Derivation of snow thickness information on sea ice using in-situ and satellite based multi-frequency polarimetric scatterometer and SAR data

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The recent and rapid reduction in Arctic sea ice has received considerable scientific and media attention during the past decade. This decrease has occurred to both its seasonal extent and to its thickness distribution. Modelling studies suggest that the long-term declining trend for both the extent and thickness of Arctic sea ice will continue for at least the next several decades due to an enhanced greenhouse effect resulting from the atmospheric build-up of anthropogenic produced gases. Global climate models participating in the latest Intergovernmental Panel on Climate Change - Fourth Assessment Report (IPCC-AR4) show that a transition to a summertime ice-free Arctic could occur both abruptly and earlier than previously anticipated. However, the sea ice cover remains highly variable from year-to-year within respect to its extent and thickness distribution owing to large scale atmospheric circulation pattern changes which operate over a continuum of time and space scales throughout the Arctic. These atmospheric circulation changes manifest to deposit spatially varying amounts of precipitation in the form of snow accumulation once the sea ice has formed, however, our ability to measure and quantify these amounts using optically based satellite remote sensing techniques is severely limited owing to cloud cover and 24-hour darkness during much of the fall and winter. The snow cover on sea ice is a critical component of snow/sea ice system because it controls the ice thickness and melt behaviour of the ice. As a result, it also largely controls the mechanical properties of the ice such as ice strength and break-up potential. This research will use all-weather imaging microwave remote sensing data acquired from both the ice surface and satellites along with snow covered thermodynamic sea ice and microwave scattering models fed with in situ collected snow and sea ice property data. The expected results will permit an estimation the snow cover characteristics (thickness distribution, snow water equivalent, liquid water content) at various times during the spring transition such that an improved understanding of the role of snow on sea ice can be assessed towards determining its role in the interannual variability in Arctic sea ice extent and thickness.