| 利用贝叶斯方法改进华南地区冰雹识别效果 |
| |
| 引用本文： | 李博勇,胡志群,郑佳锋,陈超. 利用贝叶斯方法改进华南地区冰雹识别效果[J]. 热带气象学报, 2021, 37(1): 112-125. DOI: 10.16032/j.issn.1004-4965.2021.011 |
| |
| 作者姓名： | 李博勇 胡志群 郑佳锋 陈超 |
| |
| 作者单位： | 成都信息工程大学大气科学学院,四川成都610225;中国气象科学研究院灾害天气国家重点实验室,北京100081;中国气象科学研究院灾害天气国家重点实验室,北京100081;成都信息工程大学大气科学学院,四川成都610225;广东省气象台,广东广州510641 |
| |
| 基金项目： | 国家重点研发计划（2019YFC1510304）；灾害天气国家重点实验室开放课题（2020LASW-B02）；广东省重点领域研发计划（2020B1111200001）共同资助 |
| |
| 摘 要： | 使用2019年广东S波段双偏振雷达观测的冰雹和非冰雹数据,统计得到冰雹和非冰雹的雷达反射率Z、差分反射率ZDR和相关系数CC先验概率密度分布,采用贝叶斯方法,根据雷达参量在冰雹和非冰雹条件下的概率以及冰雹和非冰雹的先验概率来确定某一距离库上所测到的(Z、ZDR、CC)所代表冰雹和非冰雹的概率,并用两个个例,比较分析了 ...
|
| 关 键 词： | 偏振雷达 贝叶斯方法 冰雹 相态识别 |
| 收稿时间： | 2020-04-20 |
USING BAYESIAN METHOD TO IMPROVE HAIL IDENTIFICATION IN SOUTH CHINA |
| |
| LI Bo-yong,HU Zhi-qun,ZHENG Jia-feng,CHEN Chao. USING BAYESIAN METHOD TO IMPROVE HAIL IDENTIFICATION IN SOUTH CHINA[J]. Journal of Tropical Meteorology, 2021, 37(1): 112-125. DOI: 10.16032/j.issn.1004-4965.2021.011 |
| |
| Authors: | LI Bo-yong HU Zhi-qun ZHENG Jia-feng CHEN Chao |
| |
| Affiliation: | 1.School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu 610225, China2.State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China3.Guangdong Meteorological Observatory, Guangzhou 510641, China |
| |
| Abstract: | This paper uses the hail and non-hail data observed by the Guangdong S-band dual-polarization radar in 2019 to statistically obtain the priori probability density distribution of hail and non-hail radar reflectivity Z, differential reflectivity ZDR and correlation coefficient CC. Based on the probability of radar parameters under hail and non-hail conditions and the prior probability of hail and non-hail, the present study uses the Bayesian method to determine the probability of hail and non-hail represented by (Z, ZDR, CC) measured at a certain range bin. Two cases are also used to compare and analyze the effects of WSR-88D hail recognition algorithm and the Bayesian method on hail recognition. The analysis shows that both methods can identify hail clouds more accurately, but the Bayesian method has a larger recognition range, which may be due to the rain mixed up with hail in southern China. |
| |
| Keywords: | polarimetric radar Bayesian method hail phase identification |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
| 点击此处可从《热带气象学报》浏览原始摘要信息 |
|
点击此处可从《热带气象学报》下载全文 |
|
