Extended Abstract (608K)12.1
A new blended global snow product using visible, passive microwave, and scatterometer satellite data
James L. Foster, NASA/GSFC, Greenbelt, MD; and D. K. Hall, J. B. Eylander, G. A. Riggs, E. J. Kim, M. Tedesco, S. V. Nghiem, R. E. J. Kelly, and B. J. Choudhury
The objective is to show the development of a joint U.S. Air Force/NASA blended, global snow product, utilizing Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Microwave Scanning Radiometer for NASA's Earth Observing System (AMSR-E) passive microwave data, and QuikSCAT scatterometer data. These data are being blended into a single, global, daily, and user-friendly product. The initial blended snow product is an example of data fusion with minimal modeling to expeditiously yield improved snow products, which include snow cover extent, fractional snow cover, onset of snowmelt, and areas of snow cover that are actively melting. Snow products at medium resolution (currently 25 km) are initially validated using data from the northern U.S. and from data gathered in Colorado at Cold Lands Project Experiment (CLPX) sites in 2002 and 2003. The AMSR-E product is especially useful in detecting snow through clouds. However, passive microwave data misses snow in those regions where the snow cover is rather thin, along the margins of the continental snow line and on the lee side of the Rocky Mountains. In these regions, MODIS can map shallow snow cover. Because the confidence for mapping snow cover extent is greater with the visible product than with the microwave product when cloud free MODIS observations are available, they are used as “truth.” The microwave-derived snow cover will be used only in those areas where MODIS is not applicable due to the presence of clouds and darkness. AMSR-E data at 19 GHz (horizontal channel) is used in association with the difference between ascending and descending satellite passes to detect the onset of melt, and QuikSCAT data (14 GHz) are used to map areas of snow that are actively melting. The next step is to include snow water equivalent (SWE) into our blended product. In addition, we are working to improve the resolution of the global daily snow cover and SWE products toward 5 km. We will also incorporate an 89-GHz global snow detection and SWE algorithm into the blended product software.
Session 12, Advances in Remote Sensing and Data Assimilation in Hydrology, Part IV
Thursday, 24 January 2008, 3:30 PM-5:00 PM, 223
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