Classification of snow cover and precipitation using SSM/I measurements: case studies

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Abstract
A satellite-based method for global classification of precipitation and snow cover in the microwave portion of the electromagnetic spectrum has been developed using three channels of data from the Special Sensor Microwave/ Imager (SSM/I). A decision tree algorithm is developed for the global classification of snow cover and precipitation over large geographical regions. Potential problem areas like desert regions are also identified in the decision-tree process. Oier 40 case studies of SSM/I data over small geographical regions (i.e., the Gulf Coast of the United States, African desert, etc.) were analysed to develop and test these algorithms. Case studies involving Manually Digitized Radar (MDR)data, NOAA weekly snow cover charts and surface weather charts were used to validate the algorithm.