| 基于多普勒天气雷达的冰雹云早期识别与预警方法研究 |
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| 引用本文： | 热苏力&#,阿不拉,牛生杰,张磊,王红岩. 基于多普勒天气雷达的冰雹云早期识别与预警方法研究[J]. 冰川冻土, 2017, 39(3): 641-650. DOI: 10.7522/j.issn.1000-0240.2017.0073 |
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| 作者姓名： | 热苏力&# 阿不拉 牛生杰 张磊 王红岩 |
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| 作者单位： | 1. 南京信息工程大学 大气物理学院, 江苏 南京 210044;2. 新疆维吾尔自治区人工影响天气办公室, 新疆 乌鲁木齐 830002;3. 阿克苏地区人工影响天气办公室, 新疆 阿克苏 843000 |
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| 基金项目： | 新疆气象局中亚大气科学研究基金项目“新疆重点防雹区冰雹天气特征及预报预警方法与应用研究”（CASS201709）资助 |
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| 摘 要： | 利用C波段新一代多普勒天气雷达监测资料和探空数据，对新疆南疆阿克苏地区西部绿洲2009-2015年28个降雹个例、32个对流风暴降雹单体进行分析，把发生在该区域的暴雹单体分为弱、中、强等三种类型，并综合分析不同强度降雹单体的“初生”、“跃增”和“酝酿”三个冰雹云生命史关键阶段的空间分布、演变规律以及不同温度层之间的关系，筛选出了能够提前识别各类冰雹云的雷达回波特征参量及指标阈值，并以此作为判识因子，建立了三种冰雹云提前识别及预警概念模型，同时对其识别能力进行验证，获得了三类冰雹云80%以上的识别准确率和合适的早期识别与有效作业指挥时间提前量，为该区域强冰雹云的早期识别与有效实施人工防雹作业决策提供科学依据。
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| 关 键 词： | 冰雹云 物理过程 雷达识别与预警 阿克苏西部绿洲 多普勒天气雷达 |
| 收稿时间： | 2017-01-12 |
| 修稿时间： | 2017-03-25 |
Study of early identifying and warning hail cloud by using Doppler Weather Radar |
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| Rasul Abla,NIU Shengjie,ZHANG Lei,WANG Hongyan. Study of early identifying and warning hail cloud by using Doppler Weather Radar[J]. Journal of Glaciology and Geocryology, 2017, 39(3): 641-650. DOI: 10.7522/j.issn.1000-0240.2017.0073 |
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| Authors: | Rasul Abla NIU Shengjie ZHANG Lei WANG Hongyan |
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| Affiliation: | 1. School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing 210044, China;2. Xinjiang Uygur Autonomous Region Weather Modification Office, Ürümqi 830002, China;3. Aksu Weather Modification Office, Aksu 843000, Xinjiang, China |
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| Abstract: | Using C Band data of new Doppler Weather Radar and sounding data, in this study, 28 hail cases and 32 convection storm monomers upon the western oasis of Aksu Prefecture in Xinjiang from 2009 through 2015 were analyzed. The hail clouds were divided into three types (weak, medium and strong) and the life history of each hailstorm cloud be divided into three key stages (primary, jump and incubation) and then the spatial distribution, evolution and the relationship between different temperature layers were analyzed comprehensively. As a result, the characteristic parameters of radar echo and index threshold were selected, which could be helpful for identifying hail cloud in advance. Three hail cloud advance identification and early warning concept models had been established. At the same time, their recognition ability was validated. The results show that using this method, more than 80% recognition accuracy and appropriate early identification and effective operation time could be obtained, which may provide a scientific basis for early identification of hailstorm and decision making for effective artificial hail work. |
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| Keywords: | hail cloud physical process radar identification and warning oasis in western Aksu Prefecture Doppler Weather Radar |
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