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Peer-reviewedCC BY 4.0Earth's Future

Cross‐Network Synergies Fundamental to Sustained Global Ocean Carbon Observing

8 more authors

Abstract

The ocean's critical role in absorbing anthropogenic carbon dioxide (CO 2 ) and the resulting changes in the ocean carbon cycle are monitored by global‐scale observing networks, including the Global Ocean Ship‐based Investigations Program (GO‐SHIP), Surface Ocean CO 2 Observing Network (SOCONET), and Biogeochemical‐Argo (BGC‐Argo). Given the scale of the challenge to characterize the evolving ocean carbon cycle, no single network is sufficient; a coordinated, collaborative, cross‐network approach is essential. This manuscript describes the overarching research questions driving these three networks and details their inherent synergies and dependencies, such as GO‐SHIP and SOCONET delivering reference‐quality measurements for validation of other in situ and satellite‐based data, GO‐SHIP providing opportunities for float deployment, and BGC‐Argo filling gaps with high‐frequency autonomous data. We provide recommendations for optimizing these relationships and an intra‐network strategy moving forward. As representatives of the science committees for these networks, we are committed to sustaining and enhancing the collaborative structure necessary to fill critical knowledge gaps in ocean carbon cycle research, improve climate prediction, and enable future ocean ecosystem forecasting.

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BibTeX
@article{sutton2026crossnetwork,
  title = {{Cross‐Network Synergies Fundamental to Sustained Global Ocean Carbon Observing}},
  author = {Adrienne J Sutton and Dorothee C E Bakker and Leticia Barbero and Henry C Bittig and Brendan Carter and Hervé Claustre and Richard A Feely and Masao Ishii and Kenneth S Johnson and Elaine Mcdonagh and Shin‐ichiro Nakaoka and Kevin O’brien and Orens Pasqueron de Fomervault and Christopher Sabine and Richard Sanders and Tobias Steinhoff and Toste Tanhua and Maciej Telszewski and Bronte Tilbrook and Rik Wanninkhof},
  journal = {Earth's Future},
  year = {2026},
  month = oct,
  doi = {10.1029/2026ef008722},
  url = {https://hal.science/hal-05804540v1},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Cross‐Network Synergies Fundamental to Sustained Global Ocean Carbon Observing
AU  - Adrienne J Sutton
AU  - Dorothee C E Bakker
AU  - Leticia Barbero
AU  - Henry C Bittig
AU  - Brendan Carter
AU  - Hervé Claustre
AU  - Richard A Feely
AU  - Masao Ishii
AU  - Kenneth S Johnson
AU  - Elaine Mcdonagh
AU  - Shin‐ichiro Nakaoka
AU  - Kevin O’brien
AU  - Orens Pasqueron de Fomervault
AU  - Christopher Sabine
AU  - Richard Sanders
AU  - Tobias Steinhoff
AU  - Toste Tanhua
AU  - Maciej Telszewski
AU  - Bronte Tilbrook
AU  - Rik Wanninkhof
PY  - 2026
DA  - 2026/10/14
JO  - Earth's Future
DO  - 10.1029/2026ef008722
UR  - https://hal.science/hal-05804540v1
AB  - The ocean's critical role in absorbing anthropogenic carbon dioxide (CO 2 ) and the resulting changes in the ocean carbon cycle are monitored by global‐scale observing networks, including the Global Ocean Ship‐based Investigations Program (GO‐SHIP), Surface Ocean CO 2 Observing Network (SOCONET), and Biogeochemical‐Argo (BGC‐Argo). Given the scale of the challenge to characterize the evolving ocean carbon cycle, no single network is sufficient; a coordinated, collaborative, cross‐network approach is essential. This manuscript describes the overarching research questions driving these three networks and details their inherent synergies and dependencies, such as GO‐SHIP and SOCONET delivering reference‐quality measurements for validation of other in situ and satellite‐based data, GO‐SHIP providing opportunities for float deployment, and BGC‐Argo filling gaps with high‐frequency autonomous data. We provide recommendations for optimizing these relationships and an intra‐network strategy moving forward. As representatives of the science committees for these networks, we are committed to sustaining and enhancing the collaborative structure necessary to fill critical knowledge gaps in ocean carbon cycle research, improve climate prediction, and enable future ocean ecosystem forecasting.
SN  - 2328-4277
SN  - 2328-4277
ER  -