The implementation and effectiveness of Calving Algorithms in numerical ice models (CalvingMIP)

Ice calving plays a significant role in ice sheet mass loss. Predictions of future ice sheet mass balance require accurate representations of the calving process in numerical ice models to determine rates of future global mean sea level rise. Whilst calving has recently begun to be implemented in numerical models there has not yet been a systematic investigation into how this implementation compares between different ice flow models. The Calving Model Intercomparison Project (CalvingMIP) has been established to address this question by providing a framework of experiments to investigate the accuracy of simulated calving rates and how simulated properties at the calving front evolve over time. Our initial focus has been on how calving is implemented in models, therefore focusing on calving algorithms, rather than on how much ice should be calved at a particular time via a calving law. Our results, from thirteen different numerical modelling groups, show that the majority of calving algorithms implemented are able to accurately implement a given calving rate with an ice front that evolves smoothly throughout the calving process, albeit with slightly more variation of results in a more complex domain. These results show that we can have confidence in the models capacity to accurately implement calving laws in the future.

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Publication Details

Journal
The Cryosphere
Published
2026-11-11
DOI
https://doi.org/10.5194/tc-20-6453-2026
Primary Topic
Cryospheric studies and observations
Type
article
Field-Weighted Citation Impact
0.00

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article

The implementation and effectiveness of Calving Algorithms in numerical ice models (CalvingMIP)

Frank Pattyn, G. Hilmar Gudmundsson, Tyler Pelle, Gong Cheng et al.
The Cryosphere
Cryospheric studies and observations
article

The implementation and effectiveness of Calving Algorithms in numerical ice models (CalvingMIP)

Frank Pattyn, G. Hilmar Gudmundsson, Tyler Pelle, Gong Cheng, Jorge A. Bernales, Youngmin Choi, Cruz Garcia-Molina, Martin Rückamp, Stephen Cornford, Torsten Albrecht, Daniel Abele, Daniel Moreno-Parada, Helene L. Seroussi, Liyun Zhao, Thomas Zwinger, Fabien Gillet‐Chaulet, Constantijn J. Berends, Angelika Humbert, Gunter Leguy, Marisa Montoya, Alexander Robinson, William H. Lipscomb, Javier Blasco, Jorge Álvarez-Solas, Mathieu Morlighem, Luisa Wagner, James R. Jordan, Yanmei Tian, Roderick S. W. van de Wal, Jowan M. Barnes
article en

Abstract

Ice calving plays a significant role in ice sheet mass loss. Predictions of future ice sheet mass balance require accurate representations of the calving process in numerical ice models to determine rates of future global mean sea level rise. Whilst calving has recently begun to be implemented in numerical models there has not yet been a systematic investigation into how this implementation compares between different ice flow models. The Calving Model Intercomparison Project (CalvingMIP) has been established to address this question by providing a framework of experiments to investigate the accuracy of simulated calving rates and how simulated properties at the calving front evolve over time. Our initial focus has been on how calving is implemented in models, therefore focusing on calving algorithms, rather than on how much ice should be calved at a particular time via a calving law. Our results, from thirteen different numerical modelling groups, show that the majority of calving algorithms implemented are able to accurately implement a given calving rate with an ice front that evolves smoothly throughout the calving process, albeit with slightly more variation of results in a more complex domain. These results show that we can have confidence in the models capacity to accurately implement calving laws in the future.

The CryosphereVol. 20(11)
Institut polytechnique de Grenoble (FR), Dartmouth College (US), NSF National Center for Atmospheric Research (US), Bavarian Academy of Sciences and Humanities (DE), Universidad Complutense de Madrid (ES), Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung (DE), Centre National de la Recherche Scientifique (FR), Université Libre de Bruxelles (BE), Consejo Superior de Investigaciones Científicas (ES), Scripps Institution of Oceanography (US), University of Bremen (DE), Utrecht University (NL), Beijing Normal University (CN), Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) (DE), Leibniz Association (DE), Northumbria University (GB), Danish Meteorological Institute (DK), University of Bristol (GB), University of California San Diego (US), Swansea University (GB), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Institut des Géosciences de l'Environnement (FR), NSF NCAR Climate and Global Dynamics Laboratory (US), Earth System Science Interdisciplinary Center (US), CSC - IT Center for Science (Finland) (FI), Instituto de Geociencias (ES), Max Planck Institute for the Science of Human History (DE), Institut de Recherche pour le Développement (FR), Potsdam Institute for Climate Impact Research (DE), Technical University of Munich (DE), University of Maryland, College Park (US)
National Science Foundation, National Aeronautics and Space Administration, Ministerio de Ciencia, Innovación y Universidades, European Commission, Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung, Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Novo Nordisk, Ministerio de Ciencia e Innovación, Horizon 2020 Framework Programme, HORIZON EUROPE Framework Programme, National Key Research and Development Program of China, H2020 Research Infrastructures
Climate action
Cryospheric studies and observations
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