A Kalman Filter Approach to the Global Satellite Mapping of Precipitation (GSMaP) from Combined Passive Microwave and Infrared Radiometric Data

Abstract

  A system has been developed and implemented that integrates passive microwave radiometer data with infrared radiometer data in order to have high temporal (1 hour) and spatial (0.1 degree) resolution global precipitation estimates. The product (GSMaP_MVK) is produced based on a Kalman filter model that refines the precipitation rate propagated based on the atmospheric moving vector derived from two successive IR images. The proposed method was evaluated and compared with other high-resolution precipitation products and the ground-based data collected by the Automated Meteorological Data Acquisition System (AMeDAS) near Japan. It was clearly shown that the approach described in this paper performed better than without the Kalman filter, and the time series of the hourly global precipitation pattern demonstrated the potential capabilities for weather monitoring and typhoon tracking. The GSMaP_MVK product achieved a score comparable to the CMORPH and the 3B42RT products.