Impact of sea-ice model complexity on the performance of an unstructured-grid sea-ice/ocean model under different atmospheric forcing

Abstract:

We have equipped the unstructured-grid global sea-ice and ocean model FESOM2 with a set of physical parameterizations by integrating 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 grid, 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 in a fair way 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 and ERA5 forcings. The results suggest that a more complex sea-ice representation in the model leads to a better agreement between modeled and observed sea-ice concentration and thickness and snow thickness. However, the results strongly depend on the employed atmospheric forcing, with NCEP performing better than ERA5 in particular for the complex sea-ice formulation. In this respect, we show that the parameter calibration can compensate for differences between atmospheric forcings much more effectively in the simple model version in which sea ice has no heat capacity