Comparison of Two Convective/Stratiform Precipitation Classification Techniques: Radar Reflectivity Texture versus Drop Size Distribution–Based Approach

Abstract

AbstractC-band polarimetric radar measurements spanning two wet seasons are used to perform a critical evaluation of two algorithms for the classification of stratiform and convective precipitation. The first approach is based on the horizontal texture of the radar reflectivity field (two classes: stratiform, convective), and the second approach is based on the properties of the drop size distribution (DSD) parameters as derived from a set of polarimetric variables (three classes: stratiform, mixed, convective). To investigate how well those two methods compare quantitatively, probability density functions of reflectivity, rain rate, 5-dBZ echo top height, and DSD parameters (namely, the median volume diameter and the “generalized” intercept parameter) are built. The study found that while the two methods agree well on the identification of stratiform precipitation, large differences are obtained for convective rainfall. The texture-based approach seems to classify too many points as being of convective nature compared to the DSD-based method. Among the points that are classified as convective by the texture-based approach, 25% correspond to low concentration of relatively small particles associated with rain rates below 10 mm h−1. This large proportion of unrealistically low convective rain rates is not produced by the DSD-based approach, which only classifies 4% of the convective points with rain rates below 10 mm h−1. These points were found to be mainly isolated points embedded within stratiform precipitation and associated with low cloud-top height, suggesting a misclassification of the texture-based approach. Thus, to improve the statistics of the convective class, three modified equations of the peakedness criterion used in the radar-based algorithm are proposed to decrease the number of misclassified points.