Physical drivers of the recent Southern Ocean carbon uptake in an eddying ocean
Bibliographic record
Abstract
<!--!introduction!--> Owing to its cool temperatures and vigorous water mass formation, the strongly eddying Southern Ocean is a key region of ocean CO2 uptake. In this study we assess the role of 1) wind stress and buoyancy forcing and 2) the representation of mesoscale eddies, in affecting the mean and temporal variations of the Southern Ocean carbon uptake in the past 60 years. We analyze global ocean biogeochemistry simulations based on the NEMO-MOPS and FESOM-REcoM models and ranging from 1° and 0.5° resolutions (where eddies are parameterized) to eddy-rich 0.25° and 0.1° resolutions. The 0.25° model is also used to perform sensitivity experiments to unravel the relative role of wind stress and of buoyancy forcing for the carbon uptake variations. We find that eddy-rich models have steeper isopycnals across the Antarctic Circumpolar Current, which results in higher anthropogenic carbon uptake and storage than in models where eddies are parameterized. This, in combination with a somewhat lower outgassing of natural CO2, gives rise to a steeper trend of the Southern Ocean carbon uptake in the eddy-rich than in the eddy-parameterized models. Wind stress and buoyancy forcing are the main drivers of an increased outgassing of natural CO2 over the past decades and drive most of its interannual and decadal variability, with wind stress dominating at subpolar latitudes, and buoyancy forcing in water mass formation regions. However, our experiments indicate that the stalling of the Southern Ocean carbon uptake in the 1990s was mostly driven by a reduction of its anthropogenic carbon uptake.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".