A clustering-based method for identifying and tracking squall line
Abstract. The squall line is a type of convective system characterized by storm cells arranged in a line or band pattern, which is usually associated with disastrous weather. The identification and tracking of squall lines plays an important role in early warning of meteorological disasters. Based on weather radar data, a clustering-based identifying and tracking algorithm for squall lines is presented. Clustering analysis is designed to distinguish the strong echo area and estimate the feature value including reflectivity value, length, width, area, endpoints, central axes, and centroid. The clusters in the linearly arranged form are merged to improve the identification ability in the development stage of squall lines. The three-dimensional structure and movement tracking of the squall line are obtained using the centroid and velocity of the squall lines identified in a single layer. It is demonstrated that the method can effectively identify and track one or more squall lines over a weather radar scanning area. The result shows that the recognition accuracy rate in the single scan elevation of this method is 95.06 %, as well as a false positive rate of 3.17 %. This method improves the accuracy of squall line identification in the development stage of squall lines and works relatively efficiently even when high interference contaminates.
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