Specific patterns of XCO2 observed by GOSAT during 2009–2016 and assessed with model simulations over China

  • Nian Bie
  • Liping LeiEmail author
  • Zhonghua He
  • Zhaocheng Zeng
  • Liangyun Liu
  • Bing Zhang
  • Bofeng Cai
Research Paper


Spatiotemporal patterns of column-averaged dry air mole fraction of CO2 (XCO2) have not been well characterized on a regional scale due to limitations in data availability and precision. This paper addresses these issues by examining such patterns in China using the long-term mapping XCO2 dataset (2009–2016) derived from the Greenhouse gases Observing SATellite (GOSAT). XCO2 simulations are also constructed using the high-resolution nested-grid GEOS-Chem model. The following results are found: Firstly, the correlation coefficient between the anthropogenic emissions and XCO2 spatial distribution is nearly zero in summer but up to 0.32 in autumn. Secondly, on average, XCO2 increases by 2.08 ppm every year from 2010 to 2015, with a sharp increase of 2.6 ppm in 2013. Lastly, in the analysis of three typical regions, the GOSAT XCO2 time series is in better agreement with the GEOS-Chem simulation of XCO2 in the Taklimakan Desert region (the least difference with bias 0.65±0.78 ppm), compared with the northern urban agglomeration region (−1.3±1.2 ppm) and the northeastern forest region (−1.4±1.4 ppm). The results are likely attributable to uncertainty in both the satellite-retrieved XCO2 data and the model simulation data.


GEOS-Chem GOSAT OCO-2 Specific pattern XCO2 


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ACOS v7.3 were produced by the ACOS/OCO-2 project at the Jet Propulsion Laboratory, California Institute of Technology, and obtained from the JPL website We are grateful for NASA, ACOS/OCO-2 project, NIES GOSAT Project and geos-chem team. This research was supported by the National Key Research and Development Program of China (Grant No. 2016YFA0600303) and the Key Deployment Projects of the Chinese Academy of Sciences (Grant No. ZDRW-ZS-2019-1-3).


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Copyright information

© Science China Press and Springer-Verlag GmbH Germany, part of Springer Nature 2020

Authors and Affiliations

  • Nian Bie
    • 1
    • 2
  • Liping Lei
    • 1
    Email author
  • Zhonghua He
    • 1
    • 2
  • Zhaocheng Zeng
    • 3
  • Liangyun Liu
    • 1
  • Bing Zhang
    • 1
  • Bofeng Cai
    • 4
  1. 1.Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital EarthChinese Academy of SciencesBeijingChina
  2. 2.University of Chinese Academy of SciencesBeijingChina
  3. 3.Division of Geological and Planetary SciencesCalifornia Institute of TechnologyPasadenaUSA
  4. 4.The Center for Climate Change and Environmental PolicyChinese Academy for Environmental Planning, Ministry of Environmental ProtectionBeijingChina

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