Open AccessDesigning variable ocean model resolution based on the observed ocean variability
Author(s) -
Sein Dmitry V.,
Danilov Sergey,
Biastoch Arne,
Durgadoo Jonathan V.,
Sidorenko Dmitry,
Harig Sven,
Wang Qiang
Publication year - 2016
Publication title -
journal of advances in modeling earth systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.03
H-Index - 58
ISSN - 1942-2466
DOI - 10.1002/2016ms000650
Subject(s) - ocean gyre , polygon mesh , ocean current , ocean dynamics , geology , jet (fluid) , variable (mathematics) , flow (mathematics) , ocean general circulation model , climatology , meteorology , general circulation model , mechanics , geometry , climate change , physics , mathematics , oceanography , mathematical analysis , subtropics , fishery , biology
If unstructured meshes are refined to locally represent eddy dynamics in ocean circulation models, a practical question arises on how to vary the resolution and where to deploy the refinement. We propose to use the observed sea surface height variability as the refinement criterion. We explore the utility of this method (i) in a suite of idealized experiments simulating a wind‐driven double gyre flow in a stratified circular basin and (ii) in simulations of global ocean circulation performed with FESOM. Two practical approaches of mesh refinement are compared. In the first approach the uniform refinement is confined within the areas where the observed variability exceeds a given threshold. In the second one the refinement varies linearly following the observed variability. The resolution is fixed in time. For the double gyre case it is shown that the variability obtained in a high‐resolution reference run can be well captured on variable‐resolution meshes if they are refined where the variability is high and additionally upstream the jet separation point. The second approach of mesh refinement proves to be more beneficial in terms of improvement downstream the midlatitude jet. Similarly, in global ocean simulations the mesh refinement based on the observed variability helps the model to simulate high variability at correct locations. The refinement also leads to a reduced bias in the upper‐ocean temperature.