Data-based estimates of ocean carbon uptake biased high from neglect of submonthly atmospheric pressure…

Abstract

Current estimates of the global ocean carbon sink based on measurements of CO 2 fugacity are inconsistent with those obtained from global ocean biogeochemistry models. Here we investigate how this gap might change by more fully accounting for submonthly variability in observation-based estimates, a step closer to the roughly hourly frequencies used in models. While these data-based estimates use hourly to 6-hourly wind speeds to compute the air-sea CO 2 flux, other input variables are available only at monthly resolution. Thus, they neglect high-frequency variability in key variables such as atmospheric pressure associated with synoptic events such as storms. To evaluate this error, we compare flux estimates from observational data sets with different temporal resolutions. Accounting for hourly variations in atmospheric pressure and daily variations in sea surface temperature, a data-based approach reduces the estimated global carbon uptake by 0.12 Pg C yr −1 , closing 25 % of the average gap between observation-based and model estimates. This reduction results from proper accounting of the covariance between wind speed and atmospheric pressure, particularly in the southern extratropics.

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BibTeX RIS

BibTeX

@article{dombret2026databased,
  title = {{Data-based estimates of ocean carbon uptake biased high from neglect of submonthly atmospheric pressure variability}},
  author = {Jeanne Dombret and Hugo Bellenger and Xavier Perrot and Laëtitia Parc and Lester Kwiatkowski and Frédéric Chevallier and Laurent Bopp and Marion Gehlen and Roland Séférian and Sarah Berthet and James Orr},
  journal = {Biogeosciences},
  year = {2026},
  month = oct,
  doi = {10.5194/bg-23-4133-2026},
  url = {https://cnrs.hal.science/hal-05759958v1},
  note = {CC BY 4.0},
}

RIS

TY  - JOUR
TI  - Data-based estimates of ocean carbon uptake biased high from neglect of submonthly atmospheric pressure variability
AU  - Jeanne Dombret
AU  - Hugo Bellenger
AU  - Xavier Perrot
AU  - Laëtitia Parc
AU  - Lester Kwiatkowski
AU  - Frédéric Chevallier
AU  - Laurent Bopp
AU  - Marion Gehlen
AU  - Roland Séférian
AU  - Sarah Berthet
AU  - James Orr
PY  - 2026
DA  - 2026/10/05
JO  - Biogeosciences
DO  - 10.5194/bg-23-4133-2026
UR  - https://cnrs.hal.science/hal-05759958v1
AB  - Current estimates of the global ocean carbon sink based on measurements of CO 2 fugacity are inconsistent with those obtained from global ocean biogeochemistry models. Here we investigate how this gap might change by more fully accounting for submonthly variability in observation-based estimates, a step closer to the roughly hourly frequencies used in models. While these data-based estimates use hourly to 6-hourly wind speeds to compute the air-sea CO 2 flux, other input variables are available only at monthly resolution. Thus, they neglect high-frequency variability in key variables such as atmospheric pressure associated with synoptic events such as storms. To evaluate this error, we compare flux estimates from observational data sets with different temporal resolutions. Accounting for hourly variations in atmospheric pressure and daily variations in sea surface temperature, a data-based approach reduces the estimated global carbon uptake by 0.12 Pg C yr −1 , closing 25 % of the average gap between observation-based and model estimates. This reduction results from proper accounting of the covariance between wind speed and atmospheric pressure, particularly in the southern extratropics.
SN  - 1726-4170
SN  - 1726-4189
ER  -

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