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- C43B-01: A spatiotemporal analysis of non-snow errors in InSAR SWE retrievals (invited)
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NOLA CC
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Ross Palomaki, University of Colorado Boulder (First Author, Presenting Author)
Zachary Hoppinen, Alaska Satellite Facility
Hans-Peter Marshall, Boise State University
Mountain snowmelt provides an important water source for billions of people, but it is currently not possible for us to measure where and how much snow is stored in a given mountain range. This presents a challenge for water resource managers in many regions. The new NISAR satellite gives us the ability to measure snow in a way that has not been previously possible. NISAR will make repeat measurements around the planet every 12 days. If the amount of snow on the ground at a given location changes within that 12 day period, it affects the NISAR signal in a particular way. However, other factors like trees and soil can also affect the NISAR signal in ways that look similar to the snow effects. We need to carefully account for these non-snow factors to make our snow measurements more accurate. In this presentation, we show how the non-snow factors change over space and time, and how they can influence the accuracy of the NISAR snow measurements.
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