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Operational Application of Optical Flow Techniques to Radar-Based Rainfall Nowcasting

机译:光流技术在基于雷达的降雨临近预报中的业务应用

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Hong Kong Observatory has been operating an in-house developed rainfall nowcasting system called “Short-range Warning of Intense Rainstorms in Localized Systems (SWIRLS)” to support rainstorm warning and rainfall nowcasting services. A crucial step in rainfall nowcasting is the tracking of radar echoes to generate motion fields for extrapolation of rainfall areas in the following few hours. SWIRLS adopted a correlation-based method in its first operational version in 1999, which was subsequently replaced by optical flow algorithm in 2010 and further enhanced in 2013. The latest optical flow algorithm employs a transformation function to enhance a selected range of reflectivity for feature tracking. It also adopts variational optical flow computation that takes advantage of the Horn–Schunck approach and the Lucas–Kanade method. This paper details the three radar echo tracking algorithms, examines their performances in several significant rainstorm cases and summaries verification results of multi-year performances. The limitations of the current approach are discussed. Developments underway along with future research areas are also presented.
机译:香港天文台一直在运作内部开发的降雨临近预报系统,称为“本地化系统暴雨的短程预警”,以支持降雨预警和降雨临近预报服务。降雨临近预报中的关键步骤是跟踪雷达回波以生成运动场,以在接下来的几个小时内推断降雨区域。 SWIRLS在1999年的第一个可操作版本中采用了基于相关性的方法,随后在2010年被光流算法所取代,并在2013年得到进一步增强。最新的光流算法采用变换函数来增强选定的反射率范围以进行特征跟踪。它还采用变光流计算,该计算利用了Horn-Schunck方法和Lucas-Kanade方法。本文详细介绍了三种雷达回波跟踪算法,检查了它们在几个重大暴雨案例中的性能,并总结了多年性能的验证结果。讨论了当前方法的局限性。还介绍了随着未来研究领域的发展。

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