| 一种雷达回波飑线智能识别的方法 |
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| 引用本文： | 王兴,王坚红,卞浩瑄,张海阳.一种雷达回波飑线智能识别的方法[J].热带气象学报,2020,36(3):317-327. |
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| 作者姓名： | 王兴 王坚红 卞浩瑄 张海阳 |
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| 作者单位： | 1.南京信息工程大学大气科学与环境气象国家级实验教学示范中心，江苏 南京 210044 |
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| 基金项目： | 国家自然科学基金项目41805033国家自然科学基金面上项目41276033中国气象局软科学研究项目2019ZZXM45江苏省产学研合作项目BY2018010 |
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| 摘 要： | 提出一种雷达回波图像中飑线特征自动识别的方法。以多普勒天气雷达探测资料为主要数据源，对雷达探测到的基本反射率的空间分布和强度进行分析，通过数值预处理、高通滤波、二值化降噪、图像特征提取、目标物的中轴线提取，以及飑线形态分析等一系列步骤，实现对雷达飑线特征的智能识别。克服了回波高值区域不连通、碎块化对飑线自动识别造成的困难。通过4次强对流天气个例检验，飑线自动识别的准确率达到75%左右，尤其对呈现直线或劣弧状，且边界清晰的高值回波区，具有更高的识别成功率。该方法将以往需要由气象专业人员主观分析、判读雷达回波图像的工作自动化、客观化，可提高飑线识别、强对流天气预警相关业务的准确性和时效性。
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| 关 键 词： | 天气学 飑线 天气雷达 雷达回波 飑线特征识别 |
| 收稿时间： | 2019-10-14 |
A METHOD FOR INTELLIGENT RECOGNITION OF RADAR SQUALL LINE |
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| WANG Xing,WANG Jian-hong,BIAN Hao-xuan,ZHANG Hai-yang.A METHOD FOR INTELLIGENT RECOGNITION OF RADAR SQUALL LINE[J].Journal of Tropical Meteorology,2020,36(3):317-327. |
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| Authors: | WANG Xing WANG Jian-hong BIAN Hao-xuan ZHANG Hai-yang |
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| Institution: | 1.National Demonstration Center for Experimental Atmospheric Science and Environmental Meteorology Education, Nanjing University of Information Science & Technology, Nanjing 210044, China2.Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China3.School of Atmospheric Science, Nanjing University of Information Science & Technology, Nanjing 210044, China |
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| Abstract: | In this paper, we propose an intelligent and early warning recognition method of squall line characteristics in weather radar images. Doppler weather radar data is used as the main data to analyze the spatial distribution and intensity of the base reflectivity detected by radar. Through data preprocessing, high-pass filtering, binarization noise reduction, image feature extraction, central axis extraction of target, and morphological analysis of the squall line, intelligent recognition and early warning of radar squall line characteristics is realized. The method overcomes the difficulty caused by the disconnection of the high-value area of the echo and the automatic identification of the squall line by the fragmentation. Through the test of 4 strong convective weather cases, the accuracy of the automatic identification of the squall line reaches about 75%. In particular, the high-value echo region, which exhibits straight or inferior arc and clear boundary, has higher identification rate. This method can automatically and objectively analyze the work of subjective analysis and judgment of radar echo images by meteorological professionals, and can improve the accuracy and effectiveness of squall line identification and strong convective weather warning services. |
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| Keywords: | synoptic meteorology squall line weather radar radar echo squall line feature recognition |
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