暴雨回波的多尺度识别及其演变信息提取方法研究
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摘要
本文采用分层聚类的方法对暴雨回波进行了多尺度识别，分析了不同尺度回波的发展演变特征，考察了TREC和多尺度识别方法对暴雨1h累积雨量的预报能力和效果。论文的主要研究内容和研究成果如下：
1将层级的k-means聚类方法引入到雷达图像的分割，通过对广州飑线过程和温州卡努台风等过程的识别，结果表明：基于k-means的分层聚类方法能够实现暴雨回波的多尺度识别，对雷达连续时次图像的识别结果分析，证明了回波识别结果是稳定的，合理的。
2这种多尺度识别暴雨回波的方法对参数的变化不是很敏感，有利于将该方法适用于不同的天气情况。在暴雨的临近预报中可以根据预报时效的不同，选择不同的尺度来识别云团。对飑线过程的临近预报，预报1h累计雨量较TREC外推的1h累计雨量更接近于雷达反演的1h累计雨量。
3对飑线和台风过程进行了暴雨回波的多尺度识别，分析了不同尺度暴雨回波的发展演变特征。结果表明：较小尺度回波的生命史一般在数十分钟，时空变化比较快，易发生合并与分裂，对其外推预测的难度较大，较大尺度回波的生命史一般在数小时，发展演变较慢，易于识别、外推。
4通过选择合适的参数，利用TREC方法能够跟踪暴雨雨带的移动，对移动矢量场进行连续性检查，可以有效去除杂乱的移动矢量。通过外推，可以对暴雨进行临近预报，预报的准确性随预报时效的增加而降低。
5利用温州单站雷达对卡努台风的观测资料、福建区域组网雷达对热带风暴碧利斯的观测资料，证明了TREC方法对螺旋雨带的跟踪能力，移动矢量场能够很好地反映雨带的旋转特征和台风眼的位置，螺旋雨带的移动类似于兰金的中尺度气旋模式，在台风眼的位置，移动速度为零，在一定的半径范围内，移动速度随着半径的增加而递增。由于雨带的旋转移动，采用拉格朗日积分方法的预报结果好于线性外推的预报结果。
6将聚类方法识别暴雨回波与TREC跟踪技术相结合，进行暴雨的临近预报，并对TREC技术和聚类技术外推预报结果的误差进行了分析，探讨了位置误差和强度误差对预报误差的影响。
A multi-scale rainstorm echoes identification method is developed by using hierarchical clustering algorithm, and echoes evolution feature with different scales are analysed. The quality of 1h accumulative rainfall amount both using the multi-scale and tracking radar echoes by correlation (TREC) have been tested using real radar retrieval.
1 Hierarchical k-means clustering method has been applied to segment radar image ,which has been investigated by squall line rainstorm observed by the GuangZhou radar and typhoon KANU rainstorm observed by the WenZhou radar. It is found that hierarchical k-means clustering method can realize multi-scale storm identification, and the result of identification is steady and reasonable by analyzing the result of segmenting consecutive CAPPI.
2 The multi-scale identification method is insensitive to varying parameter, which is favorable for applying the technique to different weather system. The different scale convective systems can be identified, tracked and extrapolated with different lead time of forecasting . 1h accumulative rainfall amount extrapolating with clustering identification and different trends are slightly closer to that retrieving by radar observation than that extrapolating with TREC technique and linear trend.
3 The evolution character of different scale rainfall echoes has been studying based on multi-scale identification of squall line and typhoon rainstorm. It has been revealed that small scale convective cells with mean lifetimes of tens of minutes, large spatio-temporal variation, feeblish regularity is difficult to nowcasting, while larger scale rainfall echoes with mean lifetimes of many hours, better regularity and obvious evolution stages has a certain extent predictability.
4 The TREC have method the capability of tracking rain-band with appropriate parameter. The "noisiness" of TREC vector can be reduced by checking the consistency of each motion vector. The forecast radar reflectivity pattern is obtained by extrapolation based on smoothed TREC vectors.
5 The TREC technique is applied to typhoon KANU observed by the WenZhou single radar and tropic storm BILIS observed by FuJian radar netting . The studies have clearly demonstrated the ability of the TREC technique tracking rotating rain-band on cyclic character of the TREC vectors and position of typhoon eye. The motion vectors of typhoon rain-band are models by a Rankine combined vortex containing a core region where velocity increase out to a ring of maximum velocity. The forecast results extrapolating by temporal integration of the two-time-level semi-Lagrangian scheme excel that extrapolating linearly.
6 Rainfall echoes are extrapolated by combining cluster identification method with TREC tracking technology. The position error and intensity error are discussed by analyzing forecast error using both clustering and TREC technique.
1将层级的k-means聚类方法引入到雷达图像的分割，通过对广州飑线过程和温州卡努台风等过程的识别，结果表明：基于k-means的分层聚类方法能够实现暴雨回波的多尺度识别，对雷达连续时次图像的识别结果分析，证明了回波识别结果是稳定的，合理的。
2这种多尺度识别暴雨回波的方法对参数的变化不是很敏感，有利于将该方法适用于不同的天气情况。在暴雨的临近预报中可以根据预报时效的不同，选择不同的尺度来识别云团。对飑线过程的临近预报，预报1h累计雨量较TREC外推的1h累计雨量更接近于雷达反演的1h累计雨量。
3对飑线和台风过程进行了暴雨回波的多尺度识别，分析了不同尺度暴雨回波的发展演变特征。结果表明：较小尺度回波的生命史一般在数十分钟，时空变化比较快，易发生合并与分裂，对其外推预测的难度较大，较大尺度回波的生命史一般在数小时，发展演变较慢，易于识别、外推。
4通过选择合适的参数，利用TREC方法能够跟踪暴雨雨带的移动，对移动矢量场进行连续性检查，可以有效去除杂乱的移动矢量。通过外推，可以对暴雨进行临近预报，预报的准确性随预报时效的增加而降低。
5利用温州单站雷达对卡努台风的观测资料、福建区域组网雷达对热带风暴碧利斯的观测资料，证明了TREC方法对螺旋雨带的跟踪能力，移动矢量场能够很好地反映雨带的旋转特征和台风眼的位置，螺旋雨带的移动类似于兰金的中尺度气旋模式，在台风眼的位置，移动速度为零，在一定的半径范围内，移动速度随着半径的增加而递增。由于雨带的旋转移动，采用拉格朗日积分方法的预报结果好于线性外推的预报结果。
6将聚类方法识别暴雨回波与TREC跟踪技术相结合，进行暴雨的临近预报，并对TREC技术和聚类技术外推预报结果的误差进行了分析，探讨了位置误差和强度误差对预报误差的影响。
A multi-scale rainstorm echoes identification method is developed by using hierarchical clustering algorithm, and echoes evolution feature with different scales are analysed. The quality of 1h accumulative rainfall amount both using the multi-scale and tracking radar echoes by correlation (TREC) have been tested using real radar retrieval.
1 Hierarchical k-means clustering method has been applied to segment radar image ,which has been investigated by squall line rainstorm observed by the GuangZhou radar and typhoon KANU rainstorm observed by the WenZhou radar. It is found that hierarchical k-means clustering method can realize multi-scale storm identification, and the result of identification is steady and reasonable by analyzing the result of segmenting consecutive CAPPI.
2 The multi-scale identification method is insensitive to varying parameter, which is favorable for applying the technique to different weather system. The different scale convective systems can be identified, tracked and extrapolated with different lead time of forecasting . 1h accumulative rainfall amount extrapolating with clustering identification and different trends are slightly closer to that retrieving by radar observation than that extrapolating with TREC technique and linear trend.
3 The evolution character of different scale rainfall echoes has been studying based on multi-scale identification of squall line and typhoon rainstorm. It has been revealed that small scale convective cells with mean lifetimes of tens of minutes, large spatio-temporal variation, feeblish regularity is difficult to nowcasting, while larger scale rainfall echoes with mean lifetimes of many hours, better regularity and obvious evolution stages has a certain extent predictability.
4 The TREC have method the capability of tracking rain-band with appropriate parameter. The "noisiness" of TREC vector can be reduced by checking the consistency of each motion vector. The forecast radar reflectivity pattern is obtained by extrapolation based on smoothed TREC vectors.
5 The TREC technique is applied to typhoon KANU observed by the WenZhou single radar and tropic storm BILIS observed by FuJian radar netting . The studies have clearly demonstrated the ability of the TREC technique tracking rotating rain-band on cyclic character of the TREC vectors and position of typhoon eye. The motion vectors of typhoon rain-band are models by a Rankine combined vortex containing a core region where velocity increase out to a ring of maximum velocity. The forecast results extrapolating by temporal integration of the two-time-level semi-Lagrangian scheme excel that extrapolating linearly.
6 Rainfall echoes are extrapolated by combining cluster identification method with TREC tracking technology. The position error and intensity error are discussed by analyzing forecast error using both clustering and TREC technique.
引文
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7 Wilson J W, Crook N A, Mueller C K, et al. Nowcasfing thunderstorm: A status report. Bull Amer Meteor Soc, 1998, 79: 2079--2099
8 Dixon M and Wiener G. TITAN: Thunderstorm Indetification, Tracking, Analysis,and Nowcasting. J. Atmos. Oceanic Technol, 1993, 8: 467-476
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