COMBINING SATELLITE, IN-SITU AND CLIMATOLOGY DATA FOR SNOW DEPTH ESTIMATION OVER HIGH-MOUNTAIN REGIONSJournal: International journal of ecosystems and ecology science (IJEES) (Vol.6, No. 3)
Publication Date: 2016-06-30
Authors : Cezar Kongoli; Sean Helfrich;
Page : 277-284
Keywords : Satellite Remote Sensing; Snow Depth; High-Mountain Regions; Optimal Interpolation; Climatology;
The objective of this paper is to present a blended snow depth analysis method applied to high-mountain regions. The blended analysis is running operationally at NOAA within a system called Interactive Multi-Sensor Snow and Ice Mapping System (IMS), generating daily snow depth output over Northern Hemisphere at 4-km resolution. Snow depth obtained from satellite passive microwave measurements are blended with snow depth measured at ground stations using a 2-Dimensional Optimal Interpolation (2D-OI) method. Unique to the production is that the analyst-derived data (snow depth and associated confidence values) are also blended into the analysis consistent with the 2D-OI method. Pseudo-observations of snow depth are also blended to improve analysis over high-elevation terrain where in-situ stations are sparse and satellite-derived estimates are less reliable. These are computed from temporally smoothed snow depth-elevation analytical expressions fitted to historical in-situ snow depth reports. Example applications of the analysis over high-mountain regions in US and elsewhere are also presented.
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