Drivers of past and future Southern Ocean change: Stratospheric ozone versus greenhouse gas impacts
Bibliographic record
Abstract
[1] We study the separate impacts of changing atmospheric greenhouse gas (GHG) and stratospheric ozone concentrations on past (1960–2010) and future (2010–2100) Southern Ocean conditions. To this end we employ a coupled atmosphere-ocean model with interactive stratospheric chemistry. In our model we separately prescribe i) GHGs that monotonically increase to 2100 and ii) ozone depleting substances (ODSs) that rapidly increase to a maximum in 1995 and then slowly return to 1960 values around 2100, following moderate emission scenarios. Past GHG and ODS changes in our model drive, in about equal measure in the annual mean, poleward intensified surface winds which act to strengthen the sub polar meridional ocean circulation cell and Antarctic Circumpolar Current (ACC). Future GHG-induced oceanic changes continue nearly monotonically to 2100, while the ODS-induced ACC transport peaks, and then reverses, a couple of decades after the ODS maximum in 1995. The ODS impact on ACC transport exceeds the corresponding GHG impact up to the second quarter of the 21st century, a result that highlights the importance of often-neglected stratospheric ozone trends for the simulation of the ocean circulation.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".