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Fractional snow cover in the Colorado and Rio Grande basins, 1995–2002
Author(s) -
Bales R. C.,
Dressler K. A.,
Imam B.,
Fassnacht S. R.,
Lampkin D.
Publication year - 2008
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2006wr005377
Subject(s) - snow , water equivalent , environmental science , advanced very high resolution radiometer , terrain , snowpack , cloud cover , hydrology (agriculture) , snowmelt , snow cover , precipitation , meteorology , climatology , physical geography , satellite , geology , cloud computing , geography , cartography , geotechnical engineering , computer science , engineering , aerospace engineering , operating system
A cloud‐masked fractional snow‐covered area (SCA) product gridded at 1 km was developed from the advanced very high resolution radiometer for the Colorado River and upper Rio Grande basins for 1995–2002. Cloud cover limited SCA retrievals on any given 1‐km 2 pixel to on average once per week. There were sufficient cloud‐free scenes to map SCA over at least part of the basins up to 21 days per month, with 3 months having only two scenes sufficiently cloud free to process. In the upper Colorado and upper Grande, SCA peaked in February–March. Maxima were 1–2 months earlier in the lower Colorado. Averaged over a month, as much as 32% of the upper Colorado and 5.5% of the lower Colorado were snow covered. Snow cover persisted longest at higher elevations for both wet and dry years. Interannual variability in snow cover persistence reflected wet‐dry year differences. Compared with an operational (binary) SCA product produced by the National Operational Hydrologic Remote Sensing Center, the current products classify a lower fraction of pixels as having detectable snow and being cloud covered (5.5% for SCA and 6% for cloud), with greatest differences in January and June in complex, forested terrain. This satellite‐derived subpixel determination of snow cover provides the potential for enhanced hydrologic forecast abilities in areas of complex, snow‐dominated terrain. As an example, we merged the SCA product with interpolated ground‐based snow water equivalent (SWE) to develop a SWE time series. This interpolated, masked SWE peaked in April, after SCA peaked and after some of the lower‐elevation snow cover had melted.