Preprints
https://doi.org/10.5194/amt-2023-216
https://doi.org/10.5194/amt-2023-216
21 Dec 2023
 | 21 Dec 2023
Status: this preprint is currently under review for the journal AMT.

A clustering-based method for identifying and tracking squall line

Zhao Shi, Yuxiang Wen, and Jianxing He

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.

Zhao Shi, Yuxiang Wen, and Jianxing He

Status: open (extended)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2023-216', Anonymous Referee #2, 12 Jan 2024 reply
Zhao Shi, Yuxiang Wen, and Jianxing He
Zhao Shi, Yuxiang Wen, and Jianxing He

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Short summary
Squall line is a type of convective system. Squall lines are often associated with damaging weather, so the Identifying and tracking of squall lines plays an important role in early meteorological disaster warnings. A clustering-based method is proposed in this article. It can identify the squall lines in radar scanning range with a accuracy rate of 95.93 %. It can also provide the three-dimensional structure and movement tracking result of each squall lines.