Are trends in total ozone consistent with stratospheric ozone trends from satellite observations? Are trends in total ozone consistent with stratospheric ozone trends from satellite observations?
Bibliographic record
Abstract
Total ozone is a measure of the protection of the biosphere from UV radiation. Extratropical total ozone recovery trends of about +0.5%/decade are consistent with the continuous decline in stratospheric halogen loading since the middle 1990s as a consequence of the Montreal Protocol and its Amendments on phasing out ODS. Nevertheless, the recovery (or chemistry-related) trends in the northern hemisphere (NH) are compensated by changes in atmospheric dynamics leading to stable ozone levels since about 2000 (apart from year-to-year variability). The near-global (60°S-60°N) average total ozone level is currently about 2-3% below the 1964-1980 mean.Lower stratospheric ozone, the dominating contributor to the total ozone column and derived from limb satellite observations, shows globally (below 60° latitude) a slightly negative (but mostly statistically insignificant) trend of about -1.5%/decade since 2000, which is not consistent with the stable total ozone levels in the NH. Some studies suggested that increases in tropospheric ozone compensate for negative lower stratospheric trends leading to stable column levels. The trend regression models applied to ozone profiles and total ozone also differ. For instance, proxies representing changes in atmospheric dynamics and transport have been included for total ozone, but not for ozone profiles, which may also lead to inconsistencies between total and stratospheric column trends.This presentation will report updated total ozone trends from five merged total ozone datasets up to 2022. The same regression model, including proxies representing atmospheric dynamics and transport, will be then applied to ozone profiles from the merged limb dataset (SAGE II-SCIAMACHY-OMPS) to evaluate the consistency between column and profile trends.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".