State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, Beijing, People's Republic of China.
PLoS One. 2012;7(9):e44659. doi: 10.1371/journal.pone.0044659. Epub 2012 Sep 19.
Global Circulation Models (GCMs) contributed to the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) and are widely used in global change research. This paper assesses the performance of the AR4 GCMs in simulating precipitation and temperature in China from 1960 to 1999 by comparison with observed data, using system bias (B), root-mean-square error (RMSE), Pearson correlation coefficient (R) and Nash-Sutcliffe model efficiency (E) metrics. Probability density functions (PDFs) are also fitted to the outputs of each model. It is shown that the performance of each GCM varies to different degrees across China. Based on the skill score derived from the four metrics, it is suggested that GCM 15 (ipsl_cm4) and GCM 3 (cccma_cgcm_t63) provide the best representations of temperature and precipitation, respectively, in terms of spatial distribution and trend over 10 years. The results also indicate that users should apply carefully the results of annual precipitation and annual temperature generated by AR4 GCMs in China due to poor performance. At a finer scale, the four metrics are also used to obtain best fit scores for ten river basins covering mainland China. Further research is proposed to improve the simulation accuracy of the AR4 GCMs regarding China.
全球环流模型（GCMs）为政府间气候变化专门委员会第四次评估报告（AR4）做出了贡献，并广泛应用于全球变化研究。本文通过与观测数据的比较，使用系统偏差（B）、均方根误差（RMSE）、皮尔逊相关系数（R）和纳什-苏特克里夫模型效率（E）等指标，评估了 AR4 GCMs 在模拟 1960 年至 1999 年中国降水和温度方面的性能。还对每个模型的输出进行了概率密度函数（PDF）拟合。结果表明，每个 GCM 在整个中国的表现存在不同程度的差异。根据四个指标得出的技能得分，建议 GCM 15（ipsl_cm4）和 GCM 3（cccma_cgcm_t63）在空间分布和 10 年趋势方面分别对温度和降水的表现最好。结果还表明，由于表现不佳，用户在中国应谨慎使用 AR4 GCMs 生成的年降水量和年温度的结果。在更细的尺度上，还使用这四个指标为覆盖中国大陆的十个流域获得了最佳拟合分数。进一步的研究被提出以提高 AR4 GCMs 对中国的模拟精度。
