Toward investigating ultra dense and rapid lightning observation data assimilation for the torrential rainfall forecast
| Project/Area Number |
18K13614
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 17020:Atmospheric and hydrospheric sciences-related
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| Research Institution | Institute of Physical and Chemical Research |
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Principal Investigator |
Yasumitsu Maejima 国立研究開発法人理化学研究所, 計算科学研究センター, 特別研究員 (90509564)
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| Project Period (FY) |
2018-04-01 – 2023-03-31
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| Project Status |
Completed (Fiscal Year 2022)
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| Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2020: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2019: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2018: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
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| Keywords | データ同化 / メソ気象学 / 数値気象予報 / 気象予報 / 豪雨予測 / 気象災害 / 数値天気予報 / 局地的豪雨 / メソ気象 / 大気力学 / 気象学 |
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| Outline of Final Research Achievements |
The local torrential rainfall that often occur mainly during warm weather periods is a disasterable weather and are considered one of the most difficult weather phenomena to predict. In this project, we adopted "ultra high dense and frequent lightning position data" as the latest big data from meteorological observations, and assimilated it using the numerical weather forecast system "SCALE-LETKF" which developed at RIKEN, in order to dramatically improve the forecast accuracy of torrential rainfall. The research aimed to dramatically improve the accuracy of forecasting the severe weather. As part of the results of this project, we received the SOLA Paper Award from the Meteorological Society of Japan in 2022.
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| Academic Significance and Societal Importance of the Research Achievements |
我が国ではほぼ毎年のように「これまで経験したことないような雨」と形容されるような豪雨が発生する状況にある一方、その予測においては、短時間で急速に発達するという物理特性に加え、災害が発生しやすい地域で具体的にどの程度降水が起きるのか、定量的に示すこは難しいという課題があった。
本研究では、これまで数値天気予報で用いられていない「雷発光データ」の同化技術を確立したこと、それによる「豪雨予測改善の道筋を立てたこと」において学術的意義を持つ。さらに、本研究成果が現業の予報等に利活用されるこによって、豪雨による社会負担軽減へつながっていくことに、社会的意義を持つ。
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Report
(6 results)
Research Products
(41 results)
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[Presentation] Big Data Assimilation: Real-Time Workflow for 30-Second-Update Forecasting and Perspectives Toward DA-AI Integration2020
Author(s)
Takemasa Miyoshi, Takumi Honda, Marimo Ohhigashi, Shigenori Otsuka, Arata Amemiya, Yasumitsu Maejima, Shunji Kotsuki, Yoshihiro Ishikawa, Hiromu Seko, Yoshito Yoshizaki, Naonori Ueda, Hirofumi Tomita, Yutaka Ishikawa, Shinsuke Satoh, Tomoo Ushio, Kana Koike, Yasuhiko Nakada
Organizer
100th American Meteorological Society Annual Meeting
Related Report
Int'l Joint Research / Invited
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