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Regional frequency analysis of short duration rainfall extremes using gridded daily rainfall data as co-variate

机译:使用网格日降雨量数据作为协变量的短时降雨极值的区域频率分析

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摘要

A regional partial duration series (PDS) model is applied for estimation of intensity duration frequency relationships of extreme rainfalls in Denmark. The model uses generalised least squares regression to relate the PDS parameters to gridded rainfall statistics from a dense network of rain gauges with daily measurements. The Poisson rate is positively correlated to the mean annual precipitation for all durations considered (1 min to 48 hours). The mean intensity can be assumed constant over Denmark for durations up to 1 hour. For durations larger than 1 hour the mean intensity is significantly correlated to the mean extreme daily precipitation. A Generalised Pareto distribution with a regional constant shape parameter is adopted. Compared to previous regional studies in Denmark a general increase in extreme rainfall intensity for durations up to 1 hour is found, whereas for larger durations both increases and decreases are seen. A subsample analysis is conducted to evaluate the impacts of non-stationarities in the rainfall data. The regional model includes the nonstationarities as an additional source of uncertainty together with sampling uncertainty and uncertainty caused by spatial variability.
机译:应用区域局部历时序列(PDS)模型估算丹麦极端降雨的强度历时频率关系。该模型使用广义最小二乘回归将PDS参数与来自具有日常测量数据的密集雨量计网络的网格化降雨统计数据相关联。在所有考虑的持续时间(1分钟至48小时)中,泊松率与年平均降水量呈正相关。可以假设丹麦的平均强度在1小时以内是恒定的。对于大于1小时的持续时间,平均强度与平均极端日降水量显着相关。采用具有区域恒定形状参数的广义帕累托分布。与丹麦先前的区域研究相比,发现长达1小时的极端降雨强度普遍增加,而对于较大的持续时间,则出现增加和减少的现象。进行了子样本分析,以评估降雨数据中非平稳性的影响。区域模型将非平稳性作为不确定性的额外来源,并包括采样不确定性和由空间变异性引起的不确定性。

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