Enhanced object-based tracking algorithm for convective rain storms and cells
Enhanced object-based tracking algorithm for convective rain storms and cells
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DOI：
10.1016/j.atmosres.2017.10.027
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发表时间：
2018-03
影响因子：
5.5
通讯作者：
C. A. Muñoz;Li-Pen Wang;P. Willems
中科院分区：
文献类型：
--
作者：
C. A. Muñoz;Li-Pen Wang;P. Willems
提出了一种新的基于对象的风暴跟踪算法，该算法基于TITAN（雷暴识别、跟踪、分析和临近预报）。TITAN是一种广泛使用的对流风暴跟踪算法，但由于其单阈值识别方法，在处理小尺度但高强度的风暴实体方面存在局限性。由于所采用的匹配方法在很大程度上依赖于连续风暴实体之间的重叠区域，因此也难以有效地跟踪快速移动的风暴。为了解决这些不足之处，本文提出了一些修改和测试。这些措施包括一个两阶段的多阈值风暴识别，一个新的配方，用于表征风暴的物理特征，和增强的匹配技术协同与光流风暴场跟踪器，以及根据这些修改，一个更复杂的合并和分裂计划。高分辨率（5分钟和529米）的雷达反射率数据18个风暴事件在比利时被用来校准和评估算法。所提出的算法的性能进行了比较，与原来的TITAN。结果表明，该算法可以更好地分离和匹配对流降雨实体，以及提供更可靠和详细的运动估计。此外，改善被发现是更显着的降雨强度更高。新算法有可能作为进一步应用的基础，如风暴临近预报和长期随机时空降雨生成。
This paper proposes a new object-based storm tracking algorithm, based upon TITAN (Thunderstorm Identification, Tracking, Analysis and Nowcasting). TITAN is a widely-used convective storm tracking algorithm but has limitations in handling small-scale yet high-intensity storm entities due to its single-threshold identification approach. It also has difficulties to effectively track fast-moving storms because of the employed matching approach that largely relies on the overlapping areas between successive storm entities. To address these deficiencies, a number of modifications are proposed and tested in this paper. These include a two-stage multi-threshold storm identification, a new formulation for characterizing storm's physical features, and an enhanced matching technique in synergy with an optical-flow storm field tracker, as well as, according to these modifications, a more complex merging and splitting scheme. High-resolution (5-min and 529-m) radar reflectivity data for 18 storm events over Belgium are used to calibrate and evaluate the algorithm. The performance of the proposed algorithm is compared with that of the original TITAN. The results suggest that the proposed algorithm can better isolate and match convective rainfall entities, as well as to provide more reliable and detailed motion estimates. Furthermore, the improvement is found to be more significant for higher rainfall intensities. The new algorithm has the potential to serve as a basis for further applications, such as storm nowcasting and long-term stochastic spatial and temporal rainfall generation.