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Analysing uncertainties in climate change impact assessment across sectors and scenarios

机译：分析跨部门和情景的气候变化影响评估中的不确定性

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摘要

Many models have been developed to explore the likely consequences of climate change. These models tend to focus on single physical or socio-economic sectors and their processes, and neglect the many feedbacks that occur between the different components of the real world. To overcome this problem, models are increasingly being combined in integrated assessment platforms (IAPs), of which the CLIMSAVE IAP is an example, modelling cross-sectoral impacts, adaptation and vulnerability to climate change in Europe by combining 10 different meta-models that focus on specific sectors. Where models are combined in this way, however, attention must be given to the potential errors and uncertainties that integration might introduce. We present a quantitative uncertainty analysis of selected outputs of the CLIMSAVE IAP based on creating and sampling from probability density functions (PDFs) of each of the IAP's input variables to take account of model and scenario uncertainty. We find limited uncertainties in aggregate outputs of the IAP, which allow specific impacts to be predicted with definable levels of confidence. However, we also find substantial overlap between different socio-economic scenarios at the European scale, suggesting that changes to socio-economic conditions cannot reliably overcome climate-related uncertainty. Nevertheless, there is evidence that particular adaptation actions may significantly alter the impacts of climate change, especially at local or national scales.
机译：已经开发出许多模型来探索气候变化的可能后果。这些模型倾向于只关注单一的物理或社会经济部门及其过程，而忽略了现实世界不同部分之间发生的许多反馈。为了克服这个问题，越来越多的模型被集成到综合评估平台（IAP）中，其中CLIMSAVE IAP就是一个例子，它通过结合10种不同的元模型来对欧洲的跨部门影响，适应性和对气候变化的脆弱性进行建模。在特定领域。但是，在以这种方式组合模型的地方，必须注意集成可能引入的潜在错误和不确定性。我们基于创建和采样每个IAP输入变量的概率密度函数（PDF）并考虑模型和场景不确定性的情况，对CLIMSAVE IAP的选定输出进行了定量不确定性分析。我们发现，IAP总产出的不确定性有限，因此可以在可确定的置信水平下预测特定影响。但是，我们还发现欧洲范围内不同社会经济情景之间存在大量重叠，这表明社会经济条件的变化无法可靠地克服与气候相关的不确定性。然而，有证据表明，特定的适应行动可能会显着改变气候变化的影响，尤其是在地方或国家范围内。

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