基于双极化雷达的山东地区强对流过程分析
Analysis of Severe Convective Process in Shandong Province Based on Dual-Polarization Radar
DOI: 10.12677/CCRL.2022.115088, PDF,    科研立项经费支持
作者: 崔金梦:山东省气象防灾减灾重点实验室,山东 济南;山东省气象台,山东 济南
关键词: 双极化雷达山东地区强对流过程Dual-Polarization Radar Shandong Province Severe Convective Process
摘要: 为提高冷涡背景下强对流过程气象预报服务的精细化水平,利用MICAPS常规高空和地面观测资料,结合济南和青岛的双极化雷达资料等,对2020年5月16~18日山东大范围强对流天气过程进行了分析研究。结果表明,此次过程主要受冷涡旋转南下及大气强不稳定影响,地面辐合线持续稳定存在,回波不断发展,高反射率因子回波维持时间较长;从探空图来看,大尺度抬升条件非常有利于触发强对流天气,700 hPa以下上升速度达到−2~−3 m/s,并且在较强垂直风切变条件下对流组织性较强;雷达回波表明导致莱西大冰雹和11级阵风的是1个超级单体,由造成莱州强天气的单体发展增强而成,导致莱西出现大冰雹的强回波对应ZDR和CC较低值,近地面ZDR为0,CC为0.8~0.9。在今后的短临预报中要根据观测资料和雷达数据及时更新判断,努力筑牢气象防灾减灾第一道防线。
Abstract: In order to improve the refinement of meteorological forecasting services for the severe convective process in the context of cold vortex, the large-scale severe convective weather process in Shandong from May 16 to 18, 2020 was analyzed and studied by using MICAPS conventional high altitude and ground observation data, combined with dual-polarization radar data in Jinan and Qingdao. The results show that the process is mainly influenced by the cold vortex southward and strong air insta-bility, the stable presence of surface convergence lines, so the radar echoes keep developing and high reflectance factor echoes last for a long time. In terms of sounding maps, the large-scale lifting conditions are very favorable for triggering severe convective weather, with a rise rate of −2~−3 m/s below 700 hPa, with strong convective organization under stronger vertical wind shear conditions. Radar echoes indicate that what caused the large hail and 11th storm in Laixi was a super monomer, and the strong echoes that caused the large hail in Laixi correspond to lower ZDR and CC values, with near-surface ZDR of 0 and CC of 0.8~0.9. In short-time forecasts, we should update our judgments based on observations and radar data in a timely manner, and strive to build up the first line of defense for meteorological disaster prevention and mitigation.
文章引用:崔金梦. 基于双极化雷达的山东地区强对流过程分析[J]. 气候变化研究快报, 2022, 11(5): 844-852. https://doi.org/10.12677/CCRL.2022.115088

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