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Notice on Academic Report by Dr.Kuo-lin Hsu University of California

Editor: 系统管理员 Date: 2017-06-06 Hits: 76

TitleQuantitative Precipitation Estimation using satellite and ground measurements



VenueAnzhong Building A3262

SpeakerProf. Kuo-lin Hsu

Presentation Abstract: 

Floods caused by extreme precipitation are the most frequent and widespread natural hazards. Statistics shows that more than hundred millions of people being affected by extreme events each year. Effective measurement of precipitation is a fundamental requirement for extreme weather monitoring. Recent developed remote sensing techniques enable precipitation measurement extendable to remote regions and ungauged basins.   In this presentation, the recent progress in global precipitation measurement system, developed at the Center for Hydrometeorology and Remote Sensing (CHRS), University of California Irvine (UCI), will be presented. Case studies will be demonstrated through precipitation estimation of heavy storm events causing extreme floods. Catchment scale streamflow simulation from extreme storm events will be discussed.


Prof. Kuo-lin Hsu is the associate director of Center for Hydrometeorology and Remote Sensing (CHRS) at University of California, Irvine. He graduated from University of Arizona for a Ph.D. degree. His research expertise includes remote sensing hydrology, hydrologic modeling, machine learning methods in hydrologic systems, hydrologic data assimilation and water resources systems planning, and et al. Dr. Hsu's current research activities are in the development of PERSIANN system to accurately determine the spatial and temporal distribution of precipitation using information from satellite and in situ (radar and gauge) observations. The classification of precipitation type (rain or snow) during the cold seasons and uncertainty analysis of model estimates are being investigated. He is also involved in the watershed hydrologic modeling using remote sensing data. He has authored more 80 peer-reviewed journal papers and 11 books.


Time10:00AM, June 11th, 2017       

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