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Given that precipitation is a major component of the earth’s water and energy cycles, reliable information on the monthly spatial distribution of precipitation is also crucial for climate science, climatological water-resource research studies, and for the evaluation of regional model simulations. In this paper, four satellite derived precipitation datasets: Climate Prediction Center MORPHING (CMORPH), Tropical Rainfall Measuring Mission (TRMM), the Precipitation Estimation Algorithm from Remotely-Sensed Information using an Artificial Neural Network (PERSIANN), and the global Satellite Mapping of Precipitation (GSMaP) are spatially analyzed and compared with the observed precipitation data provided by Bangladesh Meteorological Department (BMD). For this study, the different precipitations data sets are spatially analyzed from 2nd May 2019 to 4th May 2019 at the time of Cyclone “FANI”. It is found that the satellite derived precipitation datasets are reasonably matched with the observed but slightly different.

An Assessment of Spatial Distribution of Four Different Satellite-Derived Rainfall Estimations and Observed Precipitation over Bangladesh