Snow thickness estimation on first-year sea ice using microwave and optical remote sensing with melt modelling

The snow cover on first-year sea ice plays a paramount role in thermodynamics by modulating sea ice ablation and accretion processes. However, meteoric accumulation and redistribution of snow on first-year sea ice is highly stochastic over space and time, which makes it a poorly understood parameter. In this study, a region of late-winter snow thickness on first-year sea ice in the Canadian Arctic Archipelago is estimated using time series spaceborne C-band microwave scatterometer and optical MODIS data and a simple snow melt model. Results show good correspondence between the modeled snow thickness and remotely sensed dates of melt onset and pond onset. The mean snowmelt duration for 20 study sites is 24.6 ± 1.2 days, and the estimated mean snow thickness is 14.7 ± 3.0 cm. The overall performance of the model reveals a RMSE of 4.0 cm and a mean bias of 0.3 cm. The methodology shows promise; particularly because it can easily be scaled up in order to estimate snow thickness on seasonal sea ice on a regional basis.