Persistence of ozone anomalies in the Arctic stratospheric vortex in autumn
Bibliographic record
Abstract
Abstract. Dynamical processes during the formation phase of the Arctic stratospheric vortex in autumn (from September to December) can introduce considerable interannual variability in the amount of ozone that is incorporated into the vortex. Chemistry in autumn tends to remove part of this variability because ozone relaxes towards equilibrium. As a quantitative measure of how important dynamical variability during vortex formation is for the winter ozone abundances above the Arctic we analyze which fraction of an ozone anomaly induced during vortex formation persists until early winter (3 January). The work is based on the Lagrangian Chemistry Transport Model ATLAS. In a case study, model runs for the winter 1999–2000 are used to assess the fate of an ozone anomaly artificially introduced during the vortex formation phase on 16 September. In addition, runs with reduced resolution explore the sensitivity of the results to interannual changes in transport, mixing, temperatures and NOx. The runs provide information about the persistence of the induced ozone anomaly as a function of time, potential temperature and latitude. The induced ozone anomaly survives longer inside the polar vortex than outside the vortex. Half of the initial perturbation survives until 3 January at 550 K inside the polar vortex, with a rapid fall off towards higher levels, mainly due to NOx induced chemistry. Above 750 K the signal falls to values below 0.5%. Hence, dynamically induced ozone variability from the early vortex formation phase cannot significantly contribute to early winter variability above 750 K. At lower levels increasingly larger fractions of the initial perturbation survive, reaching 90% at 450 K. In this vertical range dynamical processes during the vortex formation phase are crucial for the ozone abundance in early winter.
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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 | 0.000 |
| 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) | 0.000 | 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".