Classification of Precipitation Types and Investigation of Their Physical Characteristics Using Three-Dimensional S-Band Dual-Polarization Radar Data - Choeng-Lyong Lee; Wonbae Bang; Chia-Lun Tsai; GyuWon Lee (Remote Sensing)
A novel classification algorithm for precipitation types (CP) was developed to address frequent misclassification issues between shallow convection and intense stratiform precipitation using existing methods and to enhance an understanding of their physical characteristics. Based on three-dimensional radar data and temperature fields, CP integrates three approaches: Storm Labeling in Three Dimensions (SLTD), a feature parameter-based algorithm (FP), and an advanced subcategorization method. The algorithm classifies precipitation into ten types: four non-precipitating, three stratiform, and three convective categories. CP was evaluated against traditional methods (SHY and FP) through both qualitative and quantitative analyses for mid-latitude warm-season systems. The CP method demonstrated improved performance, with higher skill scores (e.g., POD: 0.567–0.571) compared to SHY (0.349–0.364) and FP (0.455–0.470). Additionally, comparative analyses of vertical mean profiles of radar reflectivity, dynamical, and microphysical variables confirmed the enhanced capability of CP in distinguishing detailed precipitation structures.