Relation between storm characteristics and extreme precipitation statistics over CONUS
Relation between storm characteristics and extreme precipitation statistics over CONUS
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美国大陆地区风暴特征与极端降水统计之间的关系
DOI：
10.1016/j.advwatres.2023.104497
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发表时间：
2023
影响因子：
4.7
通讯作者：
Nikolopoulos, Efthymios I.
中科院分区：
文献类型：
--
作者：
Araujo, Diogo S.A.;Marra, Francesco;Ali, Haider;Fowler, Hayley J.;Nikolopoulos, Efthymios I.
在本文中，我们使用一个统计框架来分析风暴属性和极端降水统计之间的关系。我们使用24小时干燥间断分离来识别风暴事件。我们调查的最大风暴事件在1和24小时的持续时间的小时最大强度的统计。一个两参数的威布尔分布是用来代表降水频率在几个站从一个质量控制的每小时降水数据集在连续的美国，包括七个气候区。的分布参数和选择的风暴属性（持续时间，强度，去相关时间，对流样比）和站点属性（海拔和纬度）之间的斯皮尔曼相关性被用来衡量这些属性与极端降水的统计数据的关系。我们的研究结果表明，在整个研究区域观测到的年最大小时降水量可能是来自所使用的分布的样本，这意味着两个参数的威布尔分布是适合建模的每小时和24小时的降水极端在美国本土。每小时的事件得到的形状参数的空间变异性显示较轻的尾巴在西海岸相比，其余的美国本土，而中北部显示较重的尾巴。我们确定了与基本过程（例如，典型的风暴持续时间，典型的时间自相关，对流类风暴的比例）和分布参数。值得注意的是，对流降水的典型特征，例如，急剧的去相关时间和高小时强度，往往与分布较重的尾巴。这些结果为将风暴特征与当地极端事件统计数据联系起来迈出了第一步。
In this paper we use a statistical framework to analyze the relation between storm properties and the statistics of extreme precipitation. We identify storm events using a 24-hour dry hiatus separation. We investigate the statistics of the hourly maximum intensity for the heaviest storm events at durations of 1 and 24 h. A two-parameter Weibull distribution is used to represent precipitation frequencies at several stations from a quality-controlled hourly precipitation dataset over the contiguous United States, encompassing seven climate zones. The Spearman correlation between the distribution parameters and a selection of storm properties (duration, intensity, decorrelation time, convective-like ratio) and station properties (elevation and latitude) is used to measure the relation of these properties with the statistics of extreme precipitation. Our results indicate that observed annual maximum hourly precipitation over the entire study area are likely samples from the used distribution, implying that a two-parameter Weibull distribution is suitable for modeling hourly and 24-hour precipitation extremes over the contiguous United States. The spatial variability of shape parameters obtained for hourly events showed lighter tails in the west coast when compared to the rest of CONUS, while the central-north displays heavier tails. We identify statistically significant links (at the 95% confidence level) between storm characteristics connected with the underlying processes (e.g., typical storm duration, typical temporal autocorrelation, proportion of convective-like storms) and the parameters of the distribution. Notably, characteristics typical of convective precipitation, e.g., sharp decorrelation time and high hourly intensity, tend to be related to distributions with heavier tails. These results provide a first step towards linking the characteristics of storms with the local statistics of extremes.