Statistics-based optimization of the polarimetric radar hydrometeor classification algorithm and its application for a squall line in South China

Abstract

A modified hydrometeor classification algorithm (HCA) is developed in this study for Chinese polarimetric radars. This algorithm is based on the U.S. operational HCA. Meanwhile, the methodology of statistics-based optimization is proposed including calibration checking, datasets selection, membership functions modification, computation thresholds modification, and effect verification. Zhuhai radar, the first operational polarimetric radar in South China, applies these procedures. The systematic bias of calibration is corrected, the reliability of radar measurements deteriorates when the signal-to-noise ratio is low, and correlation coefficient within the melting layer is usually lower than that of the U.S. WSR-88D radar. Through modification based on statistical analysis of polarimetric variables, the localized HCA especially for Zhuhai is obtained, and it performs well over a one-month test through comparison with sounding and surface observations. The algorithm is then utilized for analysis of a squall line process on 11 May 2014 and is found to provide reasonable details with respect to horizontal and vertical structures, and the HCA results—especially in the mixed rain-hail region—can reflect the life cycle of the squall line. In addition, the kinematic and microphysical processes of cloud evolution and the differences between radar-detected hail and surface observations are also analyzed. The results of this study provide evidence for the improvement of this HCA developed specifically for China.

摘要

本文在美国业务的双偏振相态识别算法的基础上, 通过对雷达的定标分析和数据的统计, 修改了隶属函数参数和计算阈值, 得到了适用于中国双偏振雷达相态识别算法. 将该算法与我国第一部业务化的珠海双偏振雷达适配, 发现珠海雷达数据在低信噪比时可靠性会变差, 同时融化层中的相关系数小于美国 WSR-88D 双偏振雷达. 通过与地面和探空资料的对比, 验证了上述优化对于珠海雷达的合理性. 该算法应用于 2014 年 5 月 11 日的一次飑线过程分析中, 发现相态识别结果的水平和垂直结构均较为合理, 雨夹雹面积的变化与飑线的生命史对应. 此外, 飑线的演变微物理特征和雷达识别的冰雹及与地面观测的差异也在文中讨论. 研究结果为发展国内双偏振相态识别算法提供了依据.