Articles | Volume 23, issue 3
https://doi.org/10.5194/bg-23-967-2026
https://doi.org/10.5194/bg-23-967-2026
Research article
 | 
03 Feb 2026
Research article |  | 03 Feb 2026

Reconstruction and spatiotemporal analysis of global surface ocean pCO2 considering sea area characteristics

Huisheng Wu, Yunlong Ji, Lejie Wang, Xiaoke Liu, Wenliang Zhou, Long Cui, Yang Wang, Min Liu, and Zhuang Li

Cited articles

Chau, T. T. T., Gehlen, M., and Chevallier, F.: A seamless ensemble-based reconstruction of surface ocean pCO2 and air–sea CO2 fluxes over the global coastal and open oceans, Biogeosciences, 19, 1087–1109, https://doi.org/10.5194/bg-19-1087-2022, 2022. 
Chau, T. T. T., Chevallier, F., and Gehlen, M.: Global analysis of surface ocean CO2 fugacity and air-sea fluxes with low latency, Geophys. Res. Lett, 51, e2023GL106670, https://doi.org/10.1029/2023GL106670, 2024. 
Chen, S., Hu, C., Barnes, B. B., Wanninkhof, R., Cai, W.-J., Barbero, L., and Pierrot, D.: A machine learning approach to estimate surface ocean pCO2 from satellite measurements, Remote Sens. Environ, 228, 203–226, https://doi.org/10.1016/j.rse.2019.04.019, 2019. 
Chierici, M., Signorini, S. R., Mattsdotter-Björk, M., Fransson, A., and Olsen, A.: Surface water fCO2 algorithms for the high-latitude Pacific sector of the Southern Ocean, Remote Sens. Environ., 119, 184–196, https://doi.org/10.1016/j.rse.2011.12.020, 2012. 
Falkowski, P., Scholes, R. J., Boyle, E., Canadell, J., Canfield, D., Elser, J., and Linder, S.: The global carbon cycle: a test of our knowledge of earth as a system, Sciences, 290, 291–296, https://doi.org/10.1126/science.290.5490.291, 2000. 
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Short summary
This study reconstructs global ocean surface pCO2 (2000–2019) using multi-source data and machine learning, identifying Random Forest (RF) as the optimal model and revealing equatorial-high/polar-low patterns with rising trends.
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