| Summary: | The Louvain-la-Neuve sea Ice Model (LIM) is a three-dimensional global model for sea-ice dynamics and thermodynamics that has been specifically designed for climate studies and that is fully coupled with the oceanic general circulation model OPA on the modelling platform NEMO. This study assesses the skills of a new onedimensional snow model developed for the thermodynamic component of LIM, by comparison with the former model thermodynamics and observations. Snow is a key element in sea-ice physics and in the interactions between sea ice and atmosphere. Owing to its low thermal conductivity and high albedo, the snow cover is a very efficient insulator and it contributes directly and indirectly to the sea-ice mass balance. Given the high variability and heterogeneity of the snow cover above sea ice, it is necessary to represent different types of snow, depending on their characteristics. A multilayer approach has been chosen for the model, with time varying temperature, density and thermal conductivity for each layer. Vertical heat diffusion, surface and internal melt, precipitations, snow-ice formation and a parameterisation for melt-pond albedo are included in the model. The model is validated at Point Barrow (Alaska) and at the Ice Station POLarstern (ISPOL) in the western Weddell Sea (Southern Ocean). The new snow thermodynamic scheme leads to better snow and ice internal temperature profiles, with a setup-dependent increase in the correlation between modelled and observed temperature profiles. The model ability to reproduce observed temperatures improves with the number of snow layers, but stabilizes after a threshold layer number is reached. This threshold is different at Point Barrow and ISPOL. Ice ablation rate is quite insensitive to snow thermal conductivity in summer because almost all the variability at the surface is absorbed by snow, making the temperature gradient in the ice relatively small and steady. Nevertheless, during winter, when the air temperature falls far below the freezing point, ...
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