The improvement of TRaP by considering typhoon intensity variation

Yu Chun Chen, Gin Rong Liu, Yen Ju Chen

研究成果: 書貢獻/報告類型會議論文篇章同行評審

摘要

For years, the flash floods, mudflows and landslides brought by typhoons always cause severe loss of property and human life. For this reason, it is crucial to develop a more accurate and prompt typhoon rainfall prediction technique and thus can provide necessary rainfall potential information to the relevant disaster mitigation agencies. Kidder et al. (2005) developed the Tropical Rainfall Potential (TRaP) technique, which applied satellite-borne passive microwave radiometers, to retrieve a tropical cyclone's rainfall amount and predict its 24-h accumulated rainfall distribution. However, the effects of a tropical cyclone's rainband rotation and intensity variation were not considered in their method. To obtain a better approximation to the actual rainfall system, this study will improve the TRaP technique by considering those effects. In the typhoon intensity variation part, the method proposed by DeMaria (2006) was applied to predict the 6-h intensity change with GOES-9 and MTSAT satellites, and the result was further extended to predict the 24-h intensity change and accumulated rainfall. After comparing the predicted rainfall with the rain gauge data gathered from Taiwan's offshore small islands, it shows that the accuracy of the predicted accumulated rainfall could be improved significantly while considering the effects of rainband rotation and intensity variation.

原文???core.languages.en_GB???
主出版物標題32nd Asian Conference on Remote Sensing 2011, ACRS 2011
頁面198-202
頁數5
出版狀態已出版 - 2011
事件32nd Asian Conference on Remote Sensing 2011, ACRS 2011 - Tapei, Taiwan
持續時間: 3 10月 20117 10月 2011

出版系列

名字32nd Asian Conference on Remote Sensing 2011, ACRS 2011
1

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???32nd Asian Conference on Remote Sensing 2011, ACRS 2011
國家/地區Taiwan
城市Tapei
期間3/10/117/10/11

指紋

深入研究「The improvement of TRaP by considering typhoon intensity variation」主題。共同形成了獨特的指紋。

引用此