| Project/Area Number |
18K03734
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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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| Review Section |
Basic Section 17020:Atmospheric and hydrospheric sciences-related
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| Research Institution | Hokkaido University |
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Principal Investigator |
Masaru Inatsu 北海道大学, 理学研究院, 教授 (80422450)
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| Co-Investigator(Kenkyū-buntansha) |
向川 均 京都大学, 理学研究科, 教授 (20261349)
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| Project Period (FY) |
2018-04-01 – 2022-03-31
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| Project Status |
Completed (Fiscal Year 2021)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2020: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2019: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2018: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
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| Keywords | 長期予報 / 確率過程 / 予測可能性 / ブロッキング / 確率微分方程式 / 自己組織化写像 / 大気ブロッキング |
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| Outline of Final Research Achievements |
This study developed the diagnosis of extratropical atmosphere predictability by interpreting it as the probabilistic processes that led to its chaotic variations. It was effective in the diagnosis to classify the atmosphere into several typical weather patterns by machine learning. This study applied it to reforecasts for past weathers. As a result, it was found that the weather patterns had a prediction limit of a couple of weeks. The prediction limit is short under the split jet stream regime, whereas it is long under the straight jet stream regime.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究の学術的意義はこれまで気象学に本格的に取り入れられることがなかった確率過程論や機械学習を用いた予測診断法を開発した点にある。社会的意義は、本研究によってさまざまな気象の確率分布を予測するモデルを構築する基礎が確立されることにある。異常気象を引き起こす大気ブロッキングが、大気状態として予測可能性が低いことが示された点は特筆する社会的意義である。
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