双偏振雷达水凝物分类算法优化及在雹暴云的应用分析

为提升我国多普勒双偏振雷达水凝物分类的应用水平,在美国强风暴实验室(NSSL)研发的水凝物分类算法(HCA)基础上,通过增加冰雹区与三体散射区水凝物类型的订正识别、选用数值模式温度分析场识别融化层、引入水凝物类型垂直分布限制条件等,建立了优化方法(HCA-Opt)。利用HCA-Opt分析了2021年7月9日济南市章丘区一次雹暴云的水凝物分布特征,对冰雹落区与水凝物分类结果进行比对检验,得到如下主要结论:HCA-Opt可以正确识别冰雹与三体散射区的水凝物类型,修正了HCA将其识别为地物的问题;HCA-Opt利用模式温度分析场可准确识别融化层高度,解决了强对流天气下HCA使用的融化层自动识别算法(MLDA)无法有效识别融化层的缺陷;与HCA相比,HCA-Opt识别的水凝物在垂直分布上更加合理。HCA-Opt给出的水凝物分类结果较好描述了雹暴初生、降雹不同阶段的水凝物空间分布,初步揭示了不同高度水凝物粒子相态转化特征。HCA-Opt识别的水凝物分类中,中(小)雨与霰的可信度最高,冰晶与湿雪的可信度较低,且容易与干雪混淆;总体而言,HCA-Opt提高了水凝物分类识别技巧,对冰雹预警和落区判别具...

The Hydrometeor Classification Optimum Algorithm for Polarimetric Radar and Its Application for the Hailstorm Cloud

To promote the application level of hydrometeor classification for Chinese Doppler polarimetric radar, based on the hydrometeor classification algorithm (HCA) developed by the National Severe Storm Laboratory (NSSL) of the United States, we design an optimum algorithm, named HCA-Opt, by adding the amendatory identification for the hydrometeor in hail and three-body scatter area, using the temperature of the numerical weather model analysis field to detect the location of the melting layer, and integrating restricted condition of vertical distribution for all hydrometeors. HCA-Opt is utilized to analyze the distribution characteristics of hydrometeor during a hailstorm cloud weather in Zhangqiu of Jinan City on 9 July 2021, and the location of the hail and the hydrometeor classification result are verified. The conclusions are as follows. The type of hydrometeor wrongly recognized as ground clutter by the HCA in the hail and the three-body scatter region can be correctly identified by the HCA-Opt. HCA-Opt can use the temperature from model analysis field to accurately identify the height of melting layer, solving the defect that the melting layer could not be detected by the algorithm in severe convective weather in HCA. Compared to HCA, the vertical distribution of hydrometeor identified by HCA-Opt is more reasonable. Besides, the classification result retrieved from the HCA-Opt can better describe the spatial distribution of hydrometeor at newborn and hailfalling stages of hailstorm, and initially reflect the characteristics of phase transformation at different heights. Through the verification, the reliability of the moderate (light) rain and graupel identified by the HCA-Opt is the highest, while that of the crystal and wet snow is lower, and easy to be mixed with the dry snow. Overall, the HCA-Opt can improve the skill of hydrometeor identification to certain extent, provide indicative information for warning and detecting the hailfalling area and have a good operational application prospect.