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Comparing statistical post-processing of regional and global climate scenarios for hydrological impacts assessment: A case study of two Canadian catchments

机译:比较区域和全球气候情景的统计后处理以评估水文影响:两个加拿大流域的案例研究

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Projected climate change effects on streamflow are investigated for the 2041-2070 horizon following the SRES A2 emissions scenario over two snowmelt-dominated catchments in Canada. A 16-member ensemble of SWAT hydrological model (HM) simulations, based on a comprehensive ensemble of the Canadian Regional Climate Model (CRCM) simulations driven by two global climate models (GCMs), with five realizations of the Canadian CGCM3 and three realizations of the German ECHAM5 is established per catchment. This study aims to evaluate, once model bias has been removed by statistical post-processing (SP), how the RCM-simulated climate changes differ from those of the parent GCMs, and how they affect the assessment of climate change-induced hydrological impacts at the catchment scale. The variability of streamflow caused by the use of different SP methods (mean-based versus distribution-based) within each statistical post-processing pathway of climate model outputs (bias correction versus perturbation) is also evaluated, as well as the uncertainty of natural climate variability. The simulations cover 1971 2000 in the reference period and 2041-2070 in the future period. For a set of criteria, results based on raw and statistically post-processed model outputs for the reference climate are compared with observations. This process demonstrates that SP is important not only for GCMs outputs, but also for CRCM outputs. SP leads to a high level of agreement between the CRCM and the driving GCMs in reproducing patterns of observed climate. The ensemble spread of the climate change signal on streamflow is large and varies with catchments and hydrological periods (winter/summer flows). The results of various hydrological indicators show that most of the uncertainty arises from the natural climate variability followed by the statistical post-processing. The uncertainty linked to the choice of statistical pathway is much larger than that associated with the choice of the method in quantifying the hydrological impacts. We find that the incorporation of dynamical downscaling of global models through the CRCM as an intermediate step in the GCM RCM SP HM model chain does not lead to considerable differences in the assessment of the climate change impacts on streamflow for the study catchments. (C) 2014 Elsevier B.V. All rights reserved.
机译:在加拿大两个以雪融为主的流域,根据SRES A2排放情景,研究了2041-2070年气候变化对河流径流的预计影响。基于由两个全球气候模型(GCM)驱动的加拿大区域气候模型(CRCM)模拟的综合集合,其中包括五个实现的加拿大CGCM3和三个实现的SWAT水文模型(HM)模拟的16个成员的集合每个集水区建立了德国ECHAM5。这项研究旨在评估,一旦通过统计后处理(SP)消除了模型偏差,RCM模拟的气候变化与原始GCM的气候变化有何不同,以及它们如何影响气候变化对水文影响的评估。集水规模。还评估了在气候模型输出的每个统计后处理路径(偏倚校正与扰动)的每个统计后处理路径中使用不同的SP方法(基于均值与基于分布)所导致的流量变化性,以及自然气候的不确定性变化性。模拟涵盖参考期间的1971 2000和未来期间的2041-2070。对于一组标准,将基于原始气候和统计后处理的参考气候模型输出的结果与观测值进行比较。该过程表明,SP不仅对于GCM的输出很重要,对于CRCM的输出也很重要。 SP导致CRCM与行驶中的GCM在再现观测到的气候模式方面达成高度一致。气候变化信号在水流上的整体传播很大,并且随集水区和水文时期(冬/夏季水流)而变化。各种水文指标的结果表明,大多数不确定性来自自然气候的可变性,然后是统计后处理。与统计途径选择相关的不确定性远大于与水文影响定量方法选择相关的不确定性。我们发现,通过CRCM将全球模型的动态降尺度纳入GCM RCM SP HM模型链的中间步骤,并不会导致气候变化对研究集水区的水流影响的评估存在重大差异。 (C)2014 Elsevier B.V.保留所有权利。

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