%0 Journal Article %T 列车效应诱发的扬州市特大暴雨过程分析——以2023年7月6~7日为例
Analysis of an Extremely Heavy Rainstorm Caused by Train Effect in Yangzhou—Taking 6~7 July 2023 as an Example %A 仇丹妮 %A 白杨 %A 钱勇 %A 夏露 %J Open Journal of Nature Science %P 349-358 %@ 2330-1732 %D 2025 %I Hans Publishing %R 10.12677/ojns.2025.132036 %X 2023年7月6~7日扬州地区特大暴雨过程具有覆盖范围广、短时雨强大、强降水持续时间长的特点。本文利用自动气象站资料、MICAPS气象数据资料、NCEP再分析资料、雷达回波资料等对此次降水过程进行诊断分析。结果表明：低纬强大稳定的副高与高纬稳定少动的冷涡对峙，加之低层范围宽、强度大的西南急流持续输送水汽，形成冷暖气流长久激烈交汇，是造成本次强降水的背景基础和必要条件。江淮西部有利的动力、热力、能量等中尺度对流触发条件和南北风场辐合，提供了列车效应有利的环境条件。暖区低质心高效降水和列车效应叠加，导致此次特大暴雨的发生。大尺度模式对特大暴雨多存在漏报，区域模式对降水落区等细节把握欠佳，需多关注潜势预报和新产品的应用，并提升中尺度分析能力从而提高极端降水的预报准确性。
The extremely heavy rainstorm process in Yangzhou on July 6~7, 2023 is characterized by wide coverage, strong short-term rain and long duration of heavy rainfall. Diagnosis and analysis of this precipitation process using automatic weather station data, MICAPS meteorological data, NCEP reanalysis data and radar echo data. The results indicate that the confrontation between a strong and stable subtropical high at low latitudes and a stable and less moving cold vortex at high latitudes, coupled with the continuous transport of water vapor by the southwest jet stream with a wide range and high intensity at low latitudes, formed a long-term and intense intersection of cold and warm air currents, which is the background basis and necessary condition for this heavy rainfall. The favorable mesoscale convective triggering conditions such as power, heat, and energy in the western Jianghuai region, as well as the convergence of the north-south wind field, provide favorable environmental conditions for the train effect. The superposition of the low centroid efficient precipitation in the warm region and the train effect led to the occurrence of the extremely heavy rainstorm. Large scale models often fail to report extremely heavy rainstorm, and regional models do not grasp details such as precipitation areas. More attention should be paid to potential forecasting and the application of new products, and the ability of mesoscale analysis should be improved to improve the accuracy of extreme precipitation prediction. %K 特大暴雨， %K 列车效应， %K 物理量诊断， %K 模式检验
Extremely Heavy Rainstorm %K Train Effect %K Physical Diagnosis %K Model Validation %U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=109604