Articles | Volume 13, issue 3
https://doi.org/10.5194/gmd-13-1763-2020
https://doi.org/10.5194/gmd-13-1763-2020
Methods for assessment of models
 | 
02 Apr 2020
Methods for assessment of models |  | 02 Apr 2020

On the calculation of normalized viscous–plastic sea ice stresses

Jean-François Lemieux and Frédéric Dupont

Related authors

Impact of non-normal flow rule on linear kinematic features in pan-Arctic ice-ocean simulations
Jean-Francois Lemieux, Mathieu Plante, Nils Hutter, Damien Ringeisen, Bruno Tremblay, Francois Roy, and Philippe Blain
EGUsphere, https://doi.org/10.5194/egusphere-2024-3831,https://doi.org/10.5194/egusphere-2024-3831, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
A sea ice deformation and rotation rate dataset (2017–2023) from the Environment and Climate Change Canada automated sea ice tracking system (ECCC-ASITS)
Mathieu Plante, Jean-François Lemieux, L. Bruno Tremblay, Amélie Bouchat, Damien Ringeisen, Philippe Blain, Stephen Howell, Mike Brady, Alexander S. Komarov, Béatrice Duval, Lekima Yakuden, and Frédérique Labelle
Earth Syst. Sci. Data, 17, 423–434, https://doi.org/10.5194/essd-17-423-2025,https://doi.org/10.5194/essd-17-423-2025, 2025
Short summary
CICE on a C-grid: new momentum, stress, and transport schemes for CICEv6.5
Jean-François Lemieux, William H. Lipscomb, Anthony Craig, David A. Bailey, Elizabeth C. Hunke, Philippe Blain, Till A. S. Rasmussen, Mats Bentsen, Frédéric Dupont, David Hebert, and Richard Allard
Geosci. Model Dev., 17, 6703–6724, https://doi.org/10.5194/gmd-17-6703-2024,https://doi.org/10.5194/gmd-17-6703-2024, 2024
Short summary
Using Icepack to reproduce ice mass balance buoy observations in landfast ice: improvements from the mushy-layer thermodynamics
Mathieu Plante, Jean-François Lemieux, L. Bruno Tremblay, Adrienne Tivy, Joey Angnatok, François Roy, Gregory Smith, Frédéric Dupont, and Adrian K. Turner
The Cryosphere, 18, 1685–1708, https://doi.org/10.5194/tc-18-1685-2024,https://doi.org/10.5194/tc-18-1685-2024, 2024
Short summary
Smoothed particle hydrodynamics implementation of the standard viscous–plastic sea-ice model and validation in simple idealized experiments
Oreste Marquis, Bruno Tremblay, Jean-François Lemieux, and Mohammed Islam
The Cryosphere, 18, 1013–1032, https://doi.org/10.5194/tc-18-1013-2024,https://doi.org/10.5194/tc-18-1013-2024, 2024
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

Geiger, C. A., Hibler, W. D., and Ackley, S. F.: Large-scale sea ice drift and deformation: Comparison between models and observations in the western Weddell Sea during 1992, J. Geophys. Res., 103, 21893–21913, https://doi.org/10.1029/98JC01258, 1998. a, b
Girard, L., Bouillon, S., Weiss, J., Amitrano, D., Fichefet, T., and Legat, V.: A new modeling framework for sea-ice mechanics based on elasto-brittle rheology, Ann. Glaciol., 52, 123–132, https://doi.org/10.3189/172756411795931499, 2011. a
Hibler, W. D.: A dynamic thermodynamic sea ice model, J. Phys. Oceanogr., 9, 815–846, 1979. a, b, c, d
Hibler, W. D. and Ackley, S. F.: Numerical simulation of the Weddell Sea pack ice, J. Geophys. Res., 88, 2873–2887, https://doi.org/10.1029/JC088iC05p02873, 1983. a
Hunke, E. C.: Viscous-plastic sea ice dynamics with the EVP model: linearization issues, J. Comput. Phys., 170, 18–38, https://doi.org/10.1006/jcph.2001.6710, 2001. a, b, c
Download
Short summary
Sea ice dynamics plays an important role in shaping the sea cover in polar regions. Winds and ocean currents exert large stresses on the sea ice cover. This can lead to the formation of long cracks and ridges, which strongly impact the exchange of heat, momentum and moisture between the atmosphere and the ocean. It is therefore crucial for a sea ice model to be able to represent these features. This article describes how internal sea ice stresses should be diagnosed from model simulations.
Share