首页> 外文期刊>ournal of the Meteorological Society of Japan >Algorithm for the Identification and Tracking of Convective Cells Based on Constant and Adaptive Threshold Methods Using a New Cell-Merging and -Splitting Scheme
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Algorithm for the Identification and Tracking of Convective Cells Based on Constant and Adaptive Threshold Methods Using a New Cell-Merging and -Splitting Scheme

机译:基于新的合并和分裂方案的恒定和自适应阈值方法的对流细胞识别和跟踪算法

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A new method for identifying and tracking convective cells is proposed for the statistical analysis of convective cells embedded within mesoscale convective systems using a two dimensional radar reflectivity dataset. The algorithm for the identification and tracking of convective cells determines convective regions with radar reflectivity exceeding a given constant threshold. The threshold value is gradually increased to detect a cell region with a single peak of reflectivity. The algorithm includes a new cell-merging and -splitting scheme that assumes the conservation of total area of convective cells and the maintenance of their relative locations when merging or splitting occurs, and is termed AITCC (Algorithm for the Identification and Tracking Convective Cells).The AITCC performance was evaluated in an analysis of 2004 non-severe convective cells (30-40 dBZ) and in 1268 linkages of convective cells (i.e., two successive observations of the same convective cell) observed within meso-β convective systems in the Meiyu frontal region. We demonstrated that the AITCC decreased the number of incorrect cell assignments, especially in situations where convective cells are located close together. AITCC showed promising performance (false-alarm-rate 10%) in the tracking of weak convective cells (30-40 dBZ) that seemed to be difficult for the previous tracking algorithms. AITCC is expected to enable us to calculate the statistical features of convective cells from their development to dissipation.
机译:提出了一种识别和跟踪对流细胞的新方法,用于使用二维雷达反射率数据集对中尺度对流系统中嵌入的对流细胞进行统计分析。对流单元的识别和跟踪算法确定雷达反射率超过给定常数阈值的对流区域。逐渐增加阈值以检测具有单个反射率峰值的单元区域。该算法包括一种新的细胞合并和分裂方案,该方案假设对流细胞的总面积保持不变,并且在合并或分裂发生时保持其相对位置,这种算法称为AITCC(识别和跟踪对流细胞的算法)。通过对2004年非严重对流细胞(30-40 dBZ)的分析和在美宇中β对流系统内对流细胞的1268个联系(即同一对流细胞的两次连续观测)评估了AITCC的性能。额叶区域。我们证明了AITCC减少了不正确的单元分配数量,特别是在对流单元靠在一起的情况下。 AITCC在跟踪弱对流细胞(30-40 dBZ)方面显示出令人鼓舞的性能(错误警报率<10%),这对于以前的跟踪算法而言似乎很困难。 AITCC有望使我们能够计算对流细胞从发育到耗散的统计特征。

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