Articles | Volume 10, issue 2
Model description paper
17 Feb 2017
Model description paper |  | 17 Feb 2017

The Finite-volumE Sea ice–Ocean Model (FESOM2)

Sergey Danilov, Dmitry Sidorenko, Qiang Wang, and Thomas Jung

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., 17, 2287–2297,,, 2024
Short summary
Split-explicit external mode solver in finite volume sea ice ocean model FESOM2
Tridib Banerjee, Patrick Scholz, Sergey Danilov, Knut Klingbeil, and Dimitry Sidorenko
Geosci. Model Dev. Discuss.,,, 2024
Revised manuscript 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,,, 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,,, 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,,, 2022
Short summary

Related subject area

DELWAVE 1.0: deep learning surrogate model of surface wave climate in the Adriatic Basin
Peter Mlakar, Antonio Ricchi, Sandro Carniel, Davide Bonaldo, and Matjaž Ličer
Geosci. Model Dev., 17, 4705–4725,,, 2024
Short summary
StraitFlux – precise computations of water strait fluxes on various modeling grids
Susanna Winkelbauer, Michael Mayer, and Leopold Haimberger
Geosci. Model Dev., 17, 4603–4620,,, 2024
Short summary
Comparison of the Coastal and Regional Ocean COmmunity model (CROCO) and NCAR-LES in non-hydrostatic simulations
Xiaoyu Fan, Baylor Fox-Kemper, Nobuhiro Suzuki, Qing Li, Patrick Marchesiello, Peter P. Sullivan, and Paul S. Hall
Geosci. Model Dev., 17, 4095–4113,,, 2024
Short summary
Intercomparisons of Tracker v1.1 and four other ocean particle-tracking software packages in the Regional Ocean Modeling System
Jilian Xiong and Parker MacCready
Geosci. Model Dev., 17, 3341–3356,,, 2024
Short summary
CAR36, a regional high-resolution ocean forecasting system for improving drift and beaching of Sargassum in the Caribbean archipelago
Sylvain Cailleau, Laurent Bessières, Léonel Chiendje, Flavie Dubost, Guillaume Reffray, Jean-Michel Lellouche, Simon van Gennip, Charly Régnier, Marie Drevillon, Marc Tressol, Matthieu Clavier, Julien Temple-Boyer, and Léo Berline
Geosci. Model Dev., 17, 3157–3173,,, 2024
Short summary

Cited articles

Adcroft, A. and Hallberg, R.: On methods for solving the oceanic equations of motion in generalized vertical coordinates, Ocean Model., 11, 224–233, 2006.
Blazek, J.: Computational fluid dynamics: Principles and applications, Elsevier Ltd., 2001.
Campin, J.-M., Adcroft, A., Hill, C., and Marshall, J.: Conservation of properties in a free-surface model, Ocean Model., 6, 221–244, 2004.
Chen, C., Liu, H., and Beardsley, R. C.: An unstructured, finite volume, three-dimensional, primitive equation ocean model: application to coastal ocean and estuaries, J. Atmos. Ocean. Tech., 20, 159–186, 2003.
Colella, P. and Woodward, P. R.: The piecewise parabolic method (PPM) for gas-dynamical simulations, J. Comput. Phys., 54, 174–201, 1984.
Short summary
Numerical models of global ocean circulation are used to learn about future climate. The ocean circulation is characterized by processes on different spatial scales which are still beyond the reach of present computers. We describe a new model setup that allows one to vary a model's spatial resolution and hence focus the computational power on regional dynamics, reaching a better description of local processes in areas of interest.