德国极端降水季节周期的年际变化及对气候变化的响应

Madlen Peter, H. Rust, U. Ulbrich
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引用次数: 0

摘要

摘要日降水量总和的年最大值通常可以用静止的广义极值(GEV)分布很好地描述。在世界许多地区,这种描述对于一年中某月的月最大降水量也很有效。然而,要描述季节和年际变化,则需要使用非稳态模型。因此,我们在本文中提出了一种应用于德国雨量计长期时间序列的非稳态建模策略。GEV 参数的季节变化用一系列谐函数建模,年际变化用高阶正交多项式建模。通过项之间的相互作用,我们可以使季节周期随时间变化。通常情况下,GEV 的形状参数 ξ 被估计为恒定值,在其他情况下也是如此。在这里,我们考虑了季节-年际变化,并发现这样做是有益的。利用贝叶斯信息准则(BIC),采用逐步向前回归法为每个时间序列选择合适的模型。使用量化技能得分(QSS)及其分解进行交叉验证后发现,与仅考虑季节性变化的模型相比,季节性-跨年度变化的收益水平具有性能增益。有证据表明,气候变化对德国极端降水量的影响是可以检测到的,但各地区的变化却大相径庭。一般来说,降水量的增加比减少更为普遍。极端降水量分布(2 年一遇)的中位数通常在春季和秋季增加,并转移到一年中的晚些时候;强降水(100 年一遇)主要在夏季增加,并在一年中的早些时候出现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Interannual variations in the seasonal cycle of extreme precipitation in Germany and the response to climate change
Abstract. Annual maxima of daily precipitation sums can be typically described well with a stationary generalized extreme value (GEV) distribution. In many regions of the world, such a description does also work well for monthly maxima for a given month of the year. However, the description of seasonal and interannual variations requires the use of non-stationary models. Therefore, in this paper we propose a non-stationary modeling strategy applied to long time series from rain gauges in Germany. Seasonal variations in the GEV parameters are modeled with a series of harmonic functions and interannual variations with higher-order orthogonal polynomials. By including interactions between the terms, we allow for the seasonal cycle to change with time. Frequently, the shape parameter ξ of the GEV is estimated as a constant value also in otherwise instationary models. Here, we allow for seasonal–interannual variations and find that this is beneficial. A suitable model for each time series is selected with a stepwise forward regression method using the Bayesian information criterion (BIC). A cross-validated verification with the quantile skill score (QSS) and its decomposition reveals a performance gain of seasonally–interannually varying return levels with respect to a model allowing for seasonal variations only. Some evidence can be found that the impact of climate change on extreme precipitation in Germany can be detected, whereas changes are regionally very different. In general, an increase in return levels is more prevalent than a decrease. The median of the extreme precipitation distribution (2-year return level) generally increases during spring and autumn and is shifted to later times in the year; heavy precipitation (100-year return level) rises mainly in summer and occurs earlier in the year.
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