Ghaith Falah ZiarhShamsuddin ShahidTarmizi Bin IsmailMd AsaduzzamanAshraf Dewan2024-05-202024-05-202021Ziarh, G. F., Shahid, S., Ismail, T. B., Asaduzzaman, M., & Dewan, A. (2021). Correcting bias of satellite rainfall data using physical empirical model. Atmospheric Research, 251, 105430.https://repoemc.ukm.my/handle/123456789/1345The provision of high resolution near real-time rainfall data has made satellite rainfall products very potential for monitoring hydrological hazards. However, a major challenge in their direct-use can be problematic due to measurement error. In this study, an attempt was made to correct the bias of Global Satellite Mapping of Precipitation near-real-time (GSMaP_NRT) product. Physical factors, including topography, season, windspeed and cloud types were accounted for correcting bias. Peninsular Malaysia was used as the case study area. Gridded rainfall, developed from 80 gauges for the period 2000-2018, was used along with physical factors in a two-stage procedure.enNear-real-time rainfallSatellite precipitationBias correctionEnsemble learning algorithmPhysical-empirical modelJournal