A clustering-based method for identifying and tracking squall lines
Abstract The squall line is a type of convective system that is characterized by storm cells arranged in a line or band pattern and is usually associated with disastrous weather. The identification and tracking of squall lines thus play important roles in early warning systems for meteorological disasters. Here, a clustering-based identification and tracking algorithm for squall lines is presented based on weather radar data. A clustering analysis is designed to distinguish the strong echo area and estimate the feature value, including the reflectivity value, length, width, area, endpoints, central axes, and centroid. The linearly arranged clusters are merged to improve the identification of squall line development. The three-dimensional structure and movement tracking of the squall line are obtained using the centroid and velocity of the squall lines identified in each layer. The results demonstrate that the method can effectively identify and track one or more squall lines across the radar surveillance area. The results also show that the recognition accuracy rate for the single scan elevation of this method is 95.06 %, and the false-positive rate is 3.17 %. This method improves the accuracy of squall line identification in the development stage of squall lines and still works efficiently even when high interference contamination occurs.
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource
- Language
-
Englisch
- Bibliographic citation
-
A clustering-based method for identifying and tracking squall lines ; volume:17 ; number:13 ; year:2024 ; pages:4121-4135 ; extent:15
Atmospheric measurement techniques ; 17, Heft 13 (2024), 4121-4135 (gesamt 15)
- Creator
-
Shi, Zhao
Wen, Yuxiang
He, Jianxin
- DOI
-
10.5194/amt-17-4121-2024
- URN
-
urn:nbn:de:101:1-2408061230255.082238163740
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
14.08.2025, 11:02 AM CEST
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Shi, Zhao
- Wen, Yuxiang
- He, Jianxin
Other Objects (12)
A clustering-based method for identifying and tracking squall line
Clustering ensemble method
Kalman filter based method for tracking dynamic transmission line parameters
Identifying structural domains of proteins using clustering
AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number
Tracking Lines in Higher Order Tensor Fields : Tracking Lines in Higher Order Tensor Fields
Nuclear Norm Clustering: a promising alternative method for clustering tasks
HOT–Lines : Tracking Lines in Higher Order Tensor Fields
A line-based spectral clustering method for efficient planar structure extraction from LiDAR data
Distribution network line loss analysis method based on improved clustering algorithm and isolated forest algorithm
Self consistency grouping: a stringent clustering method
A parallel ADMM-based convex clustering method
A clustering-based method for identifying and tracking squall line
Clustering ensemble method
Kalman filter based method for tracking dynamic transmission line parameters
Identifying structural domains of proteins using clustering
AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number
Tracking Lines in Higher Order Tensor Fields : Tracking Lines in Higher Order Tensor Fields
Nuclear Norm Clustering: a promising alternative method for clustering tasks
HOT–Lines : Tracking Lines in Higher Order Tensor Fields
A line-based spectral clustering method for efficient planar structure extraction from LiDAR data
Distribution network line loss analysis method based on improved clustering algorithm and isolated forest algorithm
Self consistency grouping: a stringent clustering method
A parallel ADMM-based convex clustering method
A clustering-based method for identifying and tracking squall line
Clustering ensemble method
Kalman filter based method for tracking dynamic transmission line parameters
Identifying structural domains of proteins using clustering
AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number
Tracking Lines in Higher Order Tensor Fields : Tracking Lines in Higher Order Tensor Fields
Nuclear Norm Clustering: a promising alternative method for clustering tasks
HOT–Lines : Tracking Lines in Higher Order Tensor Fields
A line-based spectral clustering method for efficient planar structure extraction from LiDAR data
Distribution network line loss analysis method based on improved clustering algorithm and isolated forest algorithm
Self consistency grouping: a stringent clustering method