Abstract
A new sea ice model, GELATO, was developed at Centre National de Recherches Météorologiques (CNRM) and coupled with OPA global ocean model. The sea ice model includes elastic–viscous–plastic rheology, redistribution of ice floes of different thicknesses, and it also takes into account leads, snow cover and snow ice formation. Climatologies of atmospheric surface parameters are used to perform a 20-year global ocean–sea ice simulation, in order to compute surface heat fluxes from diagnosed sea ice or ocean surface temperature. A surface salinity restoring term is applied only to ocean grid cells with no sea ice to avoid significant surface salinity drifts, but no correction of sea surface temperature is introduced. In the Arctic the use of an ocean model substantially improves the representation of sea ice, and particularly of the ice edge in all seasons, as advection of heat and salt can be more accurately accounted for than in the case of, for example, a sea ice–ocean mixed layer model. In contrast, in the Antarctic, a region where ocean convective processes bear a much stronger influence in shaping sea ice characteristics, a better representation of convection and probably of sea ice (for example, of frazil sea ice, brine rejection) would be needed to improve the simulation of the annual cycle of the sea ice cover. The effect of the inclusion of several ice categories in the sea ice model is assessed by running a sensitivity experiment in which only one category of sea ice is considered, along with leads. In the Arctic, such an experiment clearly shows that a multicategory sea ice model better captures the position of the sea ice edge and yields much more realistic sea ice concentrations in most of the region, which is in agreement with results from Bitz et al. [J. Geophys. Res. 106 (C2) (2001) 2441–2463].
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