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CMIP6模式中的中国冬季气温主要区域空间模态及与观测的对比分析
引用本文:陈金琪,胡景高,徐海明,郭栋.CMIP6模式中的中国冬季气温主要区域空间模态及与观测的对比分析[J].气象科学,2023,43(6):736-748.
作者姓名:陈金琪  胡景高  徐海明  郭栋
作者单位:南京信息工程大学 气象灾害教育部重点实验室/气候与环境变化国际合作联合实验室/气象灾害预报预警与评估协同创新中心, 南京 210044;内蒙古自治区气候中心, 呼和浩特 010051;南京信息工程大学 气象灾害教育部重点实验室/气候与环境变化国际合作联合实验室/气象灾害预报预警与评估协同创新中心, 南京 210044;南京信息工程大学雷丁学院, 南京 210044
基金项目:国家重点研发计划资助项目(2018YFC1505602);国家自然科学基金资助项目(41975048;41975106;42030605);江苏省自然科学基金资助项目(BK20191404)
摘    要:利用国际耦合模式比较计划第六阶段(CMIP6)的全球气候模式历史模拟试验资料,通过旋转经验正交函数分析得到了CMIP6模式中的我国冬季气温变化主要的区域空间模态。结果表明:CMIP6多模式集合平均中我国冬季气温有4个主要的区域空间模态,分别为中原—西北型,华南型,东北型以及滇藏型。其中,东北型与滇藏型是较为稳定的空间模态,在所选CMIP6模式及观测资料中都稳定存在,这也是前人研究中一致性较高的模态。而我国新疆、西北、华中及华南地区的冬季气温在空间分型上存在分歧,这些地区的分型在以往研究中的一致性也较差。华南型在所选CMIP6模式内是一致存在的模态,中原—西北型在模式内部的差异性较大。在近40 a观测资料中,新疆及西北到我国南方为统一的空间分型,在CMIP6多模式集合平均的结果中新疆及西北地区气温空间分布与我国中原地区的联系更为紧密。CMIP6模式能较好地模拟出与低温空间分布有直接联系的对流层中层的槽的位置,当CMIP6模式和观测中的冬季气温都表现为同一个空间模态时,该模态所对应的对流层中层的主要环流系统在观测和CMIP6模式中也是一致的。

关 键 词:CMIP6模式  冬季气温  空间模态  环流特征
收稿时间:2021/9/8 0:00:00
修稿时间:2021/11/15 0:00:00

Main regional spatial modes of winter temperature in China based on CMIP6 and its comparison with observations
CHEN Jinqi,HU Jinggao,XU Haiming,GUO Dong.Main regional spatial modes of winter temperature in China based on CMIP6 and its comparison with observations[J].Scientia Meteorologica Sinica,2023,43(6):736-748.
Authors:CHEN Jinqi  HU Jinggao  XU Haiming  GUO Dong
Institution:Key Laboratory of Meteorological Disaster, Ministry of Education(KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China;Climate Center of Inner Mongolia Autonomous Region, Hohhot 010051, China; Key Laboratory of Meteorological Disaster, Ministry of Education(KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China;Reading Academy, Nanjing University of Information Science & Technology, Nanjing 210044, China
Abstract:In this paper, the main regional spatial modes of winter 2 m air temperature in China were obtained by rotating empirical orthogonal function analysis based on historical simulation of global climate models for phase 6 of the Coupled Model Intercomparison Project (CMIP6). Results show that:the main regional spatial modes of winter 2 m air temperature in China based on CMIP6 multi-model ensemble mean can be classified as four types, namely Central-Northwest mode, South mode, Northeast mode and Yunnan-Tibet mode. Among them, Northeast mode and Yunnan-Tibet mode are relatively stable spatial modes, which exist stably in the selected CMIP6 models and observation data, and are the modes with high consistency in previous studies. However, there are divergences in the spatial classification of winter 2 m air temperature in Xinjiang, Northwest, central and South China, and the consistency of the classification of these regions is poor in previous studies. The South mode appears in all the selected CMIP6 models, while the Central-Northwest mode has great divergences within the models. In the observation data of recent 40 years, the spatial distribution of 2 m air temperature can classify as one mode in Xinjiang, Northwest and South China. However, in the CMIP6 multi-model ensemble mean, the spatial distribution of air temperature in Xinjiang and Northwest China is more closely related to the Central Plains of China. The CMIP6 model has good performance in simulating the location of the trough in the middle troposphere, which is directly related to the spatial distribution of low air temperature in winter. When the CMIP6 models and the observed winter temperature show the same spatial mode, the main circulation system in the middle troposphere associated with the mode is also consistent in the observation and CMIP6 models.
Keywords:CMIP6 models  winter air temperature  spatial pattern  circulation characteristics
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