New hourly extreme precipitation regions and regional annual probability estimates for the UK
New hourly extreme precipitation regions and regional annual probability estimates for the UK
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DOI：
10.1002/joc.6639
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发表时间：
2020-06-01
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影响因子：
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通讯作者：
Faulkner, Duncan
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作者：
Darwish, Motasem M.;Tye, Mani R.;Faulkner, Duncan
英国最近与极端降水有关的洪灾凸显了更好地了解这些事件的重要性。许多研究使用固定区域(例如HadUKP)和感兴趣区域(ROI)(例如洪水估计手册)方法来量化英国极端日降水量的年度超出概率(或重现期)，尽管很少有人评估对山洪暴发很重要的短期事件。英国现有的极端降水区是基于每日数据集的，与次日极端值相比，这些数据集具有不同的特征，因此它们可能不适用于量化短持续时间极端值。我们使用最近可用的、有质量控制的英国1992-2014年每小时降水量数据集来得出各种极端降水指数(例如，年最大值，0.99分位数)，并结合其他气候变量(例如，温度)、地理特征(例如，纬度)和天气模式(WPS)来描述英国每小时极端降水气候学，并定义了五个新的每小时极端区域。这些区域实现了区域同质性和不协调性的统计测量，并反映了与英国和欧洲周边地区定义的天气模式分类相关的动态过程。然后，我们利用区域频率分析(RFA)将广义极值(GeV)和广义帕累托(GP)分布分别拟合到1小时年最大值(AMAX)和0.99分位数(Q99)降水量，计算出20%、10%和2%(即5年、10年和50年重现期)的区域年概率估计(AEP)。新的区域捕捉到了英国每小时降雨量的空间变化。此外，对于每个地区，使用这两种分布的AEP估计是相似的。最后，与最极端的每小时降水累积的频率和强度有关的WPS与其他人报告的每日降水的结果并不相同。
Recent flooding related to extreme precipitation in the UK has highlighted the importance of better understanding these events. Many studies have quantified annual exceedance probabilities (or return periods) for UK extreme daily precipitation using fixed regions (e.g., HadUKP) and region of interest (ROI) (e.g., Flood Estimation Handbook) approaches, although fewer have evaluated short-duration events, which are important for flash flooding. Existing UK extreme precipitation regions are based on daily datasets which have different characteristics compared to sub-daily extremes, and their application to quantify short-duration extremes may therefore be inappropriate. We use a recently available, quality-controlled hourly precipitation dataset for the UK from 1992 to 2014 to derive various extreme precipitation indices (e.g., annual maxima, 0.99 quantile) which are combined with additional climatological variables (e.g., temperature), geographical characteristics (e.g., latitude), and weather patterns (WPs) to characterize the UK hourly extreme precipitation climatology and to define five new hourly extreme regions. These regions fulfil regional homogeneity and discordancy statistical measures, and reflect the dynamical processes associated with the weather pattern categorisation defined over the UK and surrounding European area. Thereafter, we use regional frequency analysis (RFA) to fit generalized extreme value (GEV) and generalized Pareto (GP) distributions to 1 hr annual maxima (AMAX) and 0.99 quantile (Q99) precipitation, respectively, to calculate regional annual probability estimates (AEP) for 20%, 10%, and 2% (i.e., 5-, 10-, and 50-year return periods). The new regions capture the spatial variation of hourly precipitation across the UK. Furthermore, the AEP estimates using both distributions are similar for each region. Finally, the WPs associated with the frequency and intensity of the most extreme hourly precipitation accumulations are not identical to results reported by others for daily precipitation.