Investigating the Effect of Snow-Ice Formation on Snow Depth and Density
over Arctic Sea Ice
Abstract
We examined the effect of snow-ice formation on SnowModel-LG snow depth
and density products. We coupled SnowModel-LG, a modeling system adapted
for snow depth and density reconstruction over sea ice, with HIGHTSI, a
1-D thermodynamic sea ice model, to create SnowModel-LG_HS. Pan-Arctic
model simulations spanned from 1 August 1980 through 31 July 2022. In
SnowModel-LG_HS, domain average snow depth decreased by 20%, and snow
density increased by 2% when compared to SnowModel-LG, with largest
differences in the Atlantic sector. Averaged across the CryoSat-2 era
(2011–2022), domain average April sea ice thickness retrievals from
CryoSat-2 decreased by 7.7% when snow-ice was accounted for. Evaluation
of SnowModel-LG HS against snow depth, snow-ice, and sea ice thickness
observations highlighted the importance of snow redistribution over
deformed sea ice. The findings suggest that neglecting snow and sea ice
interactions in models can lead to substantial overestimation of snow
depth over level ice.