Snow depth on Antarctic sea ice: a Lagrangian model-based approach

Snow on Antarctic sea ice is an important yet poorly resolved component of the global climate system. Whilst much attention over the past few years has been dedicated to producing reanalysis-forced models of snow on sea ice in the Arctic, none currently exist for the Southern Hemisphere. Here we present a Lagrangian-framework model of snow depth on Antarctic sea ice, in which “parcels” of ice accumulate snow as they drift around the ocean according to daily ice motion vectors. Snow accumulates from two sources; (i) snowfall from ERA5 atmospheric reanalysis and (ii) snow blown off the Antarctic continent, which we estimate using the RACMO2 ice sheet mass balance model. Ice parcels lose snow via wind-redistribution into leads and through snow-ice formation. We validate our dynamic snow product against ship-based measurements from the ASPeCT data archive, and we compare our long-term climatology against estimates derived from passive microwave (AMSR-E/2) satellites. Finally, we assess regional trends in snow depth over the past four decades and investigate whether these are driven by changes in snowfall or divergence/convergence of the Antarctic sea ice pack.