Volume 38, Issue 3 p. 1533-1542
Research Article

Multi-decadal evolution characteristics of global surface temperature anomaly data shown by observation and CMIP5 models

Xian Zhu

Xian Zhu

State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, China

Zhuhai Joint Innovative Center for Climate-Environment-Ecosystem, Future Earth Research Institute, Beijing Normal University, Zhuhai, China

Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Chinese Academy of Sciences, Lanzhou, China

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Wenjie Dong

Corresponding Author

Wenjie Dong

School of Atmospheric Sciences, Sun Yat-Sen University, Guangzhou, China

Zhuhai Joint Innovative Center for Climate-Environment-Ecosystem, Future Earth Research Institute, Beijing Normal University, Zhuhai, China

Correspondence to: W. Dong, School of Atmospheric Sciences, Sun Yat-Sen University, Tangjiawan Zhuhai, Guangdong Province, 519087, China. E-mail: [email protected]Search for more papers by this author
Zhigang Wei

Zhigang Wei

State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, China

Zhuhai Joint Innovative Center for Climate-Environment-Ecosystem, Future Earth Research Institute, Beijing Normal University, Zhuhai, China

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Yan Guo

Yan Guo

State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, China

Zhuhai Joint Innovative Center for Climate-Environment-Ecosystem, Future Earth Research Institute, Beijing Normal University, Zhuhai, China

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Xiaoqing Gao

Xiaoqing Gao

Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Chinese Academy of Sciences, Lanzhou, China

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Xiaohang Wen

Xiaohang Wen

State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, China

Zhuhai Joint Innovative Center for Climate-Environment-Ecosystem, Future Earth Research Institute, Beijing Normal University, Zhuhai, China

Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, School of Atmospheric Sciences, Chengdu University of Information Technology, China

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Shili Yang

Shili Yang

State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, China

Zhuhai Joint Innovative Center for Climate-Environment-Ecosystem, Future Earth Research Institute, Beijing Normal University, Zhuhai, China

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Zhiyuan Zheng

Zhiyuan Zheng

School of Atmospheric Sciences, Sun Yat-Sen University, Guangzhou, China

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Dongdong Yan

Dongdong Yan

State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, China

Zhuhai Joint Innovative Center for Climate-Environment-Ecosystem, Future Earth Research Institute, Beijing Normal University, Zhuhai, China

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Yuyao Zhu

Yuyao Zhu

State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, China

Zhuhai Joint Innovative Center for Climate-Environment-Ecosystem, Future Earth Research Institute, Beijing Normal University, Zhuhai, China

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Juan Chen

Juan Chen

Zhuhai Joint Innovative Center for Climate-Environment-Ecosystem, Future Earth Research Institute, Beijing Normal University, Zhuhai, China

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First published: 27 September 2017
Citations: 14

ABSTRACT

Based on methods of statistical analysis, the time series of global surface air temperature (SAT) anomalies from 1860 to 2014 has been defined by three types of phase changes that occur through the division of temperature changes into different stages. The characteristics of the three types of phase changes simulated by Coupled Model Inter-Comparison Project (CMIP5) models were evaluated. The conclusion is as follows: the SAT from 1860 to 2014 can be divided into six stages according to trend differences, and this subdivision is proved to be statistically significant. Based on trend analysis and the distribution of slopes between any two points (two points' slope) in every stage, the six stages can be summarized as three phase changes of warming, cooling, and hiatus. Between 1860 and 2014, the world experienced three heating phases (1860–1878, 1909–1942, and 1975–2004), one cooling phase (1878–1909), and two hiatus phases (1942–1975 and 2004–2014). Using the definition method, whether the next year belongs to the previous phase can be estimated. Furthermore, the temperature in 2015 was used as an example to validate the feasibility of this method. The simulations of the heating period by CMIP5 models are well; however, the characteristics shown by SAT during the cooling and hiatus period cannot be represented by CMIP5 models. As such, the projections of future heating phases using the CMIP5 models are credible, but for cooling and hiatus events they are unreliable.