Entering A New Era Of Water Science And Management: The Maturation Of Snow Remote Sensing
Painter, Thomas H. 1
1 Jet Propulsion Laboratory/California Institute of Technology
Snow cover and its melt dominate regional climate and water resources in the world鈥檚 mountainous regions, providing for critical agricultural and sustaining populations in otherwise dry regions. Snowmelt timing and magnitude in mountains tend to be controlled by absorption of solar radiation and snow water equivalent, respectively, and yet both of these are very poorly known even in the best-instrumented mountain regions of the globe.
In this talk, I discuss developments in the spaceborne and airborne remote sensing of snow properties, and the assimilation of these products into research water cycle modeling and operational forecasting. Our work with the National Weather Service鈥檚 欧美口爆视频 Basin River Forecast Center has shown marked improvements in runoff forecasting through inclusion of MODIS and VIIRS fractional snow covered area data. Moreover, the analyses have shown that the CBRFC forecasting errors are strongly sensitive to actual dust radiative forcing in snow with rising limb excursions as large as 40%. With MODIS retrievals of dust radiative forcing, the CBRFC will be implementing modifications to forecasts to reduce those errors to order < 10%.
In the last few years, the NASA Airborne Snow Observatory has emerged to provide the first spatially explicit distributions of snow water equivalent and coincident snow albedo products for mountain basins. ASO is an imaging spectrometer and imaging LiDAR system, to quantify snow water equivalent and snow albedo, provide unprecedented knowledge of snow properties, and provide complete, robust inputs to snowmelt runoff models, water management models, and systems of the future. Analyses show that with ASO data, river flows and reservoir inflows from the ASO acquisition date to 1 July can be estimated with uncertainties of less than 2%. The synergy of the ASO and the satellite retrievals will ultimately allow extension of quantitative knowledge to addressing the snowmelt water resources and availability for agricultural regions in sparsely instrumented regions of the globe.