Associated impact mechanism of heavy rain and floods in the middle and lower reaches of the Yangtze river basin based on ocean-atmosphere anomaly patterns

气候学 异常(物理) 环境科学 洪水(心理学) 大洪水 大气(单位) 流域 构造盆地 亚热带 地质学 地理 气象学 物理 地图学 考古 凝聚态物理 心理学 古生物学 渔业 心理治疗师 生物
作者
Shuxia Wang,Yisen Wang,Liping Zhang,Mingxiang Xu,Xiaomin Yao,Xin Wang
出处
期刊:Science of The Total Environment [Elsevier]
卷期号:946: 174067-174067
标识
DOI:10.1016/j.scitotenv.2024.174067
摘要

Heavy rainfall and flooding disasters are increasing due to global warming. A clear understanding of the mechanism of heavy rain and floods is the basic premise of disaster risk management. However, most previous studies emphasized more on the single anomalous signal from the average state in the whole season, which may neglect the combined influence of multiple signals in the ocean-atmosphere and differential characteristics of anomalous signals at different periods. Here, our study aimed to reveal the possible influence mechanism of heavy rain and floods in the middle and lower reaches of the Yangtze River Basin (MLRYRB) by systematically analyzing the monthly-scale and daily-scale ocean-atmosphere anomaly patterns in the preceding periods of heavy rainfall and flooding events. The results showed that heavy rainfall and flooding events were highly likely to occur in the region one month after El Niño decayed, with the flooding intensity in June having the negative correlation with the sea ice concentration anomaly in the Arctic with a lag of about 5 months (150 days). Besides, North Atlantic Oscillation, Western Pacific subtropical high, blocking, East Asian subtropical westerly jet, and the water vapor fluxes from the Arabian Sea and western Pacific Ocean could be used as the anomalous signals inducing heavy rain and floods. The daily-scale conceptual model inducing heavy rainfall and flooding events was built based on the patterns of all anomalous signals, which detailed the possible impact mechanism of heavy rain and floods in the region. By making targeted forecasts of anomalous signals and using this information in water resources planning and management based on climate mechanisms, it will have a significant impact on water management in the country.

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