Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Geosci. Model Dev., 10, 765-789, 2017
© Author(s) 2017. This work is distributed
under the Creative Commons Attribution 3.0 License.
Model description paper
17 Feb 2017
The Finite-volumE Sea ice–Ocean Model (FESOM2)
Sergey Danilov1,2, Dmitry Sidorenko1, Qiang Wang1, and Thomas Jung1 1Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany
2A. M. Obukhov Institute of Atmospheric Physics RAS, Moscow, Russia
Abstract. Version 2 of the unstructured-mesh Finite-Element Sea ice–Ocean circulation Model (FESOM) is presented. It builds upon FESOM1.4 (Wang et al., 2014) but differs by its dynamical core (finite volumes instead of finite elements), and is formulated using the arbitrary Lagrangian Eulerian (ALE) vertical coordinate, which increases model flexibility. The model inherits the framework and sea ice model from the previous version, which minimizes the efforts needed from a user to switch from one version to the other. The ocean states simulated with FESOM1.4 and FESOM2.0 driven by CORE-II forcing are compared on a mesh used for the CORE-II intercomparison project. Additionally, the performance on an eddy-permitting mesh with uniform resolution is discussed. The new version improves the numerical efficiency of FESOM in terms of CPU time by at least 3 times while retaining its fidelity in simulating sea ice and the ocean. From this it is argued that FESOM2.0 provides a major step forward in establishing unstructured-mesh models as valuable tools in climate research.

Citation: Danilov, S., Sidorenko, D., Wang, Q., and Jung, T.: The Finite-volumE Sea ice–Ocean Model (FESOM2), Geosci. Model Dev., 10, 765-789, doi:10.5194/gmd-10-765-2017, 2017.
Publications Copernicus
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.
Numerical models of global ocean circulation are used to learn about future climate. The ocean...