Articles | Volume 14, issue 4
https://doi.org/10.5194/essd-14-2081-2022
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, Andrea J. Fassbender, Brendan R. Carter, Paige D. Lavin, and Adrienne J. Sutton

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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 | EF: Editorial file upload
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
AR by Jonathan Sharp on behalf of the Authors (06 Apr 2022)
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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.
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