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Estimation of trends in rainfall extremes with mixed effects models

机译:用混合效应模型估算极端降雨的趋势

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Estimates of seasonal rainfall maxima at durations as short as 6 min are needed for many applications including the design and analysis of urban drainage systems. It is also important to investigate whether or not there is evidence of changes in these extremes, both as an indicator of the sensitivity of rainfall to anthropogenic and natural climate change and as an aid to the calibration of future scenarios. Estimation of trends in extreme values in a region needs to be based on all the available data if precision is to be achieved. However, extremes at different periods of accumulation at neighbouring sites are not independent because there are temporal and spatial correlations, respectively. A linear mixed effects (Ime) model allows for this correlation structure, and can be fitted to unequal record lengths at different sites. The modelling technique is demonstrated with an analysis of monthly maximum rainfall, at nine aggregations between 6 min and 24 h, from six sites, with record lengths between 10 and 25 years, from a region in South Australia. In terms of mean value, there is no evidence of a trend or change in the seasonal distribution of the monthly extreme rainfall. However, there is a strong evidence of an increase in variability of monthly extreme rainfall, estimated as a 58% increase in absolute value of deviation from the mean over a 25 year period. Rainfall records are often only available as a daily accumulation. A formula for the ratio of the monthly maxima at durations shorter than 24 h, down to 6 min, to the 24 h monthly maximum, in terms of: duration, month of the year, and a site specific adjustment is estimated. There is a clear seasonal variation in the ratios and there is evidence of a difference between rainfall stations. (C) 2015 Elsevier B.V. All rights reserved.
机译:对于许多应用,包括城市排水系统的设计和分析,都需要在短至6分钟的持续时间内估算季节性降雨最大值。调查这些极端情况是否有证据也很重要,既可以作为降雨对人为和自然气候变化敏感性的指标,也可以作为对未来情景的校准的辅助手段。如果要实现精度,则需要基于所有可用数据来估计区域中的极值趋势。但是,相邻站点不同积累时期的极端情况不是独立的,因为分别存在时间和空间相关性。线性混合效果(Ime)模型允许这种相关结构,并且可以适合不同位置的不相等记录长度。通过分析来自南澳大利亚一个地区的六个地点的六个月(在6分钟至24小时之间)的9个聚合体,记录了在10到25年之间的记录长度,对月最大降雨量进行了分析,从而证明了该建模技术。就平均值而言,没有证据表明每月极端降雨的季节分布有趋势或变化。但是,有确凿的证据表明每月极端降雨的变化性有所增加,据估计,在25年内,平均绝对偏差值增加了58%。降雨记录通常仅以每日累积的形式提供。估算以下持续时间少于24小时(最多6分钟)的每月最大值与每月24小时最大值的比率的公式,该公式是:持续时间,一年中的月份以及特定地点的调整。比率存在明显的季节性变化,并且有证据表明降雨站之间存在差异。 (C)2015 Elsevier B.V.保留所有权利。

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