摘要
选择常规气象观测资料、NCEP分析资料以及雷达探测资料等相关资料分析2020年5月中旬山东省的一次强对流天气过程。结果显示:此次山东省强对流天气是由高空冷涡和地面气旋的共同影响形成的。5月17日晚上是本次强对流天气最旺盛的时期,此时山东处于低层低涡右侧,高空冷涡东南象限、地面气旋东北象限,具备非常好的抬升触发条件,促进了此次强对流天气的发生发展。在此次天气发生之前,青岛、徐州探空站对流有效位能(CAPE)等具备强对流天气出现的潜势;0℃与20℃高度以及厚度均非常适宜冰雹对流天气的出现。与此同时,低层暖湿、中层干冷的特性,环境垂直风切变较大,这些均能够预示雷电、大风、强降水等强对流天气的发生。雷达资料均能够反映出强对流天气的演变特点,对强对流天气的预报预警可以起到较好的指示作用。
This paper selects conventional meteorological observation data,NCEP analysis data,and radar detection data to analyze a severe convective weather process in Shandong Province in the middle of May 2020.The results show that the severe convective weather in Shandong Province was formed by the joint influence of high altitude cold vortices and surface cyclones.The night of May 17th was the most vigorous period of this severe convective weather.At this time,Shandong was located on the right side of the low-level low vortex,the southeast quadrant of the upper cold vortex,and the northeast quadrant of the surface cyclone,which had very good lifting triggering conditions,promoting the occurrence and development of this severe convective weather.Prior to this weather occurrence,the convective effective potential energy(CAPE)of the sounding stations in Qingdao and Xuzhou had the potential for strong convective weather;The height and thickness of 0℃and 20℃were very suitable for the occurrence of hail convective weather.At the same time,the characteristics of warm and wet in the lower layer,dry and cold in the middle layer,and large vertical wind shear in the environment can all predict the occurrence of severe convective weather such as lightning,strong winds,and heavy precipitation.Radar data can reflect the evolution characteristics of strong convective weather,and can play a good indicative role in the prediction and early warning of strong convective weather.
作者
仇彦辉
Qiu Yan-hui(Shandong Shidao Meteorological Station,Weihai,Shandong 264309)
出处
《农业灾害研究》
2023年第7期154-156,共3页
Journal of Agricultural Catastrophology
关键词
强对流天气
环流背景
单体风暴
Strong convective weather
Circulation background
Single storm
