Articles | Volume 8, issue 6
https://doi.org/10.5194/gmd-8-1747-2015
https://doi.org/10.5194/gmd-8-1747-2015
Model description paper
 | 
11 Jun 2015
Model description paper |  | 11 Jun 2015

Finite-Element Sea Ice Model (FESIM), version 2

S. Danilov, Q. Wang, R. Timmermann, N. Iakovlev, D. Sidorenko, M. Kimmritz, T. Jung, and J. Schröter

Related authors

CD-type discretization for sea ice dynamics in FESOM version 2
Sergey Danilov, Carolin Mehlmann, Dmitry Sidorenko, and Qiang Wang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-37,https://doi.org/10.5194/gmd-2023-37, 2023
Preprint under review for GMD
Short summary
AWI-CM3 coupled climate model: description and evaluation experiments for a prototype post-CMIP6 model
Jan Streffing, Dmitry Sidorenko, Tido Semmler, Lorenzo Zampieri, Patrick Scholz, Miguel Andrés-Martínez, Nikolay Koldunov, Thomas Rackow, Joakim Kjellsson, Helge Goessling, Marylou Athanase, Qiang Wang, Jan Hegewald, Dmitry V. Sein, Longjiang Mu, Uwe Fladrich, Dirk Barbi, Paul Gierz, Sergey Danilov, Stephan Juricke, Gerrit Lohmann, and Thomas Jung
Geosci. Model Dev., 15, 6399–6427, https://doi.org/10.5194/gmd-15-6399-2022,https://doi.org/10.5194/gmd-15-6399-2022, 2022
Short summary
Cloud-based framework for inter-comparing submesoscale-permitting realistic ocean models
Takaya Uchida, Julien Le Sommer, Charles Stern, Ryan P. Abernathey, Chris Holdgraf, Aurélie Albert, Laurent Brodeau, Eric P. Chassignet, Xiaobiao Xu, Jonathan Gula, Guillaume Roullet, Nikolay Koldunov, Sergey Danilov, Qiang Wang, Dimitris Menemenlis, Clément Bricaud, Brian K. Arbic, Jay F. Shriver, Fangli Qiao, Bin Xiao, Arne Biastoch, René Schubert, Baylor Fox-Kemper, William K. Dewar, and Alan Wallcraft
Geosci. Model Dev., 15, 5829–5856, https://doi.org/10.5194/gmd-15-5829-2022,https://doi.org/10.5194/gmd-15-5829-2022, 2022
Short summary
Assessment of the Finite-VolumE Sea ice–Ocean Model (FESOM2.0) – Part 2: Partial bottom cells, embedded sea ice and vertical mixing library CVMix
Patrick Scholz, Dmitry Sidorenko, Sergey Danilov, Qiang Wang, Nikolay Koldunov, Dmitry Sein, and Thomas Jung
Geosci. Model Dev., 15, 335–363, https://doi.org/10.5194/gmd-15-335-2022,https://doi.org/10.5194/gmd-15-335-2022, 2022
Short summary
Plume spreading test case for coastal ocean models
Vera Fofonova​​​​​​​, Tuomas Kärnä, Knut Klingbeil, Alexey Androsov, Ivan Kuznetsov, Dmitry Sidorenko, Sergey Danilov, Hans Burchard, and Karen Helen Wiltshire
Geosci. Model Dev., 14, 6945–6975, https://doi.org/10.5194/gmd-14-6945-2021,https://doi.org/10.5194/gmd-14-6945-2021, 2021
Short summary

Related subject area

Oceanography
Barents-2.5km v2.0: an operational data-assimilative coupled ocean and sea ice ensemble prediction model for the Barents Sea and Svalbard
Johannes Röhrs, Yvonne Gusdal, Edel S. U. Rikardsen, Marina Durán Moro, Jostein Brændshøi, Nils Melsom Kristensen, Sindre Fritzner, Keguang Wang, Ann Kristin Sperrevik, Martina Idžanović, Thomas Lavergne, Jens Boldingh Debernard, and Kai H. Christensen
Geosci. Model Dev., 16, 5401–5426, https://doi.org/10.5194/gmd-16-5401-2023,https://doi.org/10.5194/gmd-16-5401-2023, 2023
Short summary
Open-ocean tides simulated by ICON-O, version icon-2.6.6
Jin-Song von Storch, Eileen Hertwig, Veit Lüschow, Nils Brüggemann, Helmuth Haak, Peter Korn, and Vikram Singh
Geosci. Model Dev., 16, 5179–5196, https://doi.org/10.5194/gmd-16-5179-2023,https://doi.org/10.5194/gmd-16-5179-2023, 2023
Short summary
Using Probability Density Functions to Evaluate Models (PDFEM, v1.0) to compare a biogeochemical model with satellite-derived chlorophyll
Bror F. Jönsson, Christopher L. Follett, Jacob Bien, Stephanie Dutkiewicz, Sangwon Hyun, Gemma Kulk, Gael L. Forget, Christian Müller, Marie-Fanny Racault, Christopher N. Hill, Thomas Jackson, and Shubha Sathyendranath
Geosci. Model Dev., 16, 4639–4657, https://doi.org/10.5194/gmd-16-4639-2023,https://doi.org/10.5194/gmd-16-4639-2023, 2023
Short summary
Data assimilation sensitivity experiments in the East Auckland Current system using 4D-Var
Rafael Santana, Helen Macdonald, Joanne O'Callaghan, Brian Powell, Sarah Wakes, and Sutara H. Suanda
Geosci. Model Dev., 16, 3675–3698, https://doi.org/10.5194/gmd-16-3675-2023,https://doi.org/10.5194/gmd-16-3675-2023, 2023
Short summary
Using the COAsT Python package to develop a standardised validation workflow for ocean physics models
David Byrne, Jeff Polton, Enda O'Dea, and Joanne Williams
Geosci. Model Dev., 16, 3749–3764, https://doi.org/10.5194/gmd-16-3749-2023,https://doi.org/10.5194/gmd-16-3749-2023, 2023
Short summary

Cited articles

Bouillon, S., Fichefet, T., Legat, V., and Madec, G.: The elastic-viscous-plastic method revisited, Ocean Model. 71, 2–12, 2013.
Budgell, W. P., Oliveira, A., and Skogen, M. D.: Scalar advection schemes for ocean modeling on unstructured triangular grids, Ocean Dynam. 57, 339–361, 2007.
Gao, G., Chen, C., Qi, J., and Beardsley, R. C.: An unstructured-grid, finite-volume sea ice model: Development, validation, and application, J. Geophys. Res., 116, C00D04, https://doi.org/10.1029/2010JC006688, 2011.
Hibler, W. D.: A dynamic thermodynamic sea ice model, J. Phys. Oceanogr., 9, 817–846, 1979.
Hunke, E. C.: Viscous-plastic sea ice dynamics with the EVP model: Linearization issues, J. Comp. Phys., 170, 18–38, 2001.
Download
Short summary
Unstructured meshes allow multi-resolution modeling of ocean dynamics. Sea ice models formulated on unstructured meshes are a necessary component of ocean models intended for climate studies. This work presents a description of a finite-element sea ice model which is used as a component of a finite-element sea ice ocean circulation model. The principles underlying its design can be of interest to other groups pursuing ocean modelling on unstructured meshes.