Remote sensing of precipitation over Indian land and oceanic regions by synergistic use of multisatellite sensors

In the present study, an attempt was made to estimate rainfall by synergistically analyzing collocated thermal infrared (TIR) brightness temperatures from Meteosat along with rainfall estimates from active microwave precipitation radar (PR) on the Tropical Rainfall Measuring Mission (TRMM) over Indian land and oceanic regions. In this study, we used broad and frequent TIR measurements from a geostationary satellite for rainfall estimation, calibrating them with sparse but more accurate PR rain rates. To make the algorithm robust, we used a two-step procedure. First, a cloud classification scheme was applied to TIR measurements using the 6.7 mu m water vapor channel and TIR radiances to delineate the rain-bearing clouds. Next, the concurrent TIR and PR observations were used to establish a regression relation between them. The relationship thus established was used to estimate rainfall from TIR measurements by applying it to rain-producing systems during southwest and northeast monsoons and tropical cyclones. Comparisons were made with TRMM-merged (3B42 V6) data, Global Precipitation Climatology Project (GPCP) monthly rain rate data, ground-based rain gauge observations from automatic weather stations, and Doppler weather radar over India. The results from combined infrared and microwave sensors were in very good agreement with the ground-based measurements, TRMM-3B42 V6, as well as GPCP.