Correcting bias of satellite rainfall data using physical empirical model

The 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...

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Veröffentlicht in:	Atmospheric research Jg. 251; S. 105430
Hauptverfasser:	Ziarh, Ghaith Falah, Shahid, Shamsuddin, Ismail, Tarmizi Bin, Asaduzzaman, Md, Dewan, Ashraf
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.04.2021
Schlagworte:	algorithms Bias correction case studies empirical models Ensemble learning algorithm hydrometeorology Malaysia meteorological data Near-real-time rainfall Physical-empirical model rain Satellite precipitation satellites time series analysis topography wind speed Malaysia Ensemble learning algorithm Bias correction Satellite precipitation Near-real-time rainfall Physical-empirical model
ISSN:	0169-8095, 1873-2895
Online-Zugang:	Volltext
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