Atmospheric Circulation Patterns Associated with the "2022.06" Extreme Flood in the Beijiang River Basin, China.
Published In: Journal of Tropical Meteorology, 2024, v. 30, n. 4. P. 444 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: ZHENG Jing; WANG Juan-huai; YANG Shou-mao 3 of 3
Abstract
The occurrence of most major basin-wide floods is closely related to persistent heavy rainfall (PHR). In June 2022, a PHR event that lasted twenty days hit the Beijiang River Basin (BRB) in South China. The record-breaking rainfall led to major floods and caused tremendous losses. This study first reviews the spatiotemporal distribution of the precipitation and the flooding process of this PHR event and then analyzes the atmospheric circulation patterns associated with the event based on the hourly reanalysis data from the European Centre for Medium-Range Weather Forecasts (ERA5). The results show that the establishment and stabilization of mid- to high-latitude blockings provided a favorable background for the "2022.06" PHR event in the BRB. The convergence of water vapor at the low level, the release of unstable energy, and the development of stronger vertical ascending movement provided the necessary dynamic conditions. The vertical circulation of water vapor was much stronger than that of climatology, while the vertical ascending movement was also more active in the BRB. The heavy rainfall belt in the BRB was formed in a region with apparently stronger divergence, which also coincided with regions of higher-than-normal updraft velocity and specific humidity. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Tropical Meteorology. 2024/12, Vol. 30, Issue 4, p444
- Document Type:Article
- Subject Area:Earth and Atmospheric Sciences
- Publication Date:2024
- ISSN:1006-8775
- DOI:10.3724/j.1006-8775.2024.043
- Accession Number:181687681
- Copyright Statement:Copyright of Journal of Tropical Meteorology is the property of Guangzhou Institute of Tropical & Oceanic Meteorology, China Meteorological Administration and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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