基于OPTICS聚類算法的雷達數據雷暴單體識別方法
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南方電網科技項目(GZHKJXM20170061)資助


A Storm Cell Identification Method for Radar Data Based on OPTICS Algorithm
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    摘要:

    雷達數據的雷暴單體識別算法是雷暴追蹤算法的重要組成部分,傳統的連續區域法只能通過改變回波強度閾值來調整雷暴單體識別結果,不能滿足當前應用需求。本文提出了一種基于OPTICS(Ordering Points to Identify the Clustering Structure)算法的雷暴識別方法,該方法能基于高回波點的密度信息進行雷暴單體識別。利用高分辨率X波段天氣雷達在兩次雷暴過程中的體掃數據檢驗了算法的效果,并與傳統方法進行了比較。結果表明:該方法能克服連續區域法在高分辨率雷達數據中可能出現的無法區分不同單體、識別結果過于零散等問題。并且能在不修改回波強度閾值的情況下靈活調整輸出結果,以適應不同應用需求。

    Abstract:

    The thunderstorm identification algorithm of radar data is an important part of the thunderstorm tracking technique. The traditional continuous region method can only adjust thunderstorm identification results by changing the reflectivity threshold, which cannot meet the current application requirements. This paper proposes a storm identification method based on the OPTICS (Ordering Points to Identify the Clustering Structure) algorithm. This method can identify storm cells based on the density information of points with high reflectivity. Using volume scan data of high-resolution X-band weather radar in two thunderstorms, the performance of the proposed algorithm is tested and compared with the traditional method. The results show that this method can overcome the problems that may occur in traditional methods in high-resolution radar data, such as being unable to distinguish adjacent cells or getting too scattered identification results. Besides, it can flexibly adjust the output results without changing the reflectivity threshold to meet the needs of different applications.

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潘巧,林其雄,劉智勇,張滔,章卓雨,何正浩.基于OPTICS聚類算法的雷達數據雷暴單體識別方法[J].氣象科技,2022,50(5):623~629

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  • 收稿日期:2021-08-30
  • 定稿日期:2022-04-29
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  • 在線發布日期: 2022-10-28
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