It has become a hot research issue to assess global and regional simulation ability and predict climate change tendency for different emission scenarios with a single model or multiple models [3, 4]. Phillips and Gleckr [6] evaluated the ability of the 20 IPCC-AR4 (the Fourth Assessment Report pathway signaling of the Intergovernmental Panel on Climate Change) models to reproduce global land annual mean precipitation; the result shows that new global climate models have better simulations of global land precipitation than the previous version. Based on the atmospheric circulation features of European climate change, AP van Ulden and van Oldenborgh [7] assessed the simulation ability of global climate models over Europe by calculating spatial correlation between observed and simulated values; the result shows that there are 8 models which have well-projected European atmospheric circulation changes.

Johnson and Sharma [8] assessed the credibility of global climate models in time and space using the ��Variable Convergence Score (VCS)�� method. Sun et al. [9] evaluated the ability of new global climate models to reproduce frequency, intensity, and other indicators of precipitation, which indicated that precipitation was still too frequent in the latest models. Chinese scientists have been working on future climate change assessment in China. Zhou and Yu [10] assessed the ability of the 19 IPCC AR4 models to reproduce precipitation climatology in China; the result shows that new GCMs simulated much better than the previous with regard to China’s climate; most models could represent the average of surface temperature, but the simulation of warming ratio in recent years still needs to be improved.

With the 22 IPCC AR4 models, Xu et al. [11] evaluated ability of various models to reproduce China’s climate changes in the 20th century; and then pointed out that the temperature simulation of each model was better than precipitation, while that multimodel ensembles mean simulated much better than a single model. Jiang et al. [12, 13] analyzed the ability of the IPCC-AR4 models to reproduce precipitation, temperature, and extreme precipitation index and project future climate changes under different emission scenarios in China. In addition, a lot of research has been done by scholars on climate change assessments and projections of GCMs [14�C17]. Messerli and Ives [18] pointed out that mountainous and highland areas were vulnerable and sensitive to climate changes. The climate environments ecosystems in these regions respond most rapidly and significantly to global Batimastat climate changes [19].