More than 80% of the total fresh water on the Earth's surface is in the form of snow or ice. Seasonal snow cover comprises approximately 30% of the Earth's land surface, while 10% is perennial cover by glaciers. There has been significant interest in the state of the cryosphere and its response to a changing climate. Specifically, the assessment of spatio-temporal variability of melt dynamics can provide insights in the response of alpine systems to regional climate variability. Existing networks of ground-based stations are able to capture changes in snow water equivalent, but are insufficient in accurately capturing the melt process across a range of spatial scales. Satellite systems operating in the solar reflective and thermal regions of the electromagnetic spectrum can address these deficiencies and have demonstrated utility in monitoring changes in seasonal snowpack systems at annual and inter-annual scales. We have initially demonstrated that coupled optical/thermal snow surface characteristics can indicate snowpack propensity for melt release. Previous work has demonstrated that snow spectral reflectance is a strong function of grain-size, which can vary as a function of the amount of entrained liquid water. This coupled with surface thermal information indexing the kinetic state of the snowpack has great potential for elucidating internal snowpack conditions related to melting.
This grant supports acquisition of a portable field radiometer, operating in the visible, near-infrared, and short-wave infrared regions of the electromagnetic spectrum. Data collected will facilitate development and validation of an algorithm designed to leverage data from moderate resolution satellite system to map melt production and discharge in seasonal snowpack systems and support research on the long-term response of the cryosphere to potential anthropogenic forcing. Additionally, the portable radiometer system will be important in development of robust and comprehensive remote sensing curriculum as part of a broader inter-university initiative to improve remote sensing instruction.
