Seasonal evolution of snow density and its impact on thermal regime of sea ice during the MOSAiC expedition

Snow density is a crucial parameter for sea ice modelling at the physical process level. The seasonal evolution of surface (top 3 cm) and bulk (entire layer) snow densities observed during the MOSAiC expedition was investigated and used to assess four snow density schemes. A numerical snow and sea ice model was applied to simulate the sensitivity of sea ice to snow density and snow precipitation during the period when snow was dry. Snow densities of 348, 308, and 487 kg m-3 were derived from linear regression of snow water equivalent (SWE) against snow depth, using samples collected during three distinct periods: The entire MOSAiC period, the winter-spring period (October-May), and the summer-Autumn period (June-September), respectively. The examined snow density schemes produced mean snow densities consistent with MOSAiC observations; however, none of the schemes adequately captured the observed temporal variability in snow density. The modelled mean snow surface temperature and ice thickness showed a linear relationship with snow density, whereas the modelled mean in-snow and in-ice temperatures showed an inverse linear relationship with snow density. The impacts of a time-dependent snow density on snow and ice thermodynamic regimes were stronger than in the model runs using a constant snow density during the model period. Model sensitivity experiments showed that a higher snow density reduces snow and ice temperatures, promoting ice growth, whereas increased snow precipitation has the opposite effect. However, excessive snow accumulation can thicken the ice due to snow-ice formation.