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首页> 外文期刊>Hydrology and Earth System Sciences >Accounting for global-mean warming and scaling uncertainties in climate change impact studies: application to a regulated lake system
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Accounting for global-mean warming and scaling uncertainties in climate change impact studies: application to a regulated lake system

机译：气候变化影响研究中全球平均变暖和规模不确定性的考虑：在受监管的湖泊系统中的应用

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A probabilistic assessment of climate change and related impacts should consider a large range of potential future climate scenarios. State-of-the-art climate models, especially coupled atmosphere-ocean general circulation models and Regional Climate Models (RCMs) cannot, however, be used to simulate such a large number of scenarios. This paper presents a methodology for obtaining future climate scenarios through a simple scaling methodology. The projections of several key meteorological variables obtained from a few regional climate model runs are scaled, based on different global-mean warming projections drawn in a probability distribution of future global-mean warming. The resulting climate change scenarios are used to drive a hydrological and a water management model to analyse the potential climate change impacts on a water resources system. This methodology enables a joint quantification of the climate change impact uncertainty induced by the global-mean warming scenarios and the regional climate response. It is applied to a case study in Switzerland, a water resources system formed by three interconnected lakes located in the Jura Mountains. The system behaviour is simulated for a control period (1961–1990) and a future period (2070–2099). The potential climate change impacts are assessed through a set of impact indices related to different fields of interest (hydrology, agriculture and ecology). The results obtained show that future climate conditions will have a significant influence on the performance of the system and that the uncertainty induced by the inter-RCM variability will contribute to much of the uncertainty of the prediction of the total impact. These CSRs cover the area considered in the 2001–2004 EU funded project SWURVE.
机译：对气候变化及其相关影响进行概率评估时，应考虑大量潜在的未来气候情景。但是，不能使用最新的气候模型，尤其是大气海洋耦合的一般循环模型和区域气候模型（RCM）来模拟如此大量的情景。本文提出了一种通过简单的定标方法获得未来气候情景的方法。根据在未来全球平均变暖的概率分布中得出的不同的全球平均变暖预测，对从几个区域气候模型运行中获得的几个关键气象变量的预测进行缩放。由此产生的气候变化情景被用来驱动水文和水资源管理模型，以分析气候变化对水资源系统的潜在影响。这种方法可以对全球平均变暖情景和区域气候响应引起的气候变化影响不确定性进行联合量化。它被应用于瑞士的一个案例研究中，该水资源系统是由位于汝拉山区的三个相互连接的湖泊组成的。在控制时期（1961–1990）和未来时期（2070–2099）模拟系统行为。通过一系列与不同兴趣领域（水文学，农业和生态学）相关的影响指数来评估潜在的气候变化影响。获得的结果表明，未来的气候条件将对系统的性能产生重大影响，RCM间变异性引起的不确定性将对总影响的预测产生很大的不确定性。这些企业社会责任涵盖了2001–2004年欧盟资助的项目SWURVE中考虑的领域。

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