Quantifying the Effect of Snow-Ice Formation on Snow Depth and Density
over Arctic Sea Ice
Abstract
This study quantified 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 sea ice thermodynamic model. Pan-Arctic model
simulations were performed over the period 1 August 1980 through 31 July
2022. We compared snow depth and density from the coupled product
(SnowModel-LG_HS) to the original outputs of SnowModel-LG. In
SnowModel-LG_HS, domain average snow depth decreased by 22%, and snow
density increased by 2% when compared to SnowModel-LG. The differences
were much larger in the Atlantic sector. Our simulations suggest that
when snow-on-sea-ice models account for snow-ice formation, snow depth
can be remarkably reduced. Sea ice thickness retrievals from CryoSat-2
were guided by both snow products. Averaged across the CryoSat-2 era
(2011-2022), domain average sea ice thickness retrievals decreased by
10% when snow-ice was accounted for.