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The worldwide network of in situ land surface temperatures archived in near-real time at the National Climatic Data Center (NCDC) has limited applications, since many areas are poorly represented or provide no observations. Satellite measurements offer a possible way to fill in the data voids and obtain a complete map of surface temperature over the entire globe. A method has been developed to calculate near-surface temperature using measurements from the Special Sensor Microwave/Imager (SSM/I). To accomplish this, the authors identify numerous surface types and make dynamic adjustments for variations in emissivity. Training datasets were used to define the relationship between the seven SSM/I channels and the near-surface temperature. For instance, liquid water on the surface reduces emissivity; therefore, the authors developed an adjustment to correct for this reduction. Other surface types (e.g., snow, ice, and deserts) as well as precipitation are identified, and numerous adjustments and/or filters were developed for these features. The article presents the results obtained from training datasets, as well as an independent case study, containing extreme conditions for deriving temperature from the SSM/I. The U.S. networks of first-order and cooperative stations, quality controlled by NCDC, serve as validation data. The correlation between satellite-derived and in situ temperatures during the independent case (''Blizzard of 1996'') was greater than 0.95, and the standard error was 28C. The authors also present SSM/I-derived snow cover and wetness maps from this 2-week period of the blizzard. A prototype for blending the satellite and in situ measurements into a single land surface temperature product is also presented.

Using the Special Sensor Microwave/Imager to Monitor Land Surface Temperatures, Wetness, and Snow Cover