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Evaluation and assimilation of various satellite-derived rainfall products over India

Bushair, M. T., Kumar, Prashant, Gairola, R. M.
International journal of remote sensing 2019 v.40 no.14 pp. 5315-5338
algorithms, models, monsoon season, prediction, rain, remote sensing, satellites, temperature, tropics, weather forecasting, India
Accurate prediction of rainfall from the numerical weather prediction model is one of the major objectives over tropical regions. In this study, four different satellite-derived rainfall products (viz. merged-rainfall product from TRMM (Tropical Rainfall Measuring Mission) 3B42 and IMERG (Integrated Multi-satellitE Retrievals for GPM (Global Precipitation Measurement)), and Indian meteorological satellite INSAT-3D retrieved HEM (Hydro-Estimator Method) and IMSRA (INSAT Multi-Spectral Rainfall Algorithm) rainfall) are assimilated in the Weather Research and Forecasting (WRF) model using variational method. Before assimilation of satellite retrieved rainfall product in the WRF model, selected rainfall products are compared with ground rainfall from India Meteorological Department during Indian summer monsoon (June–September) 2015. Preliminary validation results show root-mean-square-difference (mean difference) of 18.1 (2.1), 21.3 (2.1), 15.4 (−0.72), and 14.4 (0.5) mm day⁻¹ in IMSRA, HEM, IMERG, and TRMM 3B42 rainfall, respectively. Further, the four-dimensional variational data assimilation method is used daily to assimilate selected rainfall products in the WRF model during the entire month of August 2015. Results suggest that assimilation of satellite rainfall improved the WRF model analyses and subsequent temperature and moisture forecasts. Moreover, rainfall prediction is also improved with the maximum positive impact from TRMM rainfall assimilation followed by IMERG rainfall assimilation. Similar nature of improvements is also seen in rainfall prediction when INSAT-3D retrieved rainfall products (HEM and IMSRA) are used for assimilation.