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Incorporating remotely-sensed snow albedo into a spatially-distributed snowmelt model
Department of Hydrology and Water Resources, University of Arizona, Tucson, Arizona, USA
National Snow and Ice Data Center, University of Colorado, Boulder, Colorado, USA
Division of Engineering, University of California, Merced, California, USA
Donald Bren School of Environmental Science and Management, University of California, Santa Barbara, California, USA
Basin-average albedo estimated from remotely-sensed Airborne Visible/Infrared Imaging Spectroradiometer (AVIRIS) data specific to the catchment typically differed by 20% from albedo estimated using a common snow-age-based empirical relation. In some parts of the basin, differences were as large as 0.31. Using the AVIRIS albedo estimates in a distributed snowmelt model that explicitly includes net solar radiation resulted in a much more accurate estimate of the timing and magnitude of snowmelt as compared to the same model with the empirical albedo (R 2 of 0.73 versus 0.59 and magnitude error of 2% versus 36%). Model improvement was most significant in areas and at times where incident solar radiation was relatively high and temperatures low.
Received 12 November 2003; accepted 31 December 2003; published 13 February 2004.
Citation: (2004), Incorporating remotely-sensed snow albedo into a spatially-distributed snowmelt model, Geophys. Res. Lett., 31, L03501, doi:10.1029/2003GL019063.
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