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作 者:何建新[1,2] 李学华[1,2] 徐梓欣 杨玲[1,2] 雷波 王文明 He Jianxin;Li Xuehua;Xu Zixin;Yang Ling;Lei Bo;Wang Wenming(Chengdu University of Information and Technology,Chengdu 610225;Key Laboratory of Atmospheric Sounding,ChinaMeteorological Administration,Chengdu 610225;Chengdu YuanWang Science and Technology Co.,Ltd,Chengdu 610041)
机构地区:[1]成都信息工程大学电子工程学院,成都610225 [2]中国气象局大气探测重点开放实验室,成都610225 [3]成都远望科技有限责任公司,成都610041
出 处:《气象科技进展》2021年第4期82-88,共7页Advances in Meteorological Science and Technology
基 金:科技部国家重点研发计划项目(SQ2017YFC150152);四川省教育厅重点(2018Z088)。
摘 要:基于成都X波段天气雷达网络,设计了一种快速体积扫描+多RHI扫描的雷达组网扫描策略,通过优化体扫层数和雷达配置参数,增加对流单体中心RHI扫描,可获取低层空间、高时间分辨率和精细降水垂直结构;设计了一种重点区域识别、优先级计算和雷达任务智能调度的组网协同控制流程,并针对重点区域的天气过程识别问题,提出了一种基于神经网络的强对流识别算法和基于非监督学习聚类算法的强对流天气回波自动识别和定位方法。通过雷达试验表明,该组网策略和协同控制方法能有效获取强对流天气过程的垂直精细结构。Based on the X band weather radar network in Chengdu,a radar network scanning strategy of fast-speed volume scanning adding with multiple RHI scanning is designed.Through optimizing the volume scanning layers and radar configuration parameters and increasing the RHI scanning to the convective cell center,It can be used in the radar network to get the detailed precipitation structure with high time resolution,especially in low boundary layer.A flow of radar network cooperative control is also designed based on the technology of key area identification,priority calculation and intelligent scheduling of radar tasks.A strong convection identification algorithm based on neural network,and an unsupervised Learning clustering algorithm for automatic recognition and location of severe convective weather echoes are developed for key area identification.Radar experiments show that the scanning strategy and cooperative control method can obtain the detailed vertical structure of strong convective weather.
分 类 号:P412.25[天文地球—大气科学及气象学]
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