中文摘要：

在地区性的气候模型的阶段 II 基于六个地区性的气候模型( RCM )的10年的模拟为亚洲的内部比较的工程( RMIP )，部件( CPC )被用来分析并且比较温度和 降水的空间与时间的特征的普通主管的统计方法在中国上由 multi-RCMs 模仿了的 multivariate 包括吝啬的气候国家和他们的季节的转变， interannual 可变性的空间分发，和 interannual 变化。CPC 是为分析不同模型的结果的一个有效统计工具。与传统的统计方法相比， CPC 分析为观察和模拟结果提供一幅更完全的统计图画。climatological 意味着的 CPC 分析表演和特征的结果季节转移中国能被 RCM 精确地模仿。然而，大偏爱在某些年里或为单个模型在 interannual 变化存在。

英文摘要：

Based on a 10-year simulation of six Regional Climate Models （RCMs） in phase II of the Regional Cli- mate Model Inter-Comparison Project （RMIP） for Asia, the multivariate statistical method of common principal components （CPCs） is used to analyze and compare the spatiotemporal characteristics of temperature and precipi- tation simulated by multi-RCMs over China, including the mean climate states and their seasonal transition, the spatial distribution of interannual variability, and the in- terannual variation. CPC is an effective statistical tool for analyzing the results of different models. Compared with traditional statistical methods, CPC analyses provide a more complete statistical picture for observation and si- mulation results. The results of CPC analyses show that the climatological means and the characteristics of sea- sonal transition over China can be accurately simulated by RCMs. However, large biases exist in the interannual variation in certain years or for individual models.