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| X 波段双极化雷达对云中水凝物粒子的相态识别 | |
| 引用本文： | 刘亚男,肖辉,姚振东,冯亮.X 波段双极化雷达对云中水凝物粒子的相态识别[J].气候与环境研究,2012,17(6):925-936. |
| 作者姓名： | 刘亚男 肖辉 姚振东 冯亮 |
| 作者单位： | 1. 成都信息工程学院电子工程学院,成都610025;中国科学院大气物理研究所云降水物理与强风暴实验室,北京100029;大连市气象装备保障中心,大连116001 2. 中国科学院大气物理研究所云降水物理与强风暴实验室,北京,100029 3. 成都信息工程学院电子工程学院,成都,610025 |
| 基金项目： | 国家自然科学基金项目40875080, 国家科技支撑计划项目2006BAC12B01-01, 中国气象局阳江国际探空仪比对辅助遥感试验课题, 国家公益性行业(气象)科研专项GYHY201006031 |
| 摘 要： | 人工影响天气研究需对云中降水粒子的相态和分布结构进行准确识别,以便提高人工影响天气作业效率.中国科学院大气物理研究所的车载X波段双极化雷达可提供与云中降水粒子大小、形状、相态等特征密切相关的4个极化参数:反射率因子、差分反射率、差分相移率、水平和垂直极化相关系数.利用这4个极化参数加上环境温度作为5个输入参量,建立了降水粒子相态模糊逻辑识别算法,识别的降水粒子有10种:毛毛雨、雨、湿霰、干霰、小雹、大雹、雨加雹、湿雪、干雪、冰晶.利用此雷达的实际观测资料,并与地面和飞机空中实测资料对照,对我国南、北方地区观测的降水天气过程进行分析,结果表明:建立的模糊逻辑算法对云内水凝物粒子的相态识别分类合理. |
| 关 键 词： | X波段双极化雷达 模糊逻辑 相态识别 应用试验 |
| 收稿时间： | 2012/4/23 0:00:00 |
| 修稿时间： | 2012/6/26 0:00:00 |
Analyses of Hydrometeor Identification Based on X-Band Polarimetric Radar |
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| LIU Yanan,XIAO Hui,YAO Zhendong and FENG Liang.Analyses of Hydrometeor Identification Based on X-Band Polarimetric Radar[J].Climatic and Environmental Research,2012,17(6):925-936. | |
| Authors: | LIU Yanan XIAO Hui YAO Zhendong and FENG Liang |
| Institution: | Chengdu University of Information Technology, Chengdu 610025;Laboratory of Cloud-Precipitation and Severe Storms, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029;Dalian Meteorological Equipment Support Center, Dalian 116001;Laboratory of Cloud-Precipitation and Severe Storms, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029;Chengdu University of Information Technology, Chengdu 610025;Laboratory of Cloud-Precipitation and Severe Storms, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029 |
| Abstract: | The study of weather modification must exactly identify the phases of cloud hydrometeor particles to improve the weather modification performance. The vehicle-borne X-band dual-polarization radar system set up by the Laboratory of Cloud-Precipitation and Severe Storms (LACS), Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences, can provide several dual-polarization radar observables, including radar reflectivity, differential reflectivity, specific differential propagation phase, and correlation coefficient, which are related to the sizes, shapes, and phases of hydrometeor particles. In this paper, the four polarimetric observables combined with environmental temperature are considered as five input parameters, and a fuzzy logic algorithm for hydrometeor particle identification is developed and implemented to discriminate ten different hydrometeor types including drizzle, rain, wet graupel, dry graupel, small hail, large hail, rain and hail mixture, wet snow, dry snow, and ice crystals. The identification algorithm is tested and estimated by using the radar data observed in southern and northern China, and comparing the results with the surface field observation and airborne instrument observations. The classification results indicate that the fuzzy logic algorithm is reasonable and practicable. |
| Keywords: | X-band dual-polarization radar Fuzzy logic Hydrometeor classification Compatibility test |
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