A novel algorithm for detection of precipitation in tropical regions using PMW radiometers

A novel algorithm for the detection of precipitation is described and tested. The algorithm is applicable to any modern passive microwave radiometer on board polar satellites independently of the observation geometry and channel frequency assortment. The algorithm is based on the application of canonical correlation analysis (CCA) and on the definition of a threshold to be applied to the resulting linear combination of the brightness temperatures in all available channels. The algorithm has been developed using a two-year dataset of co-located SSMIS and TRMM-PR measurements and AMSU-MHS and TRMM-PR measurements. This dataset was partitioned into 4 classes depending on the background surface emissivity (vegetated land, arid land, ocean, and coast) and the same procedure was applied for each surface class. In this paper we describe the procedure and we evaluate the results in comparison with many well-known algorithm for the detection of precipitation. The novel CCA algorithm show a small rate of false alarms and superior detection capability, it can efficiently detect (POD between 0.53 and 0.70) minimum rain rate varying from 0.15 mm/h (AMSU over ocean) to 0.40 (SSMIS over coast) with the remarkable result of 0.23 mm/h over arid land surface. The total amount of precipitation that the CCA algorithm can detect is around 80% over Ocean and Vegetated land and between 68 and 75% over coast and arid land.