Snow property characterization for improved radar altimetry estimates of sea ice thickness

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Earth's climate is experiencing unprecedented change and monitoring and predicting the nature of this change is an ongoing global scientific endeavor. Inclusion of sea ice in global climate models is paramount due to its control on heat transfer between the atmosphere and ocean. For example, with less sea ice, more ocean heat can transfer to the Arctic atmosphere, leading to further warming and less sea ice, a particularly damaging positive feedback loop. Arctic sea ice extent has declined by 13% and thinned by nearly 40% over the past four decades as estimated from satellites, with the Arctic Ocean predicted to become ice free in summer for the first time before 2050. Today, more than 80% of the Arctic sea ice cover is composed of seasonal sea ice. Considerable uncertainty remains as to how these changes will influence the Arctic marine ecosystem, Arctic and mid-latitude climates and ecosystems, socio-economic issues such as pan-Arctic shipping and cruise tourism, and the livelihood of indigenous communities including those in northern Canada. The snow cover on sea ice is a critical component of snow/sea ice system because it controls the ice accretion and ablation rate due to its relatively small thermal conductivity. Because of the high albedo of snow, shortwave radiative exchanges dominate the sea ice-albedo' feedback mechanism and act to insulate the sea ice from the warming atmosphere during the spring to summer transition. As a result, the snow cover ultimately controls sea ice thickness and subsequent melt behavior and largely determines the mechanical strength properties which control sea ice summer break-up potential. The accuracy of pan-Arctic sea ice thickness estimates from satellite remote sensing depends on the performance of statistical thresholding methods using radar altimetry to distinguish sea ice floes from sea ice leads and open water. However, these simple methods do not fully account for seasonally and spatially varying complex geophysical processes in the snow cover on sea ice, which affect radar propagation and add considerable error and uncertainty to estimates. These salient variables include snow depth, snow density, snow grain size and specific surface area, snow electrical properties including liquid water and snow brine content. New and improved geophysical instrumentation developed in recent years now permits characterization of these key snow variables with significantly improved accuracy. The instrumentation suite described in this proposal will significantly improve performance of dielectric and microwave scattering models for assessment of radar altimetry estimates of snow thickness on sea ice. This proposal also describes the urgency for a suite of state-of-the-art snow geophysical instrumentation and an HQP data collection focused plan towards improved snow geophysical property measurements towards Arctic-wide improvements to sea ice thickness estimates from radar altimetry. *****************