Development of cloud radar assimilation methods for local heavy rain prediction
| Project/Area Number |
18K13841
|
|---|
| Research Category |
Grant-in-Aid for Early-Career Scientists
|
| Allocation Type | Multi-year Fund |
|---|
| Review Section |
Basic Section 22040:Hydroengineering-related
|
|---|
| Research Institution | National Research Institute for Earth Science and Disaster Prevention |
|---|
Principal Investigator |
Kato Ryohei 国立研究開発法人防災科学技術研究所, 水・土砂防災研究部門, 主任研究員 (70811868)
|
|---|
| Project Period (FY) |
2018-04-01 – 2022-03-31
|
| Project Status |
Completed (Fiscal Year 2021)
|
| Budget Amount *help |
¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
Fiscal Year 2020: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2019: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2018: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
|
|---|
| Keywords | 雲レーダー / データ同化 / 数値予測 / 局地的大雨 / ナウキャスト |
|---|
| Outline of Final Research Achievements |
This study aimed to improve the accuracy of very- short-range numerical forecasts for local heavy rain by developing an assimilation method of cloud radar that can capture cloud droplets before raindrops form. By assimilating cloud radar data from special observations that succeeded in capturing cumulonimbus clouds that caused local heavy rain at a very high frequency of every minute, using a method called nudging, and improving the initial value of a numerical weather prediction model, we succeeded in predicting local heavy rain from the stage before rainfall started, which has been difficult with conventional extrapolation-based nowcasting.
|
| Academic Significance and Societal Importance of the Research Achievements |
「ゲリラ豪雨」とも呼ばれる局地的大雨は、河川の急な増水や道路の浸水などを通じて時には人的被害をも引き起こすため、その予測手法の開発は重要な研究課題である。本研究は、雲レーダー同化により雨が降る前の段階から局地的大雨の予測に成功した世界で初めての研究だといえる。本手法を実用化に向けて高度化し、予測情報を危険な場所にいる方々にいち早く伝えることで、「ゲリラ豪雨」による被害が軽減されることが期待される。
|
Report
(5 results)
Research Products
(7 results)
