Projected land ice contributions to twenty-first-century sea level rise

International audience The land ice contribution to global mean sea level rise has not yet been predicted1 using ice sheet and glacier models for the latest set of socio-economic scenarios, nor using coordinated exploration of uncertainties arising from the various computer models involved. Two rece...

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Published in:Nature
Main Authors: Edwards, Tamsin L., Nowicki, Sophie M.J., Marzeion, Ben, Hock, Regine, Goelzer, Heiko, Seroussi, Hélène, Jourdain, Nicolas, Slater, Donald A., Turner, Fiona E., Smith, Christopher J., Mckenna, Christine M., Simon, Erika G., Abe-Ouchi, Ayako, Gregory, Jonathan M., Larour, Eric Y., Lipscomb, William H., Payne, Antony J., Shepherd, Andrew P., Agosta, Cécile, Alexander, Patrick M., Albrecht, Torsten, Anderson, Brian M., Asay-Davis, Xylar S., Aschwanden, Andy, Barthel, Alice M., Bliss, Andrew K., Calov, Reinhard, Chambers, Christopher, Champollion, Nicolas, Choi, Youngmin, Cullather, Richard I., Cuzzone, Joshua K., Dumas, Christophe, Felikson, Denis, Fettweis, Xavier, Fujita, Koji, Galton-Fenzi, Benjamin K., Gladstone, Rupert M.M., Golledge, Nicholas R., Greve, Ralf, Hattermann, Tore, Hoffman, Matthew J., Humbert, Angelika, Huss, Matthias, Huybrechts, P., Immerzeel, Walter Willem (walter), Kleiner, Thomas, Kraaijenbrink, Philip D.A., Le Clec’h, Sébastien, Lee, Victoria, Leguy, Gunter R., Little, Christopher M., Lowry, Daniel P., Malles, Jan Hendrik, Martin, Daniel F., Maussion, Fabien, Morlighem, Mathieu, O’neill, James F., Nias, Isabel J., Pattyn, Frank, Pelle, Tyler, Price, Stephen F., Quiquet, Aurélien, Radić, Valentina, Reese, Ronja, Rounce, David Robert, Rückamp, Martin, Sakai, Akiko, Shafer, Courtney, Schlegel, Nicole Jeanne, Shannon, Sarah R., Smith, Robin S., Straneo, Fiamma, Sun, Sainan, Tarasov, Lev, Trusel, Luke D., van Breedam, Jonas, van de Wal, Roderick S.W., van den Broeke, M. R., Winkelmann, Ricarda, Zekollari, Harry, Zhao, Chen, Zhang, Tong, Zwinger, Thomas
Other Authors: Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Glaces et Continents, Climats et Isotopes Stables (GLACCIOS), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Modélisation du climat (CLIM), Fonds De La Recherche Scientifique - FNRS, FNRS Horizon 2020: 820829 Australian Government: ASCI000002 Horizon 2020 Framework Programme, H2020: 869304 U.S. Department of Energy, USDOE O0100718F British Antarctic Survey, BAS Bundesministerium für Bildung und Forschung, BMBF: 01LP1504D, FKZ 01LP1502C Ministerie van Onderwijs, Cultuur en Wetenschap, OCW: 024.002.001 Natural Environment Research Council, NERC: NE/T007443/1 Deutsche Forschungsgemeinschaft, DFG: WI4556/2-1, 01LP1925D, WI4556/4-1 Norges Forskningsråd: 270061, 295046 American Research Center in Sofia, ARCS National Science Foundation, NSF: 1852977 National Center for Atmospheric Research, NCAR Horizon 2020 Framework Programme, H2020: NNX17AG65G, 820575 U.S. Department of Energy, USDOE Japan Society for the Promotion of Science, KAKEN: JP16H02224, JP17H06104, JP17H06323 Ministerie van Onderwijs, Cultuur en Wetenschap, OCW Office of Science, SC Suomen Akatemia: 286587, 322430 National Centre for Atmospheric Science, NCAS National Aeronautics and Space Administration, NASA Netherlands Earth System Science Centre, NESSC European Space Agency, ESA U.S. Department of Energy, USDOE Belgian Federal Science Policy Office, BELSPO: SR/00/336 National Science Foundation, NSF: PLR-1644277, PLR-1603799 Universiteit Utrecht, UU European Regional Development Fund, ERDF Bundesministerium für Bildung und Forschung, BMBF: WI4556/3-1 Ministry of Education, Culture, Sports, Science and Technology, Monbusho National Aeronautics and Space Administration, NASA Natural Environment Research Council, NERC Natural Environment Research Council, NERC Ministry for Business Innovation and Employment, MBIE: RTUV1705, ANTA1801 International Institute for Applied Systems Analysis, IIASA: NE/T009381/1 Biological and Environmental Research, BER: DE-AC02-05CH11231 Australian Research Council, ARC: SR140300001 European Commission, EC Office of Science, SC: DE-SC0020073 Ministry of Education, Culture, Sports, Science and Technology, Monbusho: JPMXD1420318865, JPMXD1300000000 Advanced Scientific Computing Research, ASCR, Acknowledgements We thank J. Rougier for providing advice and support throughout, and writing the original random effects model. We also thank B. Fox-Kemper, H. Hewitt, R. Kopp, S. Drijfhout and J. Rohmer for discussions, suggestions and support. We thank N. Barrand, W. Chang, V. Volodina and D. Williamson for their thorough and constructive comments, which greatly improved the manuscript. We thank the Climate and Cryosphere (CliC) Project, which provided support for ISMIP6 and GlacierMIP through sponsoring of workshops, hosting the websites and ISMIP6 wiki, and promotion. We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP5 and CMIP6. We thank the climate modelling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the CMIP data and providing access, the University at Buffalo for ISMIP6 data distribution and upload, and the multiple funding agencies who support CMIP5 and CMIP6 and ESGF. We thank the ISMIP6 steering committee, the ISMIP6 model selection group and the ISMIP6 dataset preparation group for their continuous engagement in defining ISMIP6. This is ISMIP6 contribution no. 13. This publication was supported by PROTECT, which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 869304. This is PROTECT contribution number 12. T.L.E. was supported by PROTECT and the UK Natural Environment Research Council grant NE/T007443/1. F.T. was supported by PROTECT. J.F.O’N. was supported by the UK Natural Environment Research Council London Doctoral Training Partnership. R. Gladstone’s contribution was supported by Academy of Finland grants 286587 and 322430, and T. Zwinger’s by grant 322430. W.H.L. and G.R.L. were supported by the National Center for Atmospheric Research, which is a major facility sponsored by the National Science Foundation under Cooperative Agreement no. 1852977. Computing and data storage resources for CISM simulations, including the Cheyenne supercomputer (https://doi.org/10.5065/D6RX99HX), were provided by the Computational and Information Systems Laboratory (CISL) at NCAR. Support for X.A.-D., M.J.H., S.F.P. and T. Zhang was provided through the Scientific Discovery through Advanced Computing (SciDAC) programme funded by the US Department of Energy (DOE), Office of Science, Advanced Scientific Computing Research and Biological and Environmental Research programmes. N.R.G., D.P.L. and B.A. were supported by New Zealand Ministry for Business, Innovation and Employment contracts RTUV1705 (‘NZSeaRise’) and ANTA1801 (‘Antarctic Science Platform’). J.M.G. and R.S.S. were supported by the National Centre for Atmospheric Science, funded by the UK National Environment Research Council. R. Calov was funded by the PalMod project of the Bundesministerium für Bildung und Forschung (BMBF) with the grants FKZ 01LP1502C and 01LP1504D. D.F.M. and C.S. were supported by the Director, Office of Science, Offices of Advanced Scientific Computing Research (ASCR) and Biological and Environmental Research (BER), of the US Department of Energy under contract no. DE-AC02-05CH11231, as a part of the ProSPect SciDAC Partnership. BISICLES simulations used resources of the National Energy Research Scientific Computing Center (NERSC), a US Department of Energy Office of Science User Facility operated under contract no. DE-AC02-05CH11231. C.Z. and B.K.G.-F. were supported under the Australian Research Council’s Special Research Initiative for Antarctic Gateway Partnership (project ID SR140300001) and received grant funding from the Australian Government for the Australian Antarctic Program Partnership (project ID ASCI000002). Work was performed by E.L., N.-J.S. and H.S. at the California Institute of Technology’s Jet Propulsion Laboratory under a contract with the National Aeronautics and Space Administration; support was provided by grants from NASA’s Cryospheric Science, Sea Level Change Team, and Modeling, Analysis and Prediction (MAP) programmes. They acknowledge computational resources and support from the NASA Advanced Supercomputing Division. The CMIP5 and CMIP6 projection data were processed by C.M.M. with funding from the European Union’s CONSTRAIN project as part of the Horizon 2020 Research and Innovation Programme under grant agreement number 820829. A. Barthel was supported by the DOE Office of Science HiLAT-RASM project and Early Career Research programme. T.A. and R.W. are supported by the Deutsche Forschungsgemeinschaft (DFG) in the framework of the priority programme ‘Antarctic research with comparative investigations in Arctic ice areas’ by grants WI4556/2-1 and WI4556/4-1, and within the framework of the PalMod project (FKZ: 01LP1925D) supported by the German Federal Ministry of Education and Research (BMBF) as a Research for Sustainability initiative (FONA). R.R. is supported by the Deutsche Forschungsgemeinschaft (DFG) by grant WI4556/3-1 and through the TiPACCs project that receives funding from the European Union’s Horizon 2020 Research and Innovation programme under grant agreement no. 820575. Development of PISM is supported by NASA grant NNX17AG65G and NSF grants PLR-1603799 and PLR-1644277. The authors gratefully acknowledge the European Regional Development Fund (ERDF), the German Federal Ministry of Education and Research and the Land Brandenburg for supporting this project by providing resources for the high-performance computer system at the Potsdam Institute for Climate Impact Research. Computer resources for this project have also been provided by the Gauss Centre for Supercomputing, Leibniz Supercomputing Centre (http://www.lrz.de, last access: 16 July 2020) under project IDs pr94ga and pn69ru. R. Greve and C.C. were supported by Japan Society for the Promotion of Science (JSPS) KAKENHI grant nos JP16H02224 and JP17H06323. R. Greve was supported by JSPS KAKENHI grant no. JP17H06104, by a Leadership Research Grant of Hokkaido University’s Institute of Low Temperature Science (ILTS), and by the Arctic Challenge for Sustainability (ArCS, ArCS II) project of the Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) (programme grant nos JPMXD1300000000, JPMXD1420318865). F.P. and S. Sun were supported by the MIMO project within the STEREO III programme of the Belgian Science Policy Office, contract SR/00/336 and the Fonds de la Recherche Scientifique (FNRS) and the Fonds Wetenschappelijk Onderzoek-Vlaanderen (FWO) under the EOS project no. O0100718F. A. Shepherd was supported by the UK Natural Environment Research Council in partnership with the Centre for Polar Observation and Modelling and the British Antarctic Survey and by the European Space Agency Climate Change Initiative. D.F. was supported by an appointment to the NASA Postdoctoral Program at the NASA Goddard Space Flight Center, administered by Universities Space Research Association under contract with NASA. R.v.d.W. acknowledges the support of the Future Deltas programme of Utrecht University. C.J.S. was supported by a NERC/IIASA Collaborative Research Fellowship (NE/T009381/1). H.G. has received funding from the programme of the Netherlands Earth System Science Centre (NESSC), financially supported by the Dutch Ministry of Education, Culture and Science (OCW) under grant no. 024.002.001 and from the Research Council of Norway under projects INES (270061) and KeyClim (295046). F.S. acknowledges support from DOE Office of Science grant no. DE-SC0020073. High-performance computing and storage resources were provided by the Norwegian Infrastructure for Computational Science through projects NN9560K, NN9252K, NS9560K, NS9252K and NS5011K.
Format: Article in Journal/Newspaper
Language:English
Published: HAL CCSD 2021
Subjects:
Online Access:https://hal.science/hal-03230877
https://hal.science/hal-03230877/document
https://hal.science/hal-03230877/file/hal2.pdf
https://doi.org/10.1038/s41586-021-03302-y
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Summary:International audience The land ice contribution to global mean sea level rise has not yet been predicted1 using ice sheet and glacier models for the latest set of socio-economic scenarios, nor using coordinated exploration of uncertainties arising from the various computer models involved. Two recent international projects generated a large suite of projections using multiple models2–8, but primarily used previous-generation scenarios9 and climate models10, and could not fully explore known uncertainties. Here we estimate probability distributions for these projections under the new scenarios11,12 using statistical emulation of the ice sheet and glacier models. We find that limiting global warming to 1.5 degrees Celsius would halve the land ice contribution to twenty-first-century sea level rise, relative to current emissions pledges. The median decreases from 25 to 13 centimetres sea level equivalent (SLE) by 2100, with glaciers responsible for half the sea level contribution. The projected Antarctic contribution does not show a clear response to the emissions scenario, owing to uncertainties in the competing processes of increasing ice loss and snowfall accumulation in a warming climate. However, under risk-averse (pessimistic) assumptions, Antarctic ice loss could be five times higher, increasing the median land ice contribution to 42 centimetres SLE under current policies and pledges, with the 95th percentile projection exceeding half a metre even under 1.5 degrees Celsius warming. This would severely limit the possibility of mitigating future coastal flooding. Given this large range (between 13 centimetres SLE using the main projections under 1.5 degrees Celsius warming and 42 centimetres SLE using risk-averse projections under current pledges), adaptation planning for twenty-first-century sea level rise must account for a factor-of-three uncertainty in the land ice contribution until climate policies and the Antarctic response are further constrained.