日本地球惑星科学連合2018年大会

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[EE] Eveningポスター発表

セッション記号 A (大気水圏科学) » A-HW 水文・陸水・地下水学・水環境

[A-HW20] 流域の物質輸送と栄養塩循環-人間活動および気候変動の影響-

2018年5月21日(月) 17:15 〜 18:30 ポスター会場 (幕張メッセ国際展示場 7ホール)

コンビーナ:齋藤 光代(岡山大学大学院環境生命科学研究科)、小野寺 真一(広島大学大学院総合科学研究科)、細野 高啓(熊本大学大学院先導機構、共同)、Adina Paytan(University of California Santa Cruz)

[AHW20-P02] Daily rainfall forecasting through an ensemble numerical weather prediction system with an AI-based integration strategy

*Ming-Chang Wu1 (1.Taiwan Typhoon and Flood Research Institute, National Applied Research Laboratories, Taiwan)

キーワード:Daily rainfall forecasting, Ensemble numerical weather predictions, AI-based integration strategy

Typhoon rainfall is one of the most important water resources in Taiwan. However, heavy typhoon rainfall often leads to serious disasters and results in loss of lives and properties. To overcome this problem, the control of water by reservoirs is the most common measure. When a typhoon approaches Taiwan, the major goal of reservoir operation is to control floods. But as the typhoon leaves, the goal is changed to store sufficient water. To achieve these two goals, accurate typhoon rainfall forecasts are always required as an important reference for making appropriate reservoir operation decisions. In this study, by means of an ensemble numerical weather prediction system in Taiwan, the ensemble forecasts of typhoon rainfall are obtained. Furthermore, an artificial intelligence (AI) based strategy is developed to effectively combine these ensemble forecasts for providing better typhoon rainfall forecasts. To verify the performance of the proposed strategy, actual application is conducted to provide typhoon rainfall forecasts with a lead time of 1 to 3 days. The results indicate that the proposed strategy provides more accurate forecasts as compared to the simple mean of all ensemble forecasts. In conclusion, through the proposed strategy as well as the ensemble numerical weather prediction system, improved typhoon rainfall forecasts are obtained. The improved rainfall forecasts are helpful for making appropriate reservoir operation decisions during typhoons.