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Science Rendezvous > 2009 Posters
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Atmospheric Corrections for Improved Satellite Passive Microwave Retrievals over the Tibetan Plateau

Matthew H. Savoie, James Wang, Mary Jo Brodzik, and Richard Armstrong

Since 1978, satellite passive microwave data have been used to derive hemispheric-scale snow cover maps. The seasonal and inter-annual variability of the microwave snow maps compares reasonably well with simultaneous maps of snow cover derived from satellite-based, visible-wavelength sensors. In general, the microwave-derived maps tend to underestimate snow extent during fall and early winter, due to a weak signal from shallow and intermittent snow cover. The Tibet Plateau is the only large geographic region where microwave retrievals tend to consistently overestimate snow-covered area compared to the visible data. The microwave overestimate is also clearly evident in multi-year monthly climatologies. Current microwave algorithms used to derive snow cover are based on ground or aircraft measurements that are later fine-tuned for satellite use. In this way, the algorithms have implicitly accounted for the presence of an atmosphere, because the brightness temperatures used in the algorithms have already passed through the atmosphere when measured at the satellite sensor. These methods are reasonably accurate when applied as a global algorithm to most snow-covered regions. However, a thinner atmosphere between the surface and satellite is likely the source of the consistent microwave snow extent overestimate on the Tibet Plateau, where elevations range from 3,200 to over 5,000 m.

We present a methodology to adjust satellite-based microwave brightness temperatures as a function of the observed surface elevation, thereby reducing the microwave snow cover overestimate on the Tibet Plateau. We include comparisons to snow maps derived from selected visible-wavelength products. We estimate that the adjusted microwave algorithm reduces the Tibet Plateau area of disagreement with the NOAA snow charts by approximately 17% (468,000 km2) over the snow season.