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タイトル
和文: 
英文:Data-driven non-deterministic forecasting of tropical cyclone rainfall 
著者
和文: HOKSON Jose Angelo Arocena, 鼎 信次郎.  
英文: J.A. Hokson, S. Kanae.  
言語 English 
掲載誌/書名
和文: 
英文: 
巻, 号, ページ        
出版年月 2023年7月13日 
出版者
和文: 
英文: 
会議名称
和文: 
英文:XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG 2023) 
開催地
和文:ベルリン 
英文:Berlin 
アブストラクト The Western Pacific Region is the most active tropical cyclone (TC) basin. On average, twenty-six tropical cyclones affect large populations in the region every year, including those of the Philippines, Vietnam, Taiwan, China, Japan, and Korea. This study presents a statistical methodology – involving fuzzy-c clustering – for predicting TC-induced rainfall in the region. The method relies on the idea that a TC’s rainfall can be predicted using the rainfall of past TCs. Track, mean sea level pressure, movement speed, etc. are utilized to determine which past TCs to consider. The results of prediction are represented as the probability of exceedance of selected rainfall thresholds. Such representation allows the inclusion of possible extreme events that a deterministic representation may miss.

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