Affiliation:
1. Key Laboratory of Hydrometeorological Disaster Mechanism and Warning of Ministry of Water Resources Nanjing University of Information Science and Technology Nanjing China
2. Department of Civil Engineering, Faculty of Science and Engineering Swansea University Bay Campus Swansea UK
3. Anhui Key Laboratory of Atmospheric Science and Satellite Remote Sensing Anhui Institute of Meteorology Sciences Hefei China
4. School of Atmospheric Physics Nanjing University of Information Science and Technology Nanjing China
Abstract
AbstractAtmospheric rivers (ARs) are narrow, elongated belts of intense water vapor transport that often occur in mid‐latitude areas and are the primary drivers of heavy precipitation in these regions. This study investigates the impact of ARs on precipitation patterns in the Jianghuai River Basin during the Mei‐yu period. Focusing on a specific rainstorm event on June 27, 2022, we analyze atmospheric circulation, water vapor attributes, and transport trajectories. Three distinct classes of grids (Class A, significantly influenced by ARs; Class B, moderately affected; and Class C, untouched by ARs) are identified based on their response to ARs. Class A grids, located centrally, experience substantial precipitation, with a higher probability of rainstorm events. Class B grids, situated at a distance from ARs, exhibit moderate precipitation and a longer duration of rainy days. Class C grids, minimally affected by ARs, experience minimal precipitation with almost no chance of rainstorm events. The results from grid‐based analysis emphasize the localized influence of ARs, indicating a 8–30 times increase in precipitation intensity of Class A compared to Class C. The 23‐day Mei‐yu period is further categorized into AR days and non‐AR days, revealing that ARs amplify precipitation intensity by 2–5 times on average. Grid‐based and day‐based analyses provide complementary insights, with the former offering a broader spatial perspective and the latter emphasizing temporal distinctions. These findings underscore the nuanced influence of ARs on precipitation, emphasizing their role in extreme events and highlighting the importance of considering both spatial and temporal factors in understanding precipitation variability.
Funder
National Key Research and Development Program of China