Articles | Volume 14, issue 4
Earth Syst. Sci. Data, 14, 2081–2108, 2022
https://doi.org/10.5194/essd-14-2081-2022
Earth Syst. Sci. Data, 14, 2081–2108, 2022
https://doi.org/10.5194/essd-14-2081-2022
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 et al.

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Review of Sharp et al „A monthly surface pCO2 product for the California Current Large Marine Ecosystem”', Anonymous Referee #1, 15 Nov 2021
  • RC2: 'Reviewer Comment on essd-2021-328', Anonymous Referee #2, 31 Jan 2022
  • RC3: 'Comment on essd-2021-328', Anonymous Referee #3, 05 Mar 2022
  • AC1: 'Response to Reviewer Comments for essd-2021-328', Jonathan Sharp, 02 Apr 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Jonathan Sharp on behalf of the Authors (02 Apr 2022)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (06 Apr 2022) by Anton Velo
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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.