Impact of sea-ice model complexity on the performance of an
unstructured-mesh sea-ice/ocean model under different atmospheric
forcings
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 fairly
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
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 the
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 energy consistent formulations with a prognostic
ice thickness distribution.