Ozone recovery effects on mesospheric dynamics in the southern hemisphere
Bibliographic record
Abstract
The recovery of Antarctic ozone, primarily driven by the Montreal Protocol, has significantly altered stratospheric circulation. However, its effects on the mesosphere and lower thermosphere (MLT) remain underexplored. Here, we use over a decade of meteor radar observations from Davis (68.6° S, 78.0° E), Rio Grande (53.7° S, 67.7° W), and Rothera (67– 68° S, 68° W), and whole-atmosphere model outputs (GAIA and SD-WACCM-X), complemented by satellite and reanalysis datasets, to assess trends in mesospheric winds. Our results reveal a significant delay in the spring transition from westerly to easterly zonal winds at approximately 82 km. This pattern coincides with changes in gravity wave momentum flux and stratospheric winds, suggesting a link between stratospheric ozone recovery and mesospheric dynamics. Comparisons with reanalysis datasets (MERRA2 and ERA5) further validate these findings despite their limited vertical extent and assimilated observations. Model comparisons reveal that, while both GAIA and SD-WACCM-X models have limitations in reproducing the basic climatology of the mesosphere, GAIA shows a somewhat better agreement with the observed trends. These results highlight the continuing effects of ozone recovery on upper atmospheric circulation and the need for improved representation of wave-driven coupling processes in climate models.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".