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An assessment of areal coverage of severe weather parameters for severe weather outbreak diagnosis

机译：评估严重天气参数的区域覆盖范围以进行严重天气暴发诊断

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The areal extent of severeweather parameters favorable for significant severeweather is evaluated as a means of identifying major severe weather outbreaks. The first areal coverage method uses kernel density estimation (KDE) to identify severeweather outbreak locations. Aselected severeweather parameter value is computed at each grid point within the region identified by KDE. The average, median, or sum value is used to diagnose the event's severity. The second areal coverage method finds the largest contiguous region where a severe weather parameter exceeds a specified threshold that intersects theKDEregion. The severeweather parameter values at grid points within the parameter exceedance region are computed, with the average, median, or sumvalue used to diagnose the event's severity. A total of 4057 severe weather outbreaks from 1979 to 2008 are analyzed. An event is considered a major outbreak if it exceeds a selected ranking index score (developed in previous work), and is a minor event otherwise. The areal coverage method is also compared to Storm Prediction Center (SPC) day-1 convective outlooks from 2003 to 2008. Comparisons of the SPC forecasts and areal coverage diagnoses indicate the areal coverage methods have similar skill to SPC convective outlooks in discriminating major and minor severe weather outbreaks. Despite a seemingly large sample size, the rare-events nature of the dataset leads to sample size sensitivities. Nevertheless, the findings of this study suggest that areal coverage should be tested in a forecasting environment as a means of providing guidance in future outbreak scenarios.
机译：评价有利于重大恶劣天气的恶劣天气参数的面积范围，作为识别重大恶劣天气暴发的一种手段。第一种区域覆盖方法是使用核密度估计（KDE）来识别恶劣天气爆发的位置。在由KDE标识的区域内的每个网格点上计算选定的恶劣天气参数值。平均值，中位数或总和值用于诊断事件的严重性。第二种区域覆盖方法是在恶劣天气参数超过与KDE区域相交的指定阈值的情况下，找到最大的连续区域。计算参数超出范围内网格点处的恶劣天气参数值，并使用平均值，中位数或和值来诊断事件的严重性。分析了1979年至2008年之间的4057起严重天气暴发。如果事件超过选定的排名指数得分（在先前的工作中发展），则该事件被认为是重大爆发，否则，则是次要事件。还将该区域覆盖方法与2003年至2008年风暴预报中心（SPC）第一天的对流前景进行了比较。SPC预测和区域覆盖诊断的比较表明，区域覆盖方法在区分主要和次要方面与SPC对流前景具有相似的技能。严重的天气暴发。尽管样本量看似很大，但数据集的稀有事件性质导致样本量敏感性。但是，这项研究的结果表明，应该在预测环境中测试区域覆盖率，以作为在未来爆发病例中提供指导的手段。

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