The accuracy of the climate impact models depends on the representative power of the climate model used in the analysis. Many problems in these impact models can be eliminated by the selection of the appropriate climate models as an input. The main purpose of this research is to find a methodology to select the more representative climate models. In recent years, the quantity and quality of climate models have significantly improved. In several projects, many different Global Climate Model (GCM)–Regional Climate Model (GCM) combinations have been carried out. One of these recent comprehensive projects is CORDEX. The monthly temperature outputs of various GCM-RCM combinations over Europe between the years 1976 and 2005 were used in this paper for the determination of the more representative combinations. E-OBS is used as the observation data set in this research. Using the proposed method, a clear difference between the more, moderately, and less representative model combinations could be obtained. To model the future temperature climatology of Europe, the best choice of the analysis method is using MPI as GCM and either REMO or CCLM5 as RCM over the whole domain. According to our analysis, the best representative climate model combination can be performed by running MPI-CCLM5 combination over the EURO-CORDEX domain.

气候影响模型的准确性取决于分析中使用的气候模型的代表性。通过选择合适的气候模型作为输入，可以消除这些影响模型中的许多问题。本研究的主要目的是寻找一种方法来选择更具代表性的气候模型。近年来，气候模式的数量和质量都有了显着提高。在几个项目中，已经进行了许多不同的全球气候模式（GCM）-区域气候模式（GCM）组合。这些最近的综合项目之一是 CORDEX。本文使用 1976 年至 2005 年间欧洲各种 GCM-RCM 组合的月温度输出来确定更具代表性的组合。本研究使用 E-OBS 作为观测数据集。使用所提出的方法，可以获得较多、中等和较少代表性的模型组合之间的明显差异。为了模拟欧洲未来的温度气候学，分析方法的最佳选择是在整个域中使用 MPI 作为 GCM，使用 REMO 或 CCLM5 作为 RCM。根据我们的分析，最好的代表性气候模型组合可以通过在 EURO-CORDEX 域上运行 MPI-CCLM5 组合来执行。