofracture and marine ice-cliff instability20, neither of which are used here.
The extent of grounded ice in West Antarctica at 2100, 2300 and 2500 is illustrated for two emissions pathways (RCP4.5 and RCP8.5) and for experiments in which the climate forcing is held constant from 2020, 2050 or 2100, but without the inclusion of ice–ocean–atmosphere feedbacks. Mass loss in these scenarios illustrates long-term commitments locked in by cumulative forcing up to the point of stabilization. Thwaites Glacier basin retreats in all scenarios, suggesting that the threshold for its stability has already been passed. Contour intervals are 250 m. Black lines show modern coast, for context.
. Control run (constant year-2000 climatology) and RCP8.5-forced experiments (including ice–ocean–atmosphere feedbacks) for Antarctica (a) and Greenland (b), with and without the incorporation of the sub-grid grounding-line melt scheme. Without the scheme, Antarctic ice volumes are higher in the forced run than with sub-grid melt enabled, but the control run also increases in volume, which suggests that other aspects of model parameterization would need to be optimized to ensure agreement with observational constraints (Extended Data Tables 1 and 2). Greenland simulations are far less affected by the sub-grid melt scheme. The Greenland runs shown all incorporate the evolving surface mass balance and basal traction parameterization (Methods), for clearer comparison between control and perturbed experiments. c, Change in grounded ice volume in Antarctica, compared to control runs, simulated by our ice-sheet model using a range of horizontal grid resolutions (see legend) but otherwise identical parameterization and including the sub-grid grounding-line basal melt scheme. d, Rate of Greenland Ice Sheet mass loss for the best-fitting simulation (dark blue line) compared to simulations in which either a steeper increase in sliding is applied (light blue line) or sliding is maintained at a constant value for the entire run (orange line). Numbers in brackets quantify the change in till friction angle in the piecewise-linear basal traction parameter below −200 m and above 500 m, relative to the ‘No taper’ experiment. Gold boxes show the time span (x axis) and uncertainty (y axis) of empirical data values used as targets during parameter optimization, from sources detailed in Extended Data Tables 1 and 2. e, f, Target melt rates from an empirically constrained99,100 ice-sheet simulation25 (e) are used as inputs to an inverse scheme that solves for a spatially distributed melt factor to translate CMIP5 sea surface temperatures into realistic melt fields (f). This approach greatly improves the representation of ice-shelf basal melting in our simulation compared to previous studies18,20.
a–c, Ocean temperature anomalies by 2100 at 415-m depth from Greenland meltwater flux only (a), Antarctic meltwater flux only (b) and combined meltwater flux from both ice sheets (c). Anomalies are 30-year means to avoid aliasing short-term variability.
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Climate policy implications of nonlinear decline of Arctic land permafrost and other cryosphere elements
Nature Communications (2019)