ISMIP6 Antarctica: a multi-model ensemble of the Antarctic ice sheet evolution over the 21st century

Seroussi, Hélène, Nowicki, Sophie, Payne, Antony J., Goelzer, Heiko, Lipscomb, William H., Abe-Ouchi, Ayako, Agosta, Cécile, Albrecht, Torsten, Asay-Davis, Xylar, Barthel, Alice, Calov, Reinhard, Cullather, Richard, Dumas, Christophe, Galton-Fenzi, Benjamin K., Gladstone, Rupert, Golledge, Nicholas R., Gregory, Jonathan M., Greve, Ralf, Hattermann, Tore, Hoffman, Matthew J., Humbert, Angelika, Huybrechts, Philippe, Jourdain, Nicolas C., Kleiner, Thomas, Larour, Eric, Leguy, Gunter R., Lowry, Daniel P., Little, Chistopher M., Morlighem, Mathieu, Pattyn, Frank, Pelle, Tyler, Price, Stephen F., Quiquet, Aurélien, Reese, Ronja, Schlegel, Nicole-Jeanne, Shepherd, Andrew, Simon, Erika, Smith, Robin S., Straneo, Fiammetta, Sun, Sainan, Trusel, Luke D., Van Breedam, Jonas, van de Wal, Roderik S. W., Winkelmann, Ricarda, Zhao, Chen, Zhang, Tong and Zwinger, Thomas (2020) ISMIP6 Antarctica: a multi-model ensemble of the Antarctic ice sheet evolution over the 21st century. The Cryosphere, 14 (9). pp. 3033-3070. ISSN 1994-0424

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Official URL: https://doi.org/10.5194/tc-14-3033-2020

Abstract

Ice flow models of the Antarctic ice sheet are commonly used to simulate its future evolution in response to different climate scenarios and assess the mass loss that would contribute to future sea level rise. However, there is currently no consensus on estimates of the future mass balance of the ice sheet, primarily because of differences in the representation of physical processes, forcings employed and initial states of ice sheet models. This study presents results from ice flow model simulations from 13 international groups focusing on the evolution of the Antarctic ice sheet during the period 2015-2100 as part of the Ice Sheet Model Intercomparison for CMIP6 (ISMIP6). They are forced with outputs from a subset of models from the Coupled Model Intercomparison Project Phase 5 (CMIP5), representative of the spread in climate model results. Simulations of the Antarctic ice sheet contribution to sea level rise in response to increased warming during this period varies between 7:8 and 30.0 cm of sea level equivalent (SLE) under Representative Concentration Pathway (RCP) 8.5 scenario forcing. These numbers are relative to a control experiment with constant climate conditions and should therefore be added to the mass loss contribution under climate conditions similar to presentday conditions over the same period. The simulated evolution of the West Antarctic ice sheet varies widely among models, with an overall mass loss, up to 18.0 cm SLE, in response to changes in oceanic conditions. East Antarctica mass change varies between 6:1 and 8.3 cm SLE in the simulations, with a significant increase in surface mass balance outweighing the increased ice discharge under most RCP 8.5 scenario forcings. The inclusion of ice shelf collapse, here assumed to be caused by large amounts of liquid water ponding at the surface of ice shelves, yields an additional simulated mass loss of 28mm compared to simulations without ice shelf collapse. The largest sources of uncertainty come from the climate forcing, the ocean-induced melt rates, the calibration of these melt rates based on oceanic conditions taken outside of ice shelf cavities and the ice sheet dynamic response to these oceanic changes. Results under RCP 2.6 scenario based on two CMIP5 climate models show an additional mass loss of 0 and 3 cm of SLE on average compared to simulations done under present-day conditions for the two CMIP5 forcings used and display limited mass gain in East Antarctica.

Item Type: Article
Additional Information: Funding Information: Research was carried out at the Jet Propulsion Laboratory, California Institute of Technology. Helene Seroussi and Nicole Schlegel are supported by grants from NASA Cryospheric Science and Modeling, Analysis, and Predictions Programs. AB was supported by the U.S. Department of Energy (DOE) Office of Science Regional and Global Model Analysis (RGMA) component of the Earth and Environmental System Modeling (EESM) program (HiLAT-RASM project), and the DOE Office of Science (Biological and Environmental Research), Early Career Research program. Heiko Goelzer has received funding from the program 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. Rupert Gladstone and Thomas Zwinger were supported by Academy of Finland grant nos. 286587 and 322430. Chen Zhao and Ben Galton-Fenzi 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). Support for Xylar Asay-Davis, Matthew Hoffman, Stephen Price and Tong Zhang was provided through the Scientific Discovery through Advanced Computing (SciDAC) program funded by the US Department of Energy (DOE), Office of Science, Advanced Scientific Computing Research, and Biological and Environmental Research Programs. MALI Earth System Grid Federation simulations used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science user facility supported by the Office of Science of the U.S. Department of Energy under contract no. DE-AC02-05CH11231. Nicolas Jourdain is funded by the French National Research Agency (ANR) through the TROIS-AS project (ANR-15-CE01-0005-01) and the European Commission through the TiPACCs project (grant no. 820575, call H2020-LC-CLA-2018-2). Philippe Huybrechts and Jonas Van Breedam acknowledge support from the iceMOD project funded by the Research Foundation - Flanders (FWO-Vlaanderen). Ralf Greve was supported by the Japan Society for the Promotion of Science (JSPS) KAKENHI (grant nos. JP16H02224, JP17H06104 and JP17H06323). Support for Nicholas Golledge and Daniel Lowry was provided by the New Zealand Ministry of Business Innovation and Employment contract no. RTVU1705. The work of Thomas Kleiner has been conducted in the framework of the PalMod project (FKZ: 01LP1511B), supported by the German Federal Ministry of Education and Research (BMBF) as part of the Research for Sustainability initiative (FONA). Support for Mathieu Morlighem and Tyler Pelle was provided by the National Science Foundation (NSF, grant no. 1739031). Development of PISM is supported by NASA (grant no. NNX17AG65G) and the NSF (grant nos. PLR-1603799 and PLR-1644277). Luke Trusel was supported under NSF Antarctic Glaciology Program award no. 1643733. The authors gratefully acknowledge the European Regional Development Fund (ERDF), the German Federal Ministry of Education and Research and the Federal State of Brandenburg for supporting this project by providing resources on the high-performance computer system at the Potsdam Institute for Climate Impact Research. Computer resources for this project have been also provided by the Gauss Centre for Supercomputing/Leibniz Supercomputing Centre (https://www.lrz.de/, last access: 8 July 2020) under Project ID pr94ga and pn69ru. Ronja Reese was supported by the Deutsche Forschungsgemeinschaft (DFG) under grant no. WI 4556/3-1 and through the TiPACCs project, which receives funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement no. 820575. Torsten Albrecht is supported by the Deutsche Forschungsgemeinschaft (DFG) in the framework of the priority program “Antarctic Research with comparative investigations in Arctic ice areas” by grant no. WI4556/2-1. Reinhard Calov was funded by the Bundesmin-isterium für Bildung und Forschung (BMBF) grants PalMod-1.1 and PalMod-1.3. Gunter Leguy and William Lipscomb 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. Funding support for Nicholas Golledge and Daniel Lowry was provided by the New Zealand Ministry of Business, Innovation and Employment through Victoria University of Wellington (RTUV1705), the Antarctic Science Platform (ANTA1801) and the Royal Society of New Zealand (grant no. RDF-VUW1501). Funding Information: Financial support. This research has been supported by the U.S. Department of Energy, Office of Science, the Netherlands Earth System Science Centre (grant no. 024.002.001), the Academy of Finland (grant nos. 286587 and 322430), the Australian Research Council (grant no. SR140300001), the Agence Nationale de la Recherche (grant no. ANR-15-CE01-0005-01), the European Commission (TiPACCs grant no. 820575), the Research Foundation – Flanders, the Japan Society for the Promotion of Science (grant nos. JP16H02224, JP17H06104 and JP17H06323), the New Zealand Ministry of Business Innovation and Employment (grant no. RTVU1705), the German Federal Ministry of Education and Research, the Office of Polar Programs (grant no. 1739031), the National Science Foundation (grant nos. 1603799, 1644277,1852977, and 1916566), the National Aeronautics and Space Administration (grant nos. NNX17AG65G and NNX17AI03G), the Deutsche Forschungsgemeinschaft (grant nos. WI4556/2-1 and WI4556/3-1), and the Norwegian Research Council (grant nos. 280727 and 295075).
Subjects: F900 Others in Physical Sciences
Department: Faculties > Engineering and Environment > Geography and Environmental Sciences
Depositing User: Rachel Branson
Date Deposited: 16 Sep 2021 15:05
Last Modified: 16 Sep 2021 15:15
URI: http://nrl.northumbria.ac.uk/id/eprint/47230

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