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Design and results of the ice sheet model initialisation initMIP-Greenland: An ISMIP6 intercomparison

  • Heiko Goelzer*
  • , Sophie M J Nowicki
  • , Tamsin L. Edwards
  • , Matthew Beckley
  • , Ayako Abe-Ouchi
  • , Andy Aschwanden
  • , Reinhard Calov
  • , Olivier Gagliardini
  • , Fabien Gillet-Chaulet
  • , Nicholas R. Golledge
  • , Jonathan M. Gregory
  • , Ralf Greve
  • , Angelika Humbert
  • , Philippe Huybrechts
  • , Joseph H. Kennedy
  • , Eric Larour
  • , William H. Lipscomb
  • , Sébastien Leclech
  • , Victoria Lee
  • , Mathieu Morlighem
  • Frank Pattyn, Antony J. Payne, Christian B. Rodehacke, Martin Rückamp, Fuyuki Saito, Nicole Jeanne Schlegel, Helene Seroussi, Andrew Shepherd, Sainan Sun, Roderik Van De Wal, Florian A. Ziemen
*Corresponding author for this work
  • Utrecht University
  • Université libre de Bruxelles
  • NASA Goddard Space Flight Center
  • Open University Milton Keynes
  • King's College London
  • The University of Tokyo
  • University of Alaska Fairbanks
  • Potsdam Institute for Climate Impact Research
  • Université Grenoble Alpes
  • Victoria University of Wellington
  • University of Reading
  • Met Office
  • Hokkaido University
  • Alfred Wegener Institute - Helmholtz Centre for Polar and Marine Research
  • University of Bremen
  • Vrije Universiteit Brussel
  • Oak Ridge National Laboratory
  • Jet Propulsion Laboratory, California Institute of Technology
  • Los Alamos National Laboratory
  • National Center for Atmospheric Research
  • Université de Versailles Saint-Quentin-en-Yvelines
  • University of Bristol
  • University of California at Irvine
  • Danish Meteorological Institute
  • Japan Agency for Marine-Earth Science and Technology
  • University of Leeds
  • Max Planck Institute for Meteorology

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Earlier large-scale Greenland ice sheet sea-level projections (e.g. those run during the ice2sea and SeaRISE initiatives) have shown that ice sheet initial conditions have a large effect on the projections and give rise to important uncertainties. The goal of this initMIP-Greenland intercomparison exercise is to compare, evaluate, and improve the initialisation techniques used in the ice sheet modelling community and to estimate the associated uncertainties in modelled mass changes. initMIP-Greenland is the first in a series of ice sheet model intercomparison activities within ISMIP6 (the Ice Sheet Model Intercomparison Project for CMIP6), which is the primary activity within the Coupled Model Intercomparison Project Phase 6 (CMIP6) focusing on the ice sheets. Two experiments for the large-scale Greenland ice sheet have been designed to allow intercomparison between participating models of (1) the initial present-day state of the ice sheet and (2) the response in two idealised forward experiments. The forward experiments serve to evaluate the initialisation in terms of model drift (forward run without additional forcing) and in response to a large perturbation (prescribed surface mass balance anomaly); they should not be interpreted as sea-level projections. We present and discuss results that highlight the diversity of data sets, boundary conditions, and initialisation techniques used in the community to generate initial states of the Greenland ice sheet. We find good agreement across the ensemble for the dynamic response to surface mass balance changes in areas where the simulated ice sheets overlap but differences arising from the initial size of the ice sheet. The model drift in the control experiment is reduced for models that participated in earlier intercomparison exercises.

Original languageEnglish
Pages (from-to)1433-1460
Number of pages28
JournalCryosphere
Volume12
Issue number4
DOIs
Publication statusPublished - 19 Apr 2018

Funding

Acknowledgements. We acknowledge the Climate and Cryosphere (CliC) project and the World Climate Research Programme (WCRP) for their guidance, support, and sponsorship. We thank the CMIP6 panel members for their continuous leadership of the CMIP6 effort, and the Working Group on Coupled Modeling (WGCM) Infrastructure Panel (WIP) for overseeing the CMIP6 and ISMIP6 infrastructure and data request. We would like to thank Brice Noël for help with the SMB validation data and Xavier Fet-tweis, Miren Vizcaino, and Vincent Cabot for providing SMB data. We also thank Erika Simon for help with the data processing. Andy Aschwanden, Eric Larour, Sophie Nowicki, and Helene Seroussi were supported by grants from the NASA Cryospheric Science Program and Modeling, Analysis, and Prediction Program. Heiko Goelzer 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. Nicholas R. Golledge is supported by Royal Society of New Zealand Rutherford Discovery Fellowship 15-VUW-004. Philippe Huybrechts acknowledges support from the iceMOD project funded by the Research Foundation – Flanders (FWO-Vlaanderen). William H. Lipscomb and Joseph H. Kennedy were supported by the Regional and Global Climate Modeling and Earth System Modeling programmes of the U.S. Department of Energy’s Office of Science. The National Center for Atmospheric Research is sponsored by the National Science Foundation. Victoria Lee, Stephen L. Cornford, and Antony J. Payne carried out work as part of the UKESM contribution for CMIP6. Mathieu Morlighem was supported by NASA’s Cryospheric Sciences Program (no. NNX15AD55G) and the National Science Foundation’s Arctic System Science Program (ARCSS) (no. 1504230). Christian Rodehacke (DMI) has received funding from the European Research Council under the European Community’s Seventh Framework Programme (FP7/2007–2013)/ERC grant agreement 610055 as part of the Ice2Ice project as well as the Nordic Center of Excellence eSTICC (eScience Tool for In-vestigating Climate Change in northern high latitudes) funded by Nordforsk (grant 57001). Florian A. Ziemen was supported by the BMBF project PALMOD. Computational resources for MPI-PISM were made available by DKRZ through support from BMBF. IGE-ELMER simulations were performed using the Froggy platform of the CIMENT infrastructure – which is supported by the Rhône-Alpes region (grant CPER07_13 CIRA), the OSUG@2020 laBex (reference ANR10 LABX56), and the Equip@Meso project (reference ANR-10-EQPX-29-01) – and using HPC resources from GENCI-CINES (grant 2016-016066). Ralf Greve, Ayako Abe-Ouchi, and Fuyuki Saito were supported by the Arctic Challenge for Sustainability (ArCS) project of the Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT), and by the Japan Society for the Promotion of Science (JSPS) KAKENHI under grant no. 17H06104, Ralf Greve and Ayako Abe-Ouchi were additionally supported under JSPS grant no. 16H02224, and Fuyuki Saito under JSPS grant no. 17K05664. Ayako Abe-Ouchi and Fuyuki Saito were supported by the Integrated Research Program for Advancing Climate Models (TOUGOU program) from MEXT. Reinhard Calov was funded by the Leibniz Association grant SAW-2014-PIK-1 and is now funded by the Bundesministerium für Bildung und Forschung (BMBF) grants PalMod-1.1-TP5 and PalMod-1.3-TP4.

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