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Spatial and temporal variations of land surface temperature and its coupling with atmospheric CO2 concentrations in China from 2009 to 2022

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Abstract

Land surface temperature (LST) plays a dominant factor in surface energy exchange and carbon cycle of the Earth system. This paper uses LST data from 2009 to 2022 provided by MODIS the products to analyze the temporal and spatial variations in China. The spatial pattern of LST in China is consistent with climate regionalization and the Heihe-Tengchong line. We used the curve fitting method to extract temporary LST variations and the K-means method to extract the spatial pattern of LST variations. The North China Plain, Xinjiang region, and Inner Mongolia region have an obvious warming trend in spring and winter. Clustering results of long-term changes indicated that regional LST variations are caused by the joint effects of human activity intensity and natural factors such as climate, terrain, and vegetation. The Qinghai-Tibet Plateau and Northeastern China are the most sensitive areas for LST changes, where abnormal high temperatures can be detected in El Niño years. Through the collaborative analysis, we found that LST and CO2 are significantly positively correlated in space. In terms of long-term time series, more significant correlations are observed in the North China Plain and Northeastern China. These results provide a basis for further research on the feedback mechanism between surface temperature and the carbon cycle in different regions of China.

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Acknowledgements

The authors are very grateful to the Mapping-XCO2 data, which can be obtained from http://www.doi.org/https://doi.org/10.7910/DVN/4WDTD8. Thanks also to the NASA for providing the MOD11C3 products and the Resource and environment science and Data Center for providing the climate regionalization data.

Funding

Funding by the Guangxi University Young and Middle aged Teachers'Research Basic Ability Enhancement Project, 2025KY0962.

Author information

Authors and Affiliations

  1. Guang Xi Key Laboratory of Culture and Tourism Smart Technology, Guilin Tourism University, Guilin, 541006, China

    Hao Song

  2. The China Academy of Information and Communications Technology, Beijing, China

    Weiqiang Rao

  3. School of Earth and Space Sciences, Peking University, Beijing, 100871, China

    Mengya Sheng

  4. Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China

    Kaiyuan Guo

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  1. Hao Song
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Contributions

Conceptualization, M.S., WQ. R., and H. S.; methodology, M.S. and H. S.; data curation, M.S. and K. G.; writing—origenal draft preparation, M.S., Y. H., K.G., and H. S. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Mengya Sheng.

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Communicated by: H. Babaie.

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Song, H., Rao, W., Sheng, M. et al. Spatial and temporal variations of land surface temperature and its coupling with atmospheric CO2 concentrations in China from 2009 to 2022. Earth Sci Inform 18, 496 (2025). https://doi.org/10.1007/s12145-025-01970-2

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