| X波段双偏振雷达相态识别与拼图的关键技术 |
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| 引用本文： | 吴翀,刘黎平,仰美霖,马建立,李娟.X波段双偏振雷达相态识别与拼图的关键技术[J].应用气象学报,2021,32(2):200-216. |
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| 作者姓名： | 吴翀 刘黎平 仰美霖 马建立 李娟 |
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| 作者单位： | 1).中国气象科学研究院, 北京 100081 |
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| 摘 要： | X波段双偏振雷达具有时空分辨率高、易于布网的特点，但散射特性差异和衰减影响使现有S波段雷达的相态识别和拼图算法不适用于X波段双偏振雷达。该文针对X波段相态识别及拼图产品的关键技术开展研究，提出基于准垂直剖面的融化层识别方法、基于数据质量的置信度阈值调整方法、基于统计的隶属函数参数改进方法和基于衰减程度的拼图融合方法。通过对比改进后可有效提升水凝物相态识别结果的可靠性和多雷达拼图结果的合理性。在2016年汛期北京典型个例中，融合后的X波段雷达网与当地S波段业务雷达相比能够提供更精细的回波结构和水凝物相态分布，有效缓解S波段雷达在近处探测能力降低的问题，识别的降雹区与地面观测相符。
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| 关 键 词： | X波段双偏振雷达 水凝物相态识别 雷达拼图 |
| 收稿时间： | 2020-07-01 |
Key Technologies of Hydrometeor Classification and Mosaic Algorithm for X-band Polarimetric Radar |
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| Institution: | 1).Chinese Academy of Meteorological Sciences, Beijing 1000812).Institute of Urban Meteorology, CMA, Beijing 1000893).Nanjing University of Information Science & Technology, Nanjing 210044 |
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| Abstract: | The advantages of X-band polarimetric weather radar focus on its high spatio-temporal resolution and capability of multi-radar networking. However, the previously designed hydrometeor classification algorithm (HCA) for S-band weather radar is unsuitable for X-band weather radar due to the difference of backscattering characteristics and heavy precipitation attenuation. Therefore, the key technologies of hydrometeor classification algorithm and multi-radar mosaic algorithm for X-band polarimetric weather radar are proposed. First, it is found that the melting layer detection algorithm designed for S-band polarimetric weather radar is not suitable for X-band weather radar through analysis on the data collected by Beijing X-band radar network. A melting layer detection method based on quasi-vertical profile is proposed, which greatly improves the accuracy of obtaining the melting information. Second, a confidence threshold adjustment method is proposed to accurately estimate the data quality in the case of precipitation and clutter superposition. Third, an optimization method of membership functions based on data statistics is proposed to reconstruct the classification parameters suitable for Beijing X-band radar network. Finally, a multi-radar mosaic method based on rainfall attenuation is proposed, in which the reflectivity factors of networking radars are weighted and averaged by the data quality factor. Compared with the traditional method, it is found that the structural inhomogeneity of X-band radar mosaic result is effectively reduced. Those modifications effectively enhance the reliability of classification mosaic results of X-band weather radar network and provide technical support for the rapid deployment of X-band radar in China. Three typical precipitation cases in Beijing during the flood season in 2016 are used to compare the observational efficiency between X-band weather radar network and S-band operational radar. For the cases of convective rainfall, fine echo structures and reasonable hydrometeor distributions are found in X-band radar mosaic results. Especially for convective rainfall with short duration and small spatial scale, the advantage of X-band radar is more obvious, which alleviates the limited detection ability of S-band operational radar in urban areas. In addition, the hail falling area identified by X-band radar can be verified by manual observation in national weather stations. The performance of X-band weather radar network in large-scale stratiform precipitation, however, is not as good as S-band weather radar. |
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