Volume 38, Issue S1 p. e466-e474
Research Article

Global land surface air temperature dynamics since 1880

Jinfeng Wang,

Corresponding Author

Jinfeng Wang

State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China

Correspondence to: J. Wang, State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, A11, Datun Road, Beijing 100101, China. E-mail: wangjf@lreis.ac.cnSearch for more papers by this author
Chengdong Xu,

Chengdong Xu

State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China

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Maogui Hu,

Maogui Hu

State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China

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Qingxiang Li,

Qingxiang Li

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

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Zhongwei Yan,

Zhongwei Yan

START Regional Center for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China

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Phil Jones,

Phil Jones

Climatic Research Unit, University of East Anglia, Norwich, UK

Center of Excellence for Climate Change Research, Department of Meteorology, King Abdulaziz University, Jeddah, Saudi Arabia

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First published: 14 December 2017
Citations: 12

ABSTRACT

The geographical extent, magnitude, and uncertainty of global climate change have been widely discussed and have critical policy implications at both global and local scales. In this study, a new analysis of annual mean global land surface air temperature since 1880 was generated, which has greater coverage and lower uncertainty than previous distributions. The Biased Sentinel Hospitals Areal Disease Estimation (BSHADE) method, used in this study, makes a best linear unbiased estimation (BLUE) when a sample is small and biased to a spatially heterogeneous population. For the period of 1901–2010, the warming trend was found to be 0.109 °C decade−1 with 95% confidence intervals between 0.081 °C and 0.137 °C. Additionally, warming exhibited different spatial patterns in different periods. In the early 20th century (1923–1950), warming occurred mainly in the mid-high latitudes of the Northern Hemisphere, whereas in the most recent decades (1977–2014), warming was more spatially extensive across the global land surface. Compared with other common methods, the difference in results appears in the areas with few stations and in the early years, when stations had sparse coverage and were unevenly distributed. Validation, which was performed using real data that simulated the historic situation, showed a smaller error in the BSHADE estimate than in other methods. This study produced a new database with greater coverage and less uncertainty that will improve the understanding of climate dynamics on the Earth since 1880, especially in isolated areas and early periods, and will benefit the assessment of climate-change-related issues, such as the effects of human activities.