基于雷达拼图CR产品四要素识别冰雹云的方法  

A method for identifying hail clouds based on four elements of radar mosaic CR products

作　　者：马中元 王金鑫 张林才 慕瑞琪 陈鲍发 郑媛媛 王立志[8] 段和平 黄志开 董玲 张祺杰 MA Zhongyuan;WANG Jinxin;ZHANG Lincai;MU Ruiqi;CHEN Baofa;ZHENG Yuanyuan;WANG Lizhi;DUAN Heping;HUANG Zhikai;DONG Ling;ZHANG Qijie(Jiangxi Institute of Meteorological Sciences,Nanchang 330096,China;Key Laboratory of Transportation Meteorology of China Meteorological Administration,Nanjing 210041,China;Nanchang Yunyiran Technology Co.,Ltd.,Nanchang 330000,China;School of Information Engineering,Nanchang University of Engineering,Nanchang 330099,China;Jiangsu Meteorological Observatory,Nanjing 210041,China;Jingdezhen Meteorological Bureau,Jingdezhen 333000,China;Nanjing Meteorological Science and Technology Innovation Research Institute,Nanjing 210041,China;Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,China;Jiangxi Climate Center,Nanchang 330096,China;Fuzhou Meteorological Bureau,Fuzhou 334400,China)

机构地区：[1]江西省气象科学研究所,江西南昌330096 [2]中国气象局交通气象重点开放实验室,江苏南京210041 [3]南昌云宜然科技有限公司,江西南昌330000 [4]南昌工程学院信息工程学院,江西南昌330099 [5]江苏省气象台,江苏南京210041 [6]景德镇市气象局,江西景德镇333000 [7]南京气象科技创新研究院,江苏南京210041 [8]中国科学院大气物理研究所,北京100029 [9]江西省气候中心,江西南昌330096 [10]抚州市气象局,江西抚州334400

出　　处：《大气科学学报》2024年第5期826-840,共15页Transactions of Atmospheric Sciences

基　　金：北极阁基金(BJG202208);国家重点研发计划课题(2022YFC3003904);中国科学院战略性先导科技专项(A类-XDA19040202);国家自然科学基金项目(41975001);江西省气象局重点科研项目(JX2022Z04);2022年江西省气象局面上项目(JX2022M03);景德镇市科技计划项目(2022SF003)。

摘　　要：为了提高简便、快捷、自动识别冰雹云的能力,利用雷达拼图组合反射率因子(Combined Reflectivity,CR)数据,在冰雹回波超级单体四要素特征分析的基础上,提出了简约快捷的自动识别冰雹云的方法。结果表明:聚类算法(Clustering Algorithm)、散点轮廓算法(Scatter Contour Algorithm)能够较好地识别出冰雹云回波中心强度和强回波面积;强回波梯度算法(Strong Echo Gradient Algorithm)、云砧回波算法(Cloud Anvil Echo Algorithm)计算快捷。雷达拼图CR、强回波面积(Strong Echo Area,SEA)、强回波梯度(Strong Echo Gradient,SEG)和云砧回波(Cloud Anvil Echo,CAE)四要素被用来确定回波与冰雹云的关系。江西冰雹大多数发生在超级单体(Supercell)中,当CR≥60 dBZ、SEA≥100 km^(2)、SEG≤8 km、CAE比值在1∶2~1∶3时,就可能发生冰雹;有些微型超级单体(Micro Supercell)在合适的天气背景和环境条件下,即使SEA=18 km^(2)也会发生冰雹。自动识别冰雹云的方法在2022、2023年各3次冰雹过程中得到实践验证,其识别出的冰雹云区域与冰雹实况区域吻合,但也存在10%~20%的空报率。本研究结果为简便、快捷、自动识别冰雹天气提供了有效依据。Radar is the most effective tool for detecting hail.In the 1960s and 1970s,the widespread use of rain measurement radar(e.g.,Danka 41 in the UK and domestic radars such as 711,713,etc.)enabled the identification of hail clouds through radar echo features like hook-shaped,finger-shaped,and V-shaped notches.The introduction of Doppler weather radar in the late 1980s and early 1990s provided more accurate data,including radial velocity,for effective hail cloud identification.However,four factors affect the accuracy of hail cloud recognition:1)single radar limitations such as detection range,distance attenuation,blind spots,and Earth’s curvature;2)the requirement for forecasters to possess high echo analysis skills;3)the variability of classic hail cloud characteristics with orientation,elevation,and distance;4)the limited number of PUP terminals for single radar use,insufficient for county-level forecasters.Radar mosaics can effectively compensate for some of these limitations,especially through web-based radar mosaic CR(Combined Reflectivity)products,which are accessible via computers,tablets,and mobile phones for simple and convenient operation.The radar mosaic CR product gathers data from multiple radars simultaneously(within±3 min).The blind spot of one radar is covered by another,and the inter-radar distance of 100—150 km is optimal for detection,minimizing issues related to angle blind spots,Earth’s curvature,and distance attenuation.The four key elements for identifying hail clouds on the CR product chart are:1)echo intensity of 60 dBZ and strong echo core≥65 dBZ,2)strong echo in horizontal and vertical areas,3)strong echo gradient of 30—60 dBZ,and 4)weak echo length formed by cloud anvils.For example,in Jiangxi,hail echo intensity is typically≥60 dBZ,with larger hail having strong echo nuclei above 65 dBZ.A strong echo area of 60 dBZ should be≥100 km^(2),although smaller hail may represent a smaller area.The vertical thickness of the strong echo(≥6 km)is also significant,though Jiangxi radar

关 键 词：冰雹云 聚类算法 散点轮廓算法 强回波梯度 云砧回波 

分 类 号：P412.25[天文地球—大气科学及气象学]