Interaction of chemical and transport processes during the formation of the Arctic stratospheric polar vortex
Bibliographic record
Abstract
Abstract. Dynamical processes during the formation phase of the Arctic polar vortex can introduce considerable interannual variability in the amount of ozone that is incorporated into the vortex. Chemistry in autumn and early winter tends to remove part of that variability because ozone relaxes towards equilibrium. As a quantitative measure of how relevant variable dynamical processes during vortex formation are for the winter ozone abundances above the Arctic we analyze which fraction of an ozone anomaly induced dynamically during vortex formation persists until mid-winter. The work is based on the Lagrangian Chemistry Transport Model ATLAS. Model runs for the winter 1999–2000 are used to assess the fate of an ozone anomaly artificially introduced during the vortex formation phase. From these runs we get detailed information about the persistence of the induced ozone variability over time, height and latitude. Induced ozone variability survives longer inside the polar vortex compared to outside. At 540 K inside the polar vortex half of the initial perturbation survives until mid-winter (3 January) with a rapid fall off towards higher levels, mainly due to NOx induced chemistry. At 660 K 10% of the initial perturbation survives. Above 750 K the signal falls to values below 0.5%. Hence, dynamically induced ozone variability from the vortex formation phase can not significantly contribute to mid-winter variability at levels 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 mid-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 | 0.000 |
| 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 | 0.001 | 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".