江苏X波段天气雷达组网自适应协同控制技术设计与实现  

Design and implementation of collaborative adaptive processing center for X-band weather radar network in Jiangsu Province

作　　者：徐芬[1,2] 王明筠 喜度[3] 周红根 张兴海 王永亮 XU Fen;WANG Mingjun;XI Du;ZHOU Honggen;ZHANG Xinghai;WANG Yongliang(Nanjing Innovation Institute for Atmospheric Sciences,Chinese Academy of Meteorological Sciences-Jiangsu Meteorological Service,Nanjing 210041,China;Jiangsu Key Laboratory of Severe Storm Disaster Risk/Key Laboratory of Transportation Meteorology of CMA,Nanjing 210041,China;Jiangsu Meteorological Observatory,Nanjing 210041,China;Jiangsu Meteorological Observation Center,Nanjing 210041,China;Nanjing NRIET Industrial Co.Ltd,Nanjing 210000,China)

机构地区：[1]南京气象科技创新研究院/中国气象局科学研究院/江苏省气象局,南京210041 [2]江苏省强对流灾害风险预警重点实验室/中国气象局交通气象重点开放实验室,南京210041 [3]江苏省气象台,南京210041 [4]江苏省气象探测中心,南京210041 [5]南京恩瑞特实业有限公司,南京210000

出　　处：《气象科学》2025年第1期26-39,共14页Journal of the Meteorological Sciences

基　　金：中国自然科学基金委员会气象联合基金资助项目(U2142203);中国气象科学研究院基本科研业务费专项资金(2021Z003,2024Z010)。

摘　　要：针对江苏强对流天气高发区域对流低层监测和精细化观测需求,本文利用江苏苏北X波段天气雷达网,设计并实现了针对气象目标的自适应协同控制技术,包括针对晴空、降水、风暴3种气象目标的识别技术及相应观测模式的制定,以及观测模式间自适应切换机制,建立了江苏X波段天气雷达组网自适应协同控制中心(Jiangsu Collaborative Adaptive Processing Center of X-Band Weather Radar Network,JSCAPC_XNET)。结果表明:JSCAPC_XNET有效填补了S波段天气雷达网局部低层探测盲区,把晴空、降水、风暴作为重点观测的气象目标满足了对全天候天气的观测需求,在协同观测网内,利用动态面积法实现的风暴体中心区识别技术、基于冰雹单体垂直结构概念模型设计的冰雹体识别技术以及适于多雷达识别中气旋的合并处理技术实现了对不同风暴单体识别和标注。针对气象目标的观测模式自适应切换机制保证了系统在3种模式间准确切换,提升了每部雷达的观测效能,实现了重点观测目标的精细化观测。试验期内观测到了包括强冰雹单体差分反射率(Z_(DR))柱、龙卷单体低层Z_(DR)弧、龙卷碎屑特征,以及直接反映龙卷可能及地的龙卷眼区低反射率因子区、下沉反射率因子核特征等,为提升小尺度极端天气监测和预警能力提供了观测手段。This study aims to improve the low-level monitoring and fine-scale observation for severe convective weather frequently occurred in Jiangsu Province.The X-band weather radar network located at northern Jiangsu was utilized to implement the adaptive collaborative control technology,including identification technology for clear sky,precipitation,and storms,and corresponding scanning strategies with an adaptive switching mechanism.The Jiangsu Collaborative Adaptive Processing Center for X-band Weather Radar Network(JSCAPC_XNET)was established for this purpose.Results show that JSCAPC_XNET effectively fills local low-level detection gaps in the S-band weather radar network.By focusing on clear sky,precipitation,and storms,the system demostrates comprehensive capabilities for all-weather observation requirements.Within the collaborative network,various storm cells can be distinguished and labeled using a dynamic area method,hailstorms can be detected using a vertical structure concept model,and mesocyclones can be identified through a combined processing technology that integrates multiple radars from the X-band weather radar network.The adaptive switching mechanism ensures precise transitions among the three observation modes.The adaptive cooperative observation mode enhances the observation efficiency of each radar and enables fine-scale monitoring of key targets.Based on observations from the JSCAPC_XNET during the experimental period,various characteristics related to severe thunderstorm were identified,such as strong hail Z_(DR) column,tornadic cell's low-level Z_(DR) arc,tornado debris,as well as the characteristics of low reflectivity regions and the descending of reflectivity core in the tornado eye region.These signatures potentially provide valuable insights for improving the monitoring and early warning capabilities for small-scale extreme weather in the future.

关 键 词：雷达组网 协同观测模式 自适应协同控制 Z_(DR)柱 下沉反射率因子核 龙卷眼区低反射率因子区 

分 类 号：P415.2[天文地球—大气科学及气象学]