Global monthly gridded atmospheric carbon dioxide concentrations under the historical and future scenarios

Wei Cheng; Li Dan; Xiangzheng Deng; Jinming Feng; Yongli Wang; Jing Peng; Jing Tian; Wei Qi; Zhu Liu; Xinqi Zheng; Demin Zhou; Sijian Jiang; Haipeng Zhao; Xiaoyu Wang

doi:10.1038/s41597-022-01196-7

Global monthly gridded atmospheric carbon dioxide concentrations under the historical and future scenarios

Sci Data. 2022 Mar 11;9(1):83. doi: 10.1038/s41597-022-01196-7.

Authors

Wei Cheng^{1

2}, Li Dan³, Xiangzheng Deng^{4

5

6}, Jinming Feng⁷, Yongli Wang⁸, Jing Peng⁷, Jing Tian⁹, Wei Qi¹⁰, Zhu Liu¹¹, Xinqi Zheng^{12

13}, Demin Zhou^{14

15}, Sijian Jiang^{1

2}, Haipeng Zhao^{12

13}, Xiaoyu Wang^{14

15}

Affiliations

¹ Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
² Key Laboratory of Land Surface Pattern and Simulation, Chinese Academy of Sciences, Beijing, 100101, China.
³ Key Lab of Regional Climate-Environment for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China. danli@tea.ac.cn.
⁴ Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China. dengxz@igsnrr.ac.cn.
⁵ Key Laboratory of Land Surface Pattern and Simulation, Chinese Academy of Sciences, Beijing, 100101, China. dengxz@igsnrr.ac.cn.
⁶ University of Chinese Academy of Sciences, Beijing, 100049, China. dengxz@igsnrr.ac.cn.
⁷ Key Lab of Regional Climate-Environment for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China.
⁸ Key Lab of Regional Climate-Environment for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China. wangyl@tea.ac.cn.
⁹ Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China. tianj.04b@igsnrr.ac.cn.
¹⁰ Institute of Tibetan Plateau and Polar Meteorology, Chinese Academy of Meteorological Sciences, Beijing, 100081, China.
¹¹ Department of Earth System Science, Tsinghua University, Beijing, 100084, China.
¹² School of Information Engineering, China University of Geosciences, Beijing, 100083, China.
¹³ Technology Innovation Center of Territory Spatial Big-data, MNR of China, Beijing, 100036, China.
¹⁴ College of Resource, Environment and Tourism, Capital Normal University, Beijing, 100048, China.
¹⁵ Key Laboratory of 3D Information Acquisition and Application of Ministry, Capital Normal University, Beijing, 100048, China.

Abstract

Increases in atmospheric carbon dioxide (CO₂) concentrations is the main driver of global warming due to fossil fuel combustion. Satellite observations provide continuous global CO₂ retrieval products, that reveal the nonuniform distributions of atmospheric CO₂ concentrations. However, climate simulation studies are almost based on a globally uniform mean or latitudinally resolved CO₂ concentrations assumption. In this study, we reconstructed the historical global monthly distributions of atmospheric CO₂ concentrations with 1° resolution from 1850 to 2013 which are based on the historical monthly and latitudinally resolved CO₂ concentrations accounting longitudinal features retrieved from fossil-fuel CO₂ emissions from Carbon Dioxide Information Analysis Center. And the spatial distributions of nonuniform CO₂ under Shared Socio-economic Pathways and Representative Concentration Pathways scenarios were generated based on the spatial, seasonal and interannual scales of the current CO₂ concentrations from 2015 to 2150. Including the heterogenous CO₂ distributions could enhance the realism of global climate modeling, to better anticipate the potential socio-economic implications, adaptation practices, and mitigation of climate change.