Temporal changes in the structure of the UTLS and their potential impact on lower stratospheric ozone
Bibliographic record
Abstract
Although a general recovery of stratospheric ozone is expected after the successful implementation of the Montreal Protocol, strong indications for a decline in lower stratospheric ozone in the extratropics are still evident. Related studies attribute this decline to internal dynamic variability affecting the UTLS, in particular associated to the QBO and the exchange of air masses between tropical and extratropical regions. The dynamics affect the transport of ozone from the source region in the tropics into the extratropical lower stratosphere. More so, dynamics affect the structure of the lower stratosphere. In particular, the locations of the tropopause and of isentropic surfaces in the lower stratosphere, i.e., the region up to ~25 km altitude, affect the vertical profile of ozone and as such the integrated column ozone in the lower stratosphere. This study aims to address the relation between the changing altitude of the tropopause and isentropic surfaces in the lower stratosphere and the declining ozone in the extratropical UTLS. For this we use reanalysis data from ECMWF and dynamic linear modeling to study trends of the dynamic tropopause and of the thermodynamical structure and the potential consequences of these trends for lower stratospheric ozone. In particular, we ask the question: do ozone trends still show a decline if we use a dynamic instead of a fixed coordinate system to calculate these trends?
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".