Preprints
https://doi.org/10.5194/egusphere-2023-2448
https://doi.org/10.5194/egusphere-2023-2448
11 Mar 2024
 | 11 Mar 2024
Status: this preprint is open for discussion.

An optimal transformation method applied to diagnosing the ocean carbon sink

Neill Mackay, Jan Zika, Taimoor Sohail, Richard Williams, Oliver Andrews, and Andrew Watson

Abstract. The ocean carbon sink plays a critical role in climate, absorbing anthropogenic carbon from the atmosphere and mitigating climate change. The sink shows significant variability on decadal timescales, but estimates from models and observations disagree with one another, raising uncertainty over the magnitude of the sink, its variability, and its driving mechanisms. There is a need to reconcile observationally-based estimates of air-sea CO2 fluxes with those of the changing ocean carbon inventory in order to improve our understanding of the sink, and doing so requires knowledge of how carbon is transported within the interior by the ocean circulation. Here we employ a recently developed Optimal Transformation Method (OTM) that uses water mass theory to relate interior changes in tracer distributions to transports and mixing and boundary forcings, and extend its application to include carbon using synthetic data. We validate the method using model outputs from a biogeochemical state estimate, and test its ability to recover boundary carbon fluxes and interior transports consistent with changes in heat, salt and carbon. Our results show that OTM effectively reconciles boundary carbon fluxes with interior carbon distributions when given a range of prior fluxes. OTM shows considerable skill in its reconstructions, reducing root-mean-squared errors from biased priors between model ‘truth’ and reconstructed boundary carbon fluxes by up to 71 %, with bias of the reconstructions consistently ≤ 0.06 mol-Cm−2 yr−1 globally. Inter-basin transports of carbon also compare well with the model truth, with residuals < 0.25 Pg C yr−1 for reconstructions produced using a range of priors. OTM has significant potential for application to reconciling observational estimates of air-sea CO2 fluxes with the interior accumulation of anthropogenic carbon.

Neill Mackay, Jan Zika, Taimoor Sohail, Richard Williams, Oliver Andrews, and Andrew Watson

Status: open (until 08 May 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-2448', Anonymous Referee #1, 03 Apr 2024 reply
Neill Mackay, Jan Zika, Taimoor Sohail, Richard Williams, Oliver Andrews, and Andrew Watson
Neill Mackay, Jan Zika, Taimoor Sohail, Richard Williams, Oliver Andrews, and Andrew Watson

Viewed

Total article views: 188 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
125 50 13 188 9 8
  • HTML: 125
  • PDF: 50
  • XML: 13
  • Total: 188
  • BibTeX: 9
  • EndNote: 8
Views and downloads (calculated since 11 Mar 2024)
Cumulative views and downloads (calculated since 11 Mar 2024)

Viewed (geographical distribution)

Total article views: 198 (including HTML, PDF, and XML) Thereof 198 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 13 Apr 2024
Download
Short summary
The ocean absorbs carbon dioxide from the atmosphere, mitigating climate change, but estimates of the uptake do not always agree. There is a need to reconcile these differing estimates, and to improve our understanding of ocean carbon uptake. We present a new method for estimating ocean carbon uptake and test it with model data. The method effectively diagnoses the ocean carbon uptake from limited data, and therefore shows promise for reconciling different observational estimates.