Ozone Trends in the Upper Troposphere‐Lower Stratosphere Using Equivalent Latitude‐Potential Temperature Coordinates
Bibliographic record
Abstract
Abstract We analyze ozone trends in the upper troposphere and lower stratosphere (UTLS, 300–50 hPa), using geographical (latitude‐pressure and latitude‐altitude) and, for the first time, dynamical (equivalent latitude‐potential temperature, EqL‐) coordinates. Trends are determined using linear least squares fits, multiple linear regression, and dynamical linear modeling. Regardless of the method, EqL‐ improves consistency between trends across the UTLS, reduces large UT tropical uncertainties, alters the magnitude of mid‐latitude trends, and, most notably, in the Southern polar lower stratosphere, reveals statistically significant trends exceeding 8% per decade during Antarctic Spring. This provides further evidence of Antarctic ozone recovery. These robust trends are not captured using geographical coordinates. We argue that EqL‐ enables more physically grounded interpretations of chemical ozone trends and their uncertainties, as EqL‐ accounts for the adiabatic (reversible) transport of ozone.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".