![Sample our Environment & Sustainability journals, sign in here to start your access, latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5935/TOC-Subject-Sample-2021-Environment-Sustainability.jpg"})
Abstract
Based on a 10-year simulation of six Regional Climate Models (RCMs) in phase II of the Regional Climate 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 precipitation simulated by multi-RCMs over China, including the mean climate states and their seasonal transition, the spatial distribution of interannual variability, and the interannual 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 simulation results. The results of CPC analyses show that the climatological means and the characteristics of seasonal transition over China can be accurately simulated by RCMs. However, large biases exist in the interannual variation in certain years or for individual models.