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Tracking the Centre of Asymmetric Vortices Using Wind Velocity Vector Data Fields
Boundary-Layer Meteorology ( IF 2.3 ) Pub Date : 2022-09-09 , DOI: 10.1007/s10546-022-00739-0
Niall Bannigan , Leigh Orf , Eric Savory

Tornados are a major hazard in many regions around the world and as such it is necessary to analyze them. However, such analyses require accurately tracking them first. Currently, there are gaps in the available vortex detection methods when processing a wind-field dataset to locate a series of points that are identifiable as the tornado centreline. This study proposes a novel solution that corrects for deficiencies in previous attempts to identify vortex centres when applied to tornado wind-fields, which would have otherwise led to identifying merely the region of the vortex, several potential centres requiring post-processing, or erroneously approximating the tornado centre. Additionally, this method combines the efficiency required to process large datasets of temporal and spatial wind velocity vector distributions with the accuracy needed to reliably calculate a specific line as a tornado centre. This method is compared to five other approaches commonly used for vortex identification in order to assess: (a) how accurately they identify the centre region, (b) how they handle extraneous vortices that are not of interest, and (c) their computational efficiency in processing a wind-field dataset. With the proposed method, it would be possible to plot a tornado path from formation to dissipation and perform analyses to understand the vortex characteristics with respect to this path without requiring extensive user-intervention.



中文翻译:

使用风速矢量数据字段跟踪不对称涡旋的中心

龙卷风是世界上许多地区的主要灾害,因此有必要对其进行分析。但是,此类分析需要首先准确跟踪它们。目前,在处理风场数据集以定位一系列可识别为龙卷风中心线的点时,可用的涡流检测方法存在差距。本研究提出了一种新颖的解决方案,该解决方案可以纠正先前尝试在应用于龙卷风风场时识别涡旋中心的缺陷,否则这将导致仅识别涡旋区域、需要后处理的几个潜在中心或错误地近似龙卷风中心。此外,该方法将处理大型时空风速矢量分布数据集所需的效率与可靠地将特定线计算为龙卷风中心所需的精度相结合。将该方法与通常用于涡流识别的其他五种方法进行比较,以评估:(a)它们识别中心区域的准确度,(b)它们如何处理不感兴趣的无关涡流,以及(c)它们的计算效率在处理风场数据集时。使用所提出的方法,可以绘制从形成到消散的龙卷风路径,并执行分析以了解与该路径相关的涡流特征,而无需大量用户干预。将该方法与通常用于涡流识别的其他五种方法进行比较,以评估:(a)它们识别中心区域的准确度,(b)它们如何处理不感兴趣的无关涡流,以及(c)它们的计算效率在处理风场数据集时。使用所提出的方法,可以绘制从形成到消散的龙卷风路径,并执行分析以了解与该路径相关的涡流特征,而无需大量用户干预。将该方法与通常用于涡流识别的其他五种方法进行比较,以评估:(a)它们识别中心区域的准确度,(b)它们如何处理不感兴趣的无关涡流,以及(c)它们的计算效率在处理风场数据集时。使用所提出的方法,可以绘制从形成到消散的龙卷风路径,并执行分析以了解与该路径相关的涡流特征,而无需大量用户干预。

更新日期:2022-09-09
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