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Ushio, T., Sasashige, K., Kubota, T., Shige, S., Okamoto, K., Aonashi, K., Inoue, T., Takahashi, N., Iguchi, T., Kachi, M., Oki, R., Morimoto, T., & Kawasaki, Z.-I. (2009). A Kalman Filter Approach to the Global Satellite Mapping of Precipitation (GSMaP) from Combined Passive Microwave and Infrared Radiometric Data. Journal of the Meteorological Society of Japan A, 87, 137-151.
https://doi.org/10.2151/jmsj.87A.137

has been cited by the following article:

• TITLE: Comparison of Satellite Derived Rainfall Estimations: CMORPH, IMERG and GSMaP with Observed Precipitation

  AUTHORS: Deepa Roy, Sharmin Banu

  KEYWORDS: CMORPH, IMERG, GSMaP

  JOURNAL NAME: American Journal of Climate Change, Vol.10 No.4, November 29, 2021

  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.