| Project/Area Number |
16K00526
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Environmental dynamic analysis
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| Research Institution | Japan, Meteorological Research Institute |
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Principal Investigator |
Murata Akihiko 気象庁気象研究所, 応用気象研究部, 室長 (10354474)
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| Project Period (FY) |
2016-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2018: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2017: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2016: ¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
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| Keywords | 地球温暖化 / 台風 / 降水 / 地域気候モデル / 統計分布 / 領域気候モデル / 気候変動 / 気象学 |
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| Outline of Final Research Achievements |
Future changes in precipitation associated with or without tropical cyclones were analyzed by using model data obtained from simulations of the nonhydrostatic regional climate model (NHRCM) under the present and a warmer climate (RCP8.5 scenario). It is found that precipitation associated with each tropical cyclone intensifies in the future climate although tropical cyclones approaching Japan decrease. Consequently, total precipitation associated with tropical cyclones does not change. However, frequency of extreme precipitation increases. Analyses using the cumulative distribution function of daily precipitation which is not associated with tropical cyclones reveal that frequency of heavy (light) precipitation decreases (increases) over the Japan Sea side of the northern Japan. In the Pacific side of the western Japan, the cumulative distribution function shifts toward the side of heavy precipitation.
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| Academic Significance and Societal Importance of the Research Achievements |
地球温暖化に伴う降水量変化の予測には不確実性が伴うが、本研究では台風の頻度、進路などによって不確実性が大きくなりがちな台風降水を分離することで、非台風降水の不確実性を低減することを試みた。その結果、台風降水を除くことで日降水量の統計分布の信頼度が高まるという知見が得られ、この手法が予測の不確実性を低減させるための新たな方策となることが期待される。また、台風降水についても高解像度の地域気候モデルによる予測結果を用いたことで、山岳を含む複雑な地形の多い日本列島に対応した、これまでにない時空間的に詳細な解析結果が得られた。
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