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Future changes in European winter storm losses and extreme wind speeds inferred from GCM and RCM multi-model simulations

机译:欧洲冬季风暴损失的未来变化和GCM和RCM多模型模拟推断出极端风速

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Extreme wind speeds and related storm loss potential in Europe have been investigated using multi-model simulations from global (GCM) and regional (RCM) climate models. Potential future changes due to anthropogenic climate change have been analysed from these simulations following the IPCC SRES A1B scenario. The large number of available simulations allows an estimation of the robustness of detected future changes. All the climate models reproduced the observed spatial patterns of wind speeds, although some models displayed systematic biases. A storm loss model was applied to the GCM and RCM simulated wind speeds, resulting in realistic mean loss amounts calculated from 20th century climate simulations, although the inter-annual variability of losses is generally underestimated. In future climate simulations, enhanced extreme wind speeds were found over northern parts of Central and Western Europe in most simulations and in the ensemble mean (up to 5%). As a consequence, the loss potential is also higher in these regions, particularly in Central Europe. Conversely, a decrease in extreme wind speeds was found in Southern Europe, as was an associated reduction in loss potential. There was considerable spread in the projected changes of individual ensemble members, with some indicating an opposite signature to the ensemble mean. Downscaling of the large-scale simulations with RCMs has been shown to be an important source of uncertainty. Even RCMs with identical boundary forcings can show a wide range of potential changes. The robustness of the projected changes was estimated using two different measures. First, the inter-model standard deviation was calculated; however, it is sensitive to outliers and thus displayed large uncertainty ranges. Second, a multi-model combinatorics approach considered all possible sub-ensembles from GCMs and RCMs, hence taking into account the arbitrariness of model selection for multi-model studies. Based on all available GCM and RCM simulations, for example, a 25% mean increase in risk of loss for Germany has been estimated for the end of the 21st century, with a 90% confidence range of +15 to +35%.
机译:使用全球(GCM)和区域(RCM)气候模型的多模型模拟研究了欧洲的极端风速和相关风暴损失潜力。在IPCC SRES A1B场景之后,已经从这些模拟中分析了由于人为气候变化导致的潜在未来变化。大量可用模拟允许估计检测到的未来变化的稳健性。所有气候模型都复制了观察到的风速样式,尽管有些型号显示系统偏差。风暴损失模型应用于GCM和RCM模拟风速,导致20世纪的气候模拟计算的现实平均损失量,尽管损失的年间变异通常低估。在未来的气候模拟中,大多数模拟和西欧的北部地区都发现了增强的极端风速,在大多数模拟和集合中(最多5%)。因此,这些地区的损失潜力也在更高,特别是在中欧。相反,欧洲南部发现极端风速下降,损失潜力的相关降低也是如此。在个人集成成员的预计变化中有很大的传播,一些指示合并意味着对面的签名。随着RCMS的大规模模拟的缩小已被证明是一个不确定性的重要来源。即使是具有相同边界强制的RCM也可以显示出广泛的潜在变化。使用两种不同的措施估计预计变化的稳健性。首先,计算模型间标准偏差;然而,它对异常值敏感,因此显示出大的不确定性范围。其次,多模型组合方法考虑了来自GCM和RCM的所有可能的子组合,因此考虑了模型选择的多模型研究的任意性。例如,基于所有可用的GCM和RCM模拟,21世纪末估计德国损失风险的25%的平均增加,90%的置信范围+15至+ 35%。

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