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风暴的多普勒雷达自动识别
引用本文:胡胜,顾松山,庄旭东,罗慧.风暴的多普勒雷达自动识别[J].气象学报,2006,64(6):796-808.
作者姓名:胡胜  顾松山  庄旭东  罗慧
作者单位:1. 南京信息工程大学,南京,210044;广州中心气象台,广州,510080
2. 南京信息工程大学,南京,210044
3. 广州中心气象台,广州,510080
4. 陕西省气象局,西安,710015
基金项目:广东省科技计划;广东省自然科学基金
摘    要:3种基于雷达的风暴自动识别方法:(1)美国WSR-88D Build 7.0风暴算法,它利用多个预设阈值来检验回波的强度和连续性,以构造具有三维连续结构的风暴,该方法在风暴合并、分裂以及多个单体相距较近时误差较大。(2)为美国WSR-88D Biuld 9.0风暴算法(B9SI),它用7个反射率因子识别阈值替代此前唯一的一个反射率因子阈值,增加了特征核抽取和相近单体处理技术,并保留远距离上的强的2D分量。该方法在面对成串或成簇多单体时,能够识别出多个单体核,并准确定位。B9SI没有考虑反射率因子纹理结构和空间梯度的变化,也没有利用径向速度资料,因此无法描述风暴对流的发展状况。(3)CSI方法,它在降低B9SI反射率因子识别阈值的基础上,利用模糊逻辑技术对B9SI输出结果和雷达基资料做进一步的处理,以计算描述风暴对流发展强弱的对流指数。CSI首先提取一组最能描述风暴对流性特征的物理量,包括反射率因子纹理结构、反射率因子空间变化率、垂直积分含水量和径向速度标准方差,并分配权重;其次,利用每一个物理量的统计结果,结合其物理意义,设计出相应的隶属函数,以计算风暴与该物理量描述的对流性特征相匹配的概率;最后对多个概率值进行加权平均即得对流指数。此外,计算了2004年8月11日发生在广州的超级单体演变过程中的对流指数,分析表明:对流指数两次加大对应了超级单体的合并增长和辐合增长过程;风暴最强盛时对流指数为0.744;随后对流指数减小,雷达观测到的最大反射率因子对应高度明显降低,地面上开始出现大范围的强降水。

关 键 词:风暴识别  核抽取  模糊逻辑技术  对流指数。
收稿时间:2005/7/27 0:00:00
修稿时间:2005年7月27日

AUTOMATIC IDENTIFICATION OF STORM CELLS USING DOPPLER RADARS
Hu Sheng,Gu Songshan,Zhuang Xudong,Luo Hui.AUTOMATIC IDENTIFICATION OF STORM CELLS USING DOPPLER RADARS[J].Acta Meteorologica Sinica,2006,64(6):796-808.
Authors:Hu Sheng  Gu Songshan  Zhuang Xudong  Luo Hui
Abstract:Three storm automatic identification algorithms for Doppler radar are discussed. The WSR-88D Build 7.0(B7SI) tests the intensity and continuity of the objective echoes by multiple-prescribed thresholds to build three-dimensional storms,and when storms are merging,splitting,or clustered closely,the detection errors become larger.The B9SI algorithm is part of the Build 9.0 Radar Products Generator of the WSR-88D system.It uses multiple thresholds of reflectivity,newly designs the techniques of cell nucleus extraction and close-storms processing,and therefore is capable of identifying embedded cells in multi-cellular storms.The strong area components at a long distance are saved as 2D storms.But,the B9SI can't give information on the convection strength of storm,because texture and gradient of reflectivity are not calculated and radial velocity data are not used.To overcome this limitation,the CSI algorithm is designed in this paper.By using the fuzzy logic technique,and under the condition that the levels of the seven reflectivity thresholds of B9SI are lowered,the CSI processes the radar base data and the output of B9SI to obtain the convection index of storm.Finally,the convection index is obtained from the weighted average of all the likelihood values.The CSI is verified with the case of a supercell occurred in Guangzhou on 11 August,2004.The computational and analysis results show that the two rises of convection index match well with a merging growth and strong convergent growth of the supercell,and the index is 0.744 when the supercell is strongest,and then decreases.Correspondingly,the height of the maximum reflectivity,detected by the radar also reduceds,and heavy rain also occurred in a large scale area.
Keywords:Storm identification  Nucleus extraction  Fuzzy logic technique  Convection index  
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