A machine-learning reconstruction of sea surface <i>p</i>CO<sub>2</sub> in the North American Atlantic Coastal Ocean Margin from 1993 to 2021

Wu, Zelun; Lu, Wenfang; Roobaert, Alizée; Song, Luping; Yan, Xiao-Hai; Cai, Wei-Jun

doi:https://doi.org/10.5194/essd-17-43-2025

Articles | Volume 17, issue 1

https://doi.org/10.5194/essd-17-43-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/essd-17-43-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 17, issue 1

Data description paper

|

08 Jan 2025

Data description paper |

| 08 Jan 2025

A machine-learning reconstruction of sea surface pCO₂ in the North American Atlantic Coastal Ocean Margin from 1993 to 2021

Zelun Wu, Wenfang Lu, Alizée Roobaert, Luping Song, Xiao-Hai Yan, and Wei-Jun Cai

Data sets

A Reconstructed Coastal Acidification Database (ReCAD) pCO2 data product for the North American Atlantic Coastal Ocean Margins Zelun Wu et al. https://doi.org/10.5281/zenodo.14038561

Model code and software

ReCAD Zelun Wu https://github.com/zelunwu/ReCAD

Short summary

This study addresses the lack of comprehensive sea surface partial pressure of CO₂ (pCO₂) data in the North American Atlantic Coastal Ocean Margin (NAACOM) by developing the Reconstructed Coastal Acidification Database (ReCAD-NAACOM-pCO₂). The product reconstructed sea surface pCO₂ from 1993 to 2021 using machine-learning and environmental data, capturing seasonal cycles, regional variations, and long-term trends of pCO₂for coastal carbon research.

A machine-learning reconstruction of sea surface pCO2 in the North American Atlantic Coastal Ocean Margin from 1993 to 2021

Data sets

Model code and software

A machine-learning reconstruction of sea surface pCO₂ in the North American Atlantic Coastal Ocean Margin from 1993 to 2021