Abstract
Being largely dependent on agriculture, the overall development and water resource management of Bangladesh are greatly influenced by the accurate estimation of precipitation. Different satellite derived precipitation products, covering a large area, are very useful for rainfall estimation. In this study, three different satellite precipitation datasets namely Climate Prediction Center MORPHING (CMORPH), the global Satellite Mapping of Precipitation (GSMaP), and the Integrated Multi-satellitE Retrievals for GPM (IMERG) daily data are spatially analyzed and compared with the observed rainfall data from 20th May 2020 to 21st May 2020. It is observed that the satellite products matched well with the observed data set but the amount varied. Also, the spatial distribution of CMORPH and GSMaP with the observed precipitation is represented for 02 May 2019.
Highlights
In developing countries like Bangladesh, many human activities and socio-economic stability are strongly influenced by the availability and variability of precipitation (UN, 2009)
The purpose of this study was to assess the accuracy of the three satellite derived rainfall products Center MORPHING (CMORPH), Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) (IMERG), and global Satellite Mapping of Precipitation (GSMaP) for estimating the amount of precipitation during the time of cyclone “AMPHAN”
These products completely agree with the observed precipitation while in other cases they significantly vary
Summary
In developing countries like Bangladesh, many human activities and socio-economic stability are strongly influenced by the availability and variability of precipitation (UN, 2009). Rainfall data plays a very important role in weather forecasting and in various climate studies. With its good temporal and spatial coverage, rainfall data help to make decisions regarding hydrological matters as it is the main input in hydrological models. Precipitation is crucial in water resources planning and management, and directly links to agriculture, disaster mitigation, and preparedness.
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