Precipitation and Moisture Transport of the 2021 Shimokita Heavy Precipitation: A Transformed Extratropical Cyclone from Typhoon#9
-
- Akiyo Yatagai
- Graduate School of Science and Technology, Hirosaki University, Hirosaki 036-8561, Japan
-
- Shogo Saruta
- Faculty of Science and Technology, Hirosaki University, Hirosaki 036-8561, Japan
書誌事項
- 公開日
- 2024-01-11
- 資源種別
- journal article
- 権利情報
-
- https://creativecommons.org/licenses/by/4.0/
- DOI
-
- 10.3390/atmos15010094
- 公開者
- MDPI AG
説明
<jats:p>This study examines the heavy rainfall event that occurred in the Shimokita Peninsula, Japan, on 9–10 August 2021, resulting from an extra-tropical cyclone that developed from Typhoon#9 (EC9). The objective of this study is to elucidate the relationship between moisture transport and heavy rainfall and to verify the role of EC9. The authors created intensive hourly precipitation data over the Aomori Prefecture and analyzed them together with moisture fields. In most locations where the landslide disaster occurred, there were two precipitation peaks: at 9 UTC and 18 UTC on 9 August. The wind shear was strong from the lower to the upper troposphere with easterly winds in the lower troposphere and warm moist air from south for the first peak. A strong horizontal gradient of equivalent potential temperature, a northerly in lower troposphere, and moisture convergence over Shimokita Peninsula indicate the existence of the stationary front for the latter peak (18 UTC). The heavy precipitation and moisture convergence that caused the Shimokita event were identified by the stationary front of EC9 around the latter peak (15 UTC of 9th–06 UTC of 10 August). The precipitation distribution, which has a precipitation peak northeast of the EC center, is a typical typhoon-turned extratropical cyclone (EC) precipitation distribution.</jats:p>
収録刊行物
-
- Atmosphere
-
Atmosphere 15 (1), 94-, 2024-01-11
MDPI AG
- Tweet
詳細情報 詳細情報について
-
- CRID
- 1360025033658748288
-
- ISSN
- 20734433
-
- 資料種別
- journal article
-
- データソース種別
-
- Crossref
- KAKEN
- OpenAIRE

