Algorithm for the Identification and Tracking of Convective Cells Based on Constant and Adaptive Threshold Methods Using a New Cell-Merging and -Splitting Scheme

Abstract

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.