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: Lorenzo Zampieri, Frank Kauker, Jörg Fröhle, Hiroshi Sumata, Elizabeth C. Hunke, Helge F. Goessling
• Format: Article in Journal/Newspaper
• Language: English
• Published: American Geophysical Union (AGU) 2021
• Subjects: Arctic; FESOM2; Green's function; parameter optimization; sea ice; unstructured mesh; Physical geography; GB3-5030; Oceanography; GC1-1581; Sea ice
• Online Access: https://doi.org/10.1029/2020MS002438; https://doaj.org/article/f27672604e9d4268a21a6309e1118e89

Abstract 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.