| Project/Area Number |
17H02962
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Meteorology/Physical oceanography/Hydrology
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| Research Institution | Japan, Meteorological Research Institute |
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Principal Investigator |
Kawabata Takuya 気象庁気象研究所, 気象観測研究部, 室長 (80354447)
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| Co-Investigator(Kenkyū-buntansha) |
上野 玄太 統計数理研究所, モデリング研究系, 教授 (40370093)
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| Project Period (FY) |
2017-04-01 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2021)
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| Budget Amount *help |
¥17,290,000 (Direct Cost: ¥13,300,000、Indirect Cost: ¥3,990,000)
Fiscal Year 2020: ¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2019: ¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2018: ¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2017: ¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
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| Keywords | 積乱雲 / 粒子フィルタ / 非ガウス / カオス / データ同化 / 非ガウス性 / 気象学 / 観測演算子 / 確率密度 / 自然現象観測・予測 |
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| Outline of Final Research Achievements |
There is a hypothesis that the probablities of processes in cumulonimbus-develpments are non-Gaussian and then predictability becomes low. In order to investigate these processes, we developed a partcle filter with a nonhydrostatic model and an osevervation system simulation experiment. Moreover, we adapt the Baysian information criteria to determine Gaussian or non-Gaussian for each probability density. For the result, non-Gaussian processes in cumulonimbus-development was clarified and it is concluded that the source of these nonGaussian was the vertical winds. Furthermore, in oder to improve the filter in nonGaussian cases, we developed a PV inversion method and a data assimilation combined with a machine learning. Since it is important to understant the processes more in detail, th ESVD analysis was developed to investigate the initiation processes of convective phenomena.
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| Academic Significance and Societal Importance of the Research Achievements |
世界で初めて積乱雲を対象とするスケールの粒子フィルタを開発し、積乱雲発達過程における非ガウス性を調査した。気象現象がカオス的振る舞いを持つ事はよく知られているが、積乱雲におけるカオスの発生・発達について調査した研究はこれまでになく、本研究によって初めて明らかにされた。また非ガウス性を客観的に評価する手法を世界で初めて確立した。これらの成果により積乱雲に関わるカオスの研究が進み、その予測可能性の限界が明らかになっていくものと考えられる。
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