Using land surface microwave emissivities to isolate the signature of snow on different surface types

The objective of this paper is to better isolate the snow signature in microwave signals to be able to explore the ability of satellite microwave measurements to determine snowpack properties. The surface microwave effective emissivities used in this study are derived from SSM/I passive microwave observations by removing the contributions of the cloud and atmosphere and then separating out the surface temperature variations using ancillary atmospheric, cloud and surface data. The sensitivity of the effective emissivity to the presence/absence of snow is evaluated for the Northern Hemisphere. The effect of the presence of snow, the variation of land types, and temperature on the emissivities have been examined by observing the temporal and spatial variability of these measurements between 19 and 85 GHz over the Northern Hemisphere. The time-anomaly of differences between effective emissivity at 19 V and 85 V enabled the constant effects of land surface vegetation properties to be removed to isolate the snow signature. The resulting 12-year snow signal combined with skin temperature data can detect the existence of snow cover over the Northern Hemisphere on daily basis. The results of this method compared with the operational NOAA weekly snow cover maps agree at 90% of locations and times. Most of the disagreements could be explained by rapid evolution of snow emissivities associated with freeze-melt-refreeze cycles and precipitation (snowfall), and some of them by the space-time resolution differences of the microwave and operational snow cover determinations. These results compared with the NISE, NOAA IMS, CMC, and MODIS, and snow products agree within 78% to 92%.