当前和未来欧洲热浪量级:气候、趋势及其在GCM-RCM模式链中的相关不确定性

Changgui Lin, E. Kjellström, R. Wilcke, Deliang L. Chen
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引用次数: 7

摘要

摘要本研究调查了欧洲地区气候模型(RCM)和驱动全球气候模型(GCM)的当前和未来欧洲热浪强度,以每日热浪强度指数(HWMId)为代表。大型EURO-CORDEX系综的一个子集用于研究与GCM、RCM及其组合的选择相关的不确定性来源。我们最初将ERA中期再分析驱动的随机对照模型的评估运行与E-OBS(基于观测的估计)进行了比较,发现随机对照模型可以捕捉HWMId的大部分观测空间和时间特征。与GCM相比,RCM具有更高的分辨率,可以揭示与小规模过程相关的HWMId的空间特征(例如地形效应);此外,RCM令人满意地代表了HWMId的大尺度特征(例如,通过再现e-OBS揭示的总体模式,在西部沿海地区具有高值,在东部具有低值)。我们的结果表明,与驾驶GCM相比,RCM具有明显的附加值。在排放情景RCP8.5的强制下,所有GCM和RCM模拟都一致预测HWMId以指数速度上升。然而,当RCM缩小尺度时,GCM投影的气候变化信号通常会减弱,空间模式也会改变。全球变暖后模拟的未来热浪幅度变化的不确定性几乎可以同样归因于模型物理的差异(由不同的RCM表示)和与不同GCM相关的驱动数据。关于RCM选择的不确定性,一个主要因素是地形效应的不同表示。RCM之间没有观察到与不同GCM相关的系综扩展中的一致空间模式,这表明由于模型动力学和物理的非线性性质,GCM的不确定性由RCM以复杂的方式转换。总之,我们的结果支持使用动态降尺度来推导关于热浪大小的区域气候实现。
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Present and future European heat wave magnitudes: climatologies, trends, and their associated uncertainties in GCM-RCM model chains
Abstract. This study investigates present and future European heat wave magnitudes, represented by the Heat Wave Magnitude Index-daily (HWMId), for regional climate models (RCMs) and the driving global climate models (GCMs) over Europe. A subset of the large EURO-CORDEX ensemble is employed to study sources of uncertainties related to the choice of GCMs, RCMs, and their combinations. We initially compare the evaluation runs of the RCMs driven by ERA-interim reanalysis to E-OBS (observation-based estimates), finding that the RCMs can capture most of the observed spatial and temporal features of HWMId. With their higher resolution compared to GCMs, RCMs can reveal spatial features of HWMId associated with small-scale processes (e.g., orographic effects); moreover, RCMs represent large-scale features of HWMId satisfactorily (e.g., by reproducing the general pattern revealed by E-OBS with high values at western coastal regions and low values at the eastern part). Our results indicate a clear added value of the RCMs compared to the driving GCMs. Forced with the emission scenario RCP8.5, all the GCM and RCM simulations consistently project a rise in HWMId at an exponential rate. However, the climate change signals projected by the GCMs are generally attenuated when downscaled by the RCMs, with the spatial pattern also altered. The uncertainty in a simulated future change of heat wave magnitudes following global warming can be attributed almost equally to the difference in model physics (as represented by different RCMs) and to the driving data associated with different GCMs. Regarding the uncertainty associated with RCM choice, a major factor is the different representation of the orographic effects. No consistent spatial pattern in the ensemble spread associated with different GCMs is observed between the RCMs, suggesting GCM uncertainties are transformed by RCMs in a complex manner due to the nonlinear nature of model dynamics and physics. In summary, our results support the use of dynamical downscaling for deriving regional climate realization regarding heat wave magnitudes.
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