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本文评估了CMIP5和CMIP6模式对中国在1979-2005年期间的极端温度的模拟性能.结果表明:CMIP6模式可以很好地再现年最大日最高气温,年最小日最低气温和霜冻日数的空间分布特征.对于年最大日最高气温,持续暖日日数和暖昼,CMIP6模式间的不确定性相对于CMIP5模式有所降低.并且,CMIP6模式也能表现出观测到的极端温度的趋势.然而,CMIP6模式再现暖昼和冷夜的能力仍然不足,特别是在青藏高原上存在明显的冷偏差或者暖偏差对于某些指数.单个CMIP6或CMIP5模式的模拟能力就不同的指数而有所不同,某些模式的模拟能力较为突出.对于一些来自同一机构不同版本的模式,改进的CMIP6模式与CMIP5模式的模拟结果没有明显差异.多模式中位数平均的模拟效果优于大多数单个模式.“,”Using the historical simulations from 27 models in phase 5 of the Coupled ModelIntercomparison Project(CMIP5)and 27 models in phase 6(CMIP6),the authors evaluated the differences between CMIP5 and CMIP6 models in simulating the climate mean of extreme temperature over China through comparison with observations during 1979-2005.The CMIP6 models reproduce well the spatial distribution of annual maxima of daily maximum temperature(TXx),annual minima of daily minimum temperature(TNn),and frost days(FD).The model spread in CMIP6 is reduced relative to CMIP5 for some temperature indices,such as TXx,warm spell duration index(WSDI),and warm days(TX90p).The multimodel median ensembles also capture the observed trend of extreme temperature.However,the CMIP6 models still have low skill in capturing TX90p and cold nights(TN1Op)and have obvious cold biases or warm biases over the Tibetan Plateau.The ability of individual models varies for different indices,although some models outperform the others in terms of the average of all indices considered for different models.By comparing different version models from the same organization,the updated CMIP6 models show no significant difference from their counterparts from CMIP5 for some models.Compared with individual models,the median ensembles show better agreement with the observations for temperature indices and their means.