Articles | Volume 12, issue 6
https://doi.org/10.5194/gmd-12-2481-2019
https://doi.org/10.5194/gmd-12-2481-2019
Development and technical paper
 | 
27 Jun 2019
Development and technical paper |  | 27 Jun 2019

A rapidly converging initialisation method to simulate the present-day Greenland ice sheet using the GRISLI ice sheet model (version 1.3)

Sébastien Le clec'h, Aurélien Quiquet, Sylvie Charbit, Christophe Dumas, Masa Kageyama, and Catherine Ritz

Related authors

PARASO, a circum-Antarctic fully coupled ice-sheet–ocean–sea-ice–atmosphere–land model involving f.ETISh1.7, NEMO3.6, LIM3.6, COSMO5.0 and CLM4.5
Charles Pelletier, Thierry Fichefet, Hugues Goosse, Konstanze Haubner, Samuel Helsen, Pierre-Vincent Huot, Christoph Kittel, François Klein, Sébastien Le clec'h, Nicole P. M. van Lipzig, Sylvain Marchi, François Massonnet, Pierre Mathiot, Ehsan Moravveji, Eduardo Moreno-Chamarro, Pablo Ortega, Frank Pattyn, Niels Souverijns, Guillian Van Achter, Sam Vanden Broucke, Alexander Vanhulle, Deborah Verfaillie, and Lars Zipf
Geosci. Model Dev., 15, 553–594, https://doi.org/10.5194/gmd-15-553-2022,https://doi.org/10.5194/gmd-15-553-2022, 2022
Short summary
The future sea-level contribution of the Greenland ice sheet: a multi-model ensemble study of ISMIP6
Heiko Goelzer, Sophie Nowicki, Anthony Payne, Eric Larour, Helene Seroussi, William H. Lipscomb, Jonathan Gregory, Ayako Abe-Ouchi, Andrew Shepherd, Erika Simon, Cécile Agosta, Patrick Alexander, Andy Aschwanden, Alice Barthel, Reinhard Calov, Christopher Chambers, Youngmin Choi, Joshua Cuzzone, Christophe Dumas, Tamsin Edwards, Denis Felikson, Xavier Fettweis, Nicholas R. Golledge, Ralf Greve, Angelika Humbert, Philippe Huybrechts, Sebastien Le clec'h, Victoria Lee, Gunter Leguy, Chris Little, Daniel P. Lowry, Mathieu Morlighem, Isabel Nias, Aurelien Quiquet, Martin Rückamp, Nicole-Jeanne Schlegel, Donald A. Slater, Robin S. Smith, Fiamma Straneo, Lev Tarasov, Roderik van de Wal, and Michiel van den Broeke
The Cryosphere, 14, 3071–3096, https://doi.org/10.5194/tc-14-3071-2020,https://doi.org/10.5194/tc-14-3071-2020, 2020
Short summary
Eemian Greenland ice sheet simulated with a higher-order model shows strong sensitivity to surface mass balance forcing
Andreas Plach, Kerim H. Nisancioglu, Petra M. Langebroek, Andreas Born, and Sébastien Le clec'h
The Cryosphere, 13, 2133–2148, https://doi.org/10.5194/tc-13-2133-2019,https://doi.org/10.5194/tc-13-2133-2019, 2019
Short summary
Assessment of the Greenland ice sheet–atmosphere feedbacks for the next century with a regional atmospheric model coupled to an ice sheet model
Sébastien Le clec'h, Sylvie Charbit, Aurélien Quiquet, Xavier Fettweis, Christophe Dumas, Masa Kageyama, Coraline Wyard, and Catherine Ritz
The Cryosphere, 13, 373–395, https://doi.org/10.5194/tc-13-373-2019,https://doi.org/10.5194/tc-13-373-2019, 2019
Short summary
Eemian Greenland SMB strongly sensitive to model choice
Andreas Plach, Kerim H. Nisancioglu, Sébastien Le clec'h, Andreas Born, Petra M. Langebroek, Chuncheng Guo, Michael Imhof, and Thomas F. Stocker
Clim. Past, 14, 1463–1485, https://doi.org/10.5194/cp-14-1463-2018,https://doi.org/10.5194/cp-14-1463-2018, 2018
Short summary

Related subject area

Cryosphere
Towards deep-learning solutions for classification of automated snow height measurements (CleanSnow v1.0.2)
Jan Svoboda, Marc Ruesch, David Liechti, Corinne Jones, Michele Volpi, Michael Zehnder, and Jürg Schweizer
Geosci. Model Dev., 18, 1829–1849, https://doi.org/10.5194/gmd-18-1829-2025,https://doi.org/10.5194/gmd-18-1829-2025, 2025
Short summary
Quantitative sub-ice and marine tracing of Antarctic sediment provenance (TASP v1.0)
James W. Marschalek, Edward Gasson, Tina van de Flierdt, Claus-Dieter Hillenbrand, Martin J. Siegert, and Liam Holder
Geosci. Model Dev., 18, 1673–1708, https://doi.org/10.5194/gmd-18-1673-2025,https://doi.org/10.5194/gmd-18-1673-2025, 2025
Short summary
Tuning parameters of a sea ice model using machine learning
Anton Korosov, Yue Ying, and Einar Ólason
Geosci. Model Dev., 18, 885–904, https://doi.org/10.5194/gmd-18-885-2025,https://doi.org/10.5194/gmd-18-885-2025, 2025
Short summary
WRF-Chem simulations of snow nitrate and other physicochemical properties in northern China
Xia Wang, Tao Che, Xueyin Ruan, Shanna Yue, Jing Wang, Chun Zhao, and Lei Geng
Geosci. Model Dev., 18, 651–670, https://doi.org/10.5194/gmd-18-651-2025,https://doi.org/10.5194/gmd-18-651-2025, 2025
Short summary
Clustering simulated snow profiles to form avalanche forecast regions
Simon Horton, Florian Herla, and Pascal Haegeli
Geosci. Model Dev., 18, 193–209, https://doi.org/10.5194/gmd-18-193-2025,https://doi.org/10.5194/gmd-18-193-2025, 2025
Short summary

Cited articles

Arthern, R. J. and Gudmundsson, G. H.: Initialization of ice-sheet forecasts viewed as an inverse Robin problem, J. Glaciol., 56, 527–533, https://doi.org/10.3189/002214310792447699, 2010. a, b
Aschwanden, A., Fahnestock, M. A., and Truffer, M.: Complex Greenland outlet glacier flow captured, Nat. Commun., 7, 10524, https://doi.org/10.1038/ncomms10524, 2016. a
Bamber, J. L., Griggs, J. A., Hurkmans, R. T. W. L., Dowdeswell, J. A., Gogineni, S. P., Howat, I., Mouginot, J., Paden, J., Palmer, S., Rignot, E., and Steinhage, D.: A new bed elevation dataset for Greenland, The Cryosphere, 7, 499–510, https://doi.org/10.5194/tc-7-499-2013, 2013. a, b, c, d, e, f, g, h, i, j
Berrisford, P., Dee, D., Poli, P., Brugge, R., Fielding, M., Fuentes, M., Kållberg, P., Kobayashi, S., Uppala, S., and Simmons, A.: The ERA-Interim archive Version 2.0, Tech. Rep. 1, ECMWF, Shinfield Park, Reading, 2011. a
Bindschadler, R. A., Nowicki, S., Abe-Ouchi, A., Aschwanden, A., Choi, H., Fastook, J., Granzow, G., Greve, R., Gutowski, G., Herzfeld, U., Jackson, C., Johnson, J., Khroulev, C., Levermann, A., Lipscomb, W. H., Martin, M. A., Morlighem, M., Parizek, B. R., Pollard, D., Price, S. F., Ren, D., Saito, F., Sato, T., Seddik, H., Seroussi, H., Takahashi, K., Walker, R., and Wang, W. L.: Ice-sheet model sensitivities to environmental forcing and their use in projecting future sea level (the SeaRISE project), J. Glaciol., 59, 195–224, https://doi.org/10.3189/2013JoG12J125, 2013. a
Download
Short summary
To provide reliable projections of the ice-sheet contribution to future sea-level rise, ice sheet models must be able to simulate the observed ice sheet present-day state. Using a low computational iterative minimisation procedure, based on the adjustment of the basal drag coefficient, we rapidly minimise the errors between the simulated and the observed Greenland ice thickness and ice velocity, and we succeed in stabilising the simulated Greenland ice sheet state under present-day conditions.
Share