Interannual-to-decadal variability of the Southern Ocean carbon uptake in a high-resolution ocean biogeochemistry model 
Bibliographic record
Abstract
Recent studies point to pronounced decadal variability in the Southern Ocean carbon sink over the past decades, but the mechanisms are still not fully understood. In this study, the regional patterns and bio-physical drivers of the interannual-to-decadal variability of the air-sea CO2 fluxes in the Antarctic Circumpolar Current (ACC) are investigated. A suite of global ocean biogeochemistry configurations (based on the NEMO-MOPS model) is used to perform hindcast experiments covering the period 1958-2018. The configurations include a non-eddying 0.5° model, an eddy-permitting 0.25° model, and a global 0.5° model featuring an eddy-rich 0.1° nest between 30°S and 68°S. The 0.25° model is also used to perform additional sensitivity experiments, where the variability of the wind stress or of the buoyancy forcing is suppressed on interannual time scales. All simulations show a positive trend in the air-sea CO2 fluxes over ACC, with a weaker rate of increase in the 1970s and in the 1990s, and a stronger rate of increase in the 1980s and 2000s. The interannual and decadal variability of air-sea CO2 fluxes is highest in frontal regions of the ACC, especially in the Southeast Pacific basin. Wind stress emerges as the dominant driver of the large interannual and decadal variability of air-sea CO2 fluxes at subpolar latitudes. On the other hand, air-sea buoyancy fluxes gain more relevance at middle latitudes. The simulations highlight the relevant role of explicitly simulating ocean mesoscale eddies for the Southern Ocean carbon uptake. Indeed, the 0.1º model shows a steeper trend of the Southern Ocean carbon uptake with respect to the lower-resolution models, driven to a large extent by a higher uptake of anthropogenic carbon.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".