Impact of Sea‐Ice Model Complexity on the Performance of an Unstructured‐Mesh Sea‐Ice/Ocean Model under Different Atmospheric Forcings

• Published in: Journal of Advances in Modeling Earth Systems
• Main Authors: Zampieri, Lorenzo, Kauker, Frank, Fröhle, Jörg, Sumata, Hiroshi, Hunke, Elizabeth C., Goessling, Helge F., Kauker, Frank; 1 Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research Bremerhaven Germany, Fröhle, Jörg; 3 Kiel University Kiel Germany, Sumata, Hiroshi; 4 Norwegian Polar Institute Fram Centre Tromsø Norway, Hunke, Elizabeth C.; 5 Los Alamos National Laboratory Los Alamos NM USA, Goessling, Helge F.; 1 Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research Bremerhaven Germany
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2021
• Subjects: ddc:551.343; Arctic; FESOM2; Green's function; parameter optimization; sea ice; unstructured mesh; Sea ice
• Online Access: https://doi.org/10.23689/fidgeo-4315; http://resolver.sub.uni-goettingen.de/purl?gldocs-11858/8661

We have equipped the unstructured‐mesh global sea‐ice and ocean model FESOM2 with a set of physical parameterizations derived from the single‐column sea‐ice model Icepack. The update has substantially broadened the range of physical processes that can be represented by the model. The new features are directly implemented on the unstructured FESOM2 mesh, and thereby benefit from the flexibility that comes with it in terms of spatial resolution. A subset of the parameter space of three model configurations, with increasing complexity, has been calibrated with an iterative Green's function optimization method to test the impact of the model update on the sea‐ice representation. Furthermore, to explore the sensitivity of the results to different atmospheric forcings, each model configuration was calibrated separately for the NCEP‐CFSR/CFSv2 and ERA5 forcings. The results suggest that a complex model formulation leads to a better agreement between modeled and the observed sea‐ice concentration and snow thickness, while differences are smaller for sea‐ice thickness and drift speed. However, the choice of the atmospheric forcing also impacts the agreement of the FESOM2 simulations and observations, with NCEP‐CFSR/CFSv2 being particularly beneficial for the simulated sea‐ice concentration and ERA5 for sea‐ice drift speed. In this respect, our results indicate that parameter calibration can better compensate for differences among atmospheric forcings in a simpler model (i.e., sea‐ice has no heat capacity) than in more realistic formulations with a prognostic sea‐ice thickness distribution and sea ice enthalpy. Plain Language Summary: The role of model complexity in determining the performance of sea‐ice numerical simulations is still not completely understood. Some studies suggest that a more sophisticated description of the sea‐ice physics leads to simulations that agree better with sea‐ice observations. Others, however, fail to establish a link between complex model formulations and improved model performance. Here, ...