Datasets and protocols for including anomalous freshwater from melting ice sheets in climate simulations

Abstract. Anomalous freshwater fluxes from the Greenland and Antarctic ice sheets and ice shelves are impacting the surrounding oceans, and we need to be able to account for these effects in climate model simulations over the historical period and in future projections. In previous phases of the Coupled Model Intercomparison Project (CMIP), models mostly either assumed that the ice sheets were in mass balance, or that discharge from the ice sheets was constant, but in neither case was the observed increasing discharge over the historical period properly represented. In this paper, we present data products of absolute and anomalous freshwater mass fluxes from both major ice sheets, and recommendations for their use in historical simulations. These fluxes can be implemented in climate simulations as a forcing for models that do not (yet) include interactive ice sheets, or used to evaluate models that do. We also make recommendations for how climatological and anomalous fluxes can be implemented in climate models that may have different approaches to interactions with the ice sheets. These forcings are available for CMIP7 simulations and should lead to more robust and coherent simulation of sea surface temperature, sea ice and regional sea level trends in the recent historical period and, as these data are extended, improve the credibility of projections.

Authors

Institutions

Publication Details

Journal
Geoscientific model development
Published
2025-11-07
DOI
https://doi.org/10.5194/gmd-18-8333-2025
Primary Topic
Cryospheric studies and observations
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Datasets and protocols for including anomalous freshwater from melting ice sheets in climate simulations

Clive R. McMahon, Sophie Nowicki, Thomas Rackow, Kenneth D. Mankoff et al.
Geoscientific model development
Cryospheric studies and observations
article

Datasets and protocols for including anomalous freshwater from melting ice sheets in climate simulations

Clive R. McMahon, Sophie Nowicki, Thomas Rackow, Kenneth D. Mankoff, Gavin A. Schmidt, Twila Moon, Matthew H. England, Violaine Coulon, Juliana M. Marson, Anna Olivé Abelló, Benjamin Davison, Ruth Mottram, Pierre Mathiot, Jonathan Bamber, David Chandler, Andrew George Pauling, Dustin Carroll, Damien Ringeisen, Nicolas C. Jourdain, Clara Burgard, Qian Li, Paul R. Holland
article en

Abstract

Abstract. Anomalous freshwater fluxes from the Greenland and Antarctic ice sheets and ice shelves are impacting the surrounding oceans, and we need to be able to account for these effects in climate model simulations over the historical period and in future projections. In previous phases of the Coupled Model Intercomparison Project (CMIP), models mostly either assumed that the ice sheets were in mass balance, or that discharge from the ice sheets was constant, but in neither case was the observed increasing discharge over the historical period properly represented. In this paper, we present data products of absolute and anomalous freshwater mass fluxes from both major ice sheets, and recommendations for their use in historical simulations. These fluxes can be implemented in climate simulations as a forcing for models that do not (yet) include interactive ice sheets, or used to evaluate models that do. We also make recommendations for how climatological and anomalous fluxes can be implemented in climate models that may have different approaches to interactions with the ice sheets. These forcings are available for CMIP7 simulations and should lead to more robust and coherent simulation of sea surface temperature, sea ice and regional sea level trends in the recent historical period and, as these data are extended, improve the credibility of projections.

Geoscientific model developmentVol. 18(21)
Florida State University (US), Institut polytechnique de Grenoble (FR), Goddard Institute for Space Studies (US), Centre National de la Recherche Scientifique (FR), British Antarctic Survey (GB), Université Libre de Bruxelles (BE), Jet Propulsion Laboratory (US), Climate Central (US), Environment and Climate Change Canada (CA), Cooperative Institute for Research in Environmental Sciences (US), University of Colorado Boulder (US), Bjerknes Centre for Climate Research (NO), Danish Meteorological Institute (DK), University of Bristol (GB), Sorbonne Université (FR), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Integra (United States) (US), Institut des Géosciences de l'Environnement (FR), National Centre for Earth Observation (GB), Australian Centre for Advanced Computing and Communications (Australia) (AU), Sydney Institute of Marine Science (AU), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (FR), Climate Foundation (US), Institut de Recherche pour le Développement (FR), Technical University of Munich (DE), University at Buffalo, State University of New York (US), Massachusetts Institute of Technology (US), University of Otago (NZ), Université Grenoble Alpes (FR), University of Sheffield (GB), Moss Landing Marine Laboratories (US)
National Science Foundation, National Aeronautics and Space Administration, UK Research and Innovation, European Commission, Agence Nationale de la Recherche, Bundesministerium für Bildung und Forschung, Horizon 2020 Framework Programme, Earth Sciences Division, HORIZON EUROPE Framework Programme, Natural Environment Research Council, Office of Polar Programs, H2020 Societal Challenges
Openalex Percentile: Top 62%
Cryospheric studies and observations
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.