Storm Tracking via Tree Structure Representation of Radar Data
Abstract
An algorithm for automatic storm identification, tracking, and nowcasting using tree structure representation of radar reflectivity images is proposed. The algorithm aims to track and nowcast different kinds of storm objects (stratiform regions, convective storms, and storm cells) simultaneously and to preserve their spatial relationships in the tracking and nowcasting processes. The algorithm applies a region tree structure to represent intensity regions and their spatial relationships in radar reflectivity images. Storm objects are identified by clustering regions within the region tree structure. Storm tracking is accomplished using an iterative region tree matching algorithm. Storm nowcasting applies the tree structure to the nowcasting of the internal structures of storm objects. Using eight cases with different storm types, a comparative evaluation with the enhanced Thunderstorm Identification, Tracking, Analysis, and Nowcasting (ETITAN) method and the Storm Cell Identification and Tracking (SCIT) method has shown that the proposed tree-based storm-tracking algorithm achieves better performance in storm tracking and nowcasting. The critical success index (CSI) value of storm association is 78.16% for the tree-based method, as compared with 74.88% for SCIT and 74.71% for ETITAN. The CSI value of an 18-min nowcast is 29.02% for the tree-based method, as compared with 24.98% for SCIT and 24.44% for ETITAN. The evaluation also shows that the tree-based method is able to nowcast the internal structure of storms and therefore produces small mean absolute errors (MAE).
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