Improving Snow Estimates over the Red River Basin during the Spring Using Empirical Relationships Between Satellite Snow Water Equivalent and Snow-Covered Area
Technical Report,01 Jan 2018,31 Dec 2019
ENGINEER RESEARCH AND DEVELOPMENT CENTER HANOVER NH HANOVER United States
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Assessing rapid changes in snow storage during spring is critical for predicting river flooding along the Red River in the north-central United States. While passive microwave retrievals of snow water equivalent SWE over the Red River water basin are generally accurate, they are less certain during the spring due to snowmelt events. These degrade the SWE retrieval algorithms by introducing liquid water into the snowpack. To increase confidence in daily SWE estimates over the Red River basin, we use the concept of a SWE depletion curve to relate basin mean SWE to snow-covered area SCA as determined by the MODIS cloud-gap-filled daily SCA product. We use this concept to derive an empirical relation-ship between SWE and SCA over the Red River basin from 11 years of satellite observations 2007-2018. This relationship relies on the climatologically accurate passive microwave SWE product to mitigate acute inaccuracies in daily SWE retrievals caused by data gaps and complicated snowpack properties. In a comparison of SWE derived from the empirical SCA relationship to SWE estimated from the Snow Data Assimilation product, we find substantial quantitative improvement over the passive microwave SWE product during the spring melt season.
- Snow, Ice and Permafrost