A monthly surface <i>p</i>CO<sub>2</sub> product for the California Current Large Marine Ecosystem

Sharp, Jonathan D.; Fassbender, Andrea J.; Carter, Brendan R.; Lavin, Paige D.; Sutton, Adrienne J.

doi:https://doi.org/10.5194/essd-14-2081-2022

Articles | Volume 14, issue 4

https://doi.org/10.5194/essd-14-2081-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/essd-14-2081-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 14, issue 4

Data description paper

|

29 Apr 2022

Data description paper |

| 29 Apr 2022

A monthly surface pCO₂ product for the California Current Large Marine Ecosystem

Jonathan D. Sharp, Andrea J. Fassbender, Brendan R. Carter, Paige D. Lavin, and Adrienne J. Sutton

Data sets

RFR-CCS: A monthly surface pCO2 product for the California Current Large Marine Ecosystem Jonathan D. Sharp, Andrea J. Fassbender, Brendan R. Carter, Paige D. Lavin, and Adrienne J. Sutton https://doi.org/10.5281/zenodo.5523389

Model code and software

RFR-CCS Jonathan D. Sharp https://doi.org/10.5281/zenodo.6484875

Short summary

Oceanographers calculate the exchange of carbon between the ocean and atmosphere by comparing partial pressures of carbon dioxide (pCO₂). Because seawater pCO₂ is not measured everywhere at all times, interpolation schemes are required to fill observational gaps. We describe a monthly gap-filled dataset of pCO₂ in the northeast Pacific Ocean off the west coast of North America created by machine-learning interpolation. This dataset is unique in its robust representation of coastal seasonality.