Correcting bias of satellite rainfall data using physical empirical model

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dc.contributor.authorGhaith Falah Ziarh
dc.contributor.authorShamsuddin Shahid
dc.contributor.authorTarmizi Bin Ismail
dc.contributor.authorMd Asaduzzaman
dc.contributor.authorAshraf Dewan
dc.coverage.publicationMalaysia
dc.date.accessioned2024-05-20T03:08:25Z
dc.date.available2024-05-20T03:08:25Z
dc.date.issued2021
dc.description.abstractThe 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.
dc.identifier.citationZiarh, 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.
dc.identifier.urihttps://repoemc.ukm.my/handle/123456789/1345
dc.language.isoen
dc.publisherElsevier
dc.publisher.alternativeAtmospheric Research
dc.subjectNear-real-time rainfall
dc.subjectSatellite precipitation
dc.subjectBias correction
dc.subjectEnsemble learning algorithm
dc.subjectPhysical-empirical model
dc.titleCorrecting bias of satellite rainfall data using physical empirical model
dc.typeJournal

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