Abstract A stochastic rainfall model that can reproduce various rainfall characteristics at timescales between 5 min and one decade is introduced. The model generates the fine-scale rainfall time series using a randomized Bartlett-Lewis rectangular pulse model. Then the rainstorms are shuffled such that the correlation structure between the consecutive storms are preserved. Finally, the time series is rearranged again at the monthly timescale based on the result of the separate coarse-scale monthly rainfall model. The method was tested using the 69 years of 5-minute rainfall data recorded at Bochum, Germany. The mean, variance, covariance, skewness, and rainfall intermittency were well reproduced at the timescales from 5 min to a decade without any systematic bias. The extreme values were also well reproduced at timescales from 5 min to 3 days. The past-7-day rainfall before an extreme rainfall event, which is highly associated with the extreme flow discharge was reproduced well too. The rainstorm shuffling approaches introduced here may be adopted as a standard procedure in combination with any Poisson cluster rainfall model. The methods are simple and parsimonious, yet significantly reduce the systematic underestimation of rainfall variance at coarse scales, and improve the reproduction of skewness, and extreme rainfall depths values at a range of time-scales, thereby addressing well-known shortcomings of Poisson cluster rainfall models.

中文翻译：

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一个随机降雨模型，可以在几分钟到十年的时间尺度上重现重要的降雨特性

摘要 介绍了一种随机降雨模型，该模型可以再现5 min 到10 年之间的时间尺度上的各种降雨特征。该模型使用随机 Bartlett-Lewis 矩形脉冲模型生成细尺度降雨时间序列。然后对暴雨进行洗牌，从而保留连续暴雨之间的相关结构。最后，根据单独的粗尺度月降雨模型的结果，在月时间尺度上再次重新排列时间序列。该方法使用在德国波鸿记录的 69 年 5 分钟降雨数据进行了测试。均值、方差、协方差、偏度和降雨间歇性在 5 分钟到十年的时间尺度上得到了很好的再现，没有任何系统偏差。在 5 分钟到 3 天的时间尺度上也很好地再现了极值。与极端水流排放密切相关的极端降雨事件前过去7天的降雨也得到了很好的再现。这里介绍的暴雨洗牌方法可以作为标准程序与任何泊松聚类降雨模型结合使用。该方法简单简洁，但显着降低了对粗尺度降雨方差的系统性低估，提高了偏度和时间尺度范围内极端降雨深度值的再现，从而解决了泊松簇降雨众所周知的缺点楷模。这里介绍的暴雨洗牌方法可以作为标准程序与任何泊松聚类降雨模型结合使用。该方法简单简洁，但显着降低了对粗尺度降雨方差的系统性低估，提高了偏度和时间尺度范围内极端降雨深度值的再现，从而解决了泊松簇降雨众所周知的缺点楷模。这里介绍的暴雨洗牌方法可以作为标准程序与任何泊松聚类降雨模型结合使用。该方法简单简洁，但显着降低了对粗尺度降雨方差的系统性低估，提高了偏度和时间尺度范围内极端降雨深度值的再现，从而解决了泊松簇降雨众所周知的缺点楷模。