Articles | Volume 15, issue 4
https://doi.org/10.5194/essd-15-1711-2023
https://doi.org/10.5194/essd-15-1711-2023
Data description paper
 | 
17 Apr 2023
Data description paper |  | 17 Apr 2023

Spatial reconstruction of long-term (2003–2020) sea surface pCO2 in the South China Sea using a machine-learning-based regression method aided by empirical orthogonal function analysis

Zhixuan Wang, Guizhi Wang, Xianghui Guo, Yan Bai, Yi Xu, and Minhan Dai

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Cited articles

Bai, Y., Cai, W., He, X., Zhai, W., Pan, D., Dai, M., and Yu, P.: A mechanistic semi-analytical method for remotely sensing sea surface pCO2 in river-dominated coastal oceans: A case study from the East China Sea, J. Geophys. Res.-Oceans, 120, 2331–2349, 2015. 
Cao, Z., Dai, M., Zheng, N., Wang, D., Li, Q., Zhai, W., Meng, F., and Gan, J.: Dynamics of the carbonate system in a large continental shelf system under the influence of both a river plume and coastal upwelling, J. Geophys. Res.-Biogeo., 116, G02010, https://doi.org/10.1029/2010JG001596, 2011. 
Cao, Z., Yang, W., Zhao, Y., Guo, X., Yin, Z., Du, C., Zhao, H., and Dai, M.: Diagnosis of CO2 dynamics and fluxes in global coastal oceans, Natl. Sci. Rev., 7, 786–797, 2020. 
Chen, C. and Borges, A. V.: Reconciling opposing views on carbon cycling in the coastal ocean: Continental shelves as sinks and near-shore ecosystems as sources of atmospheric CO2, Deep-Sea Res. Pt. I, 56, 578–590, 2009. 
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We reconstructed monthly sea surface pCO2 data with a high spatial resolution in the South China Sea (SCS) from 2003 to 2020. We validate our reconstruction with three independent testing datasets and present a new method to assess the uncertainty of the data. The results strongly suggest that our reconstruction effectively captures the main features of the spatiotemporal patterns of pCO2 in the SCS. Using this dataset, we found that the SCS is overall a weak source of atmospheric CO2.
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