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Assessment of CMIP6 model performance for temperature and precipitation in Xinjiang,China
Authors:Xiaolu Zhang  Lijuan Hua  Dabang Jiang
Affiliation:1. College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, China;2. Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Abstract:In this study, the authors evaluate the skill of 42 climate models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) in reproducing the climatological temperature and precipitation in Xinjiang during the period 1995–2014. The results indicate that the models can reliably capture the geographical distributions of the two variables. The regionally averaged bias of temperature is 0.1°C for the annual mean, ?1.6°C in spring, 0.5°C in summer, ?0.2°C in autumn, and 1.3°C in winter. Regionally averaged annual and seasonal precipitation in Xinjiang is generally overestimated by the CMIP6 models. The simulated annual precipitation is 89% more than the observation over Xinjiang, with a regionally averaged bias of 256% in spring, ?3% in summer, 84% in autumn, and 258% in winter. Quantitative analysis indicates that most models overestimate the spatial variability of both climatological temperature and precipitation. The models show smaller discrepancies in simulating the temperature than the precipitation in Xinjiang. In comparison, both the median and arithmetic mean of the 42 models have similar skills to those of 29 selected good models, and outperform most individual models.摘要作者使用国际耦合模式比较计划第六阶段 (CMIP6) 的历史模拟试验数据, 评估了42个全球气候模式对1995–2014年新疆温度和降水气候态的模拟能力. 结果表明, CMIP6模式能够合理模拟新疆年和季节的温度和降水气候态的空间分布. 相较于观测, 多模式中位数的年均, 春季, 夏季, 秋季和冬季区域平均温度偏差分别为0.1°C, ?1.6°C, 0.5°C, ?0.2°C和1.3°C; 模式普遍高估新疆降水, 区域平均偏差分别为89%, 256%, ?3%, 84%和258%. 定量化的评估表明, 大多数模式模拟的新疆温度和降水空间变率偏大; 42个模式中位数和算数平均的模拟能力与29个优选模式的近似, 并且好于大多数单个模式.
Keywords:CMIP6  Evaluation  Temperature  Precipitation  Xinjiang
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