Symptoms of total ozone recovery inside the Antarctic vortex during Austral spring
Bibliographic record
Abstract
Abstract. The long-term evolution of total ozone column inside the Antarctic polar vortex is investigated over the 1980–2016 period. Trend analyses are performed using a multilinear regression (MLR) model based on various proxies (heat flux, Quasi-Biennial Oscillation, solar flux, Antarctic Oscillation and aerosols). Annual total ozone column corresponding to the mean monthly values inside the vortex in September and during the period of maximum ozone depletion from September 15th to October 15th are used. Total ozone columns from combined SBUV, TOMS and OMI satellite datasets and the Multi-Sensor Reanalysis (MSR-2) dataset are considered in the study. Ozone trends are computed by a piecewise trend model (PWT) before and after the turnaround in 2001. In order to evaluate total ozone within the vortex, two classification methods are used, based on the potential vorticity gradient as a function of equivalent latitude. The first standard one considers this gradient at a single isentropic level (475 K or 550 K), while the second one uses a range of isentropic levels between 400 K and 600 K. The regression model includes a new proxy that represents the stability of the vortex during the studied month period. The determination coefficient (R2) between observations and modeled values increases by ~ 0.05 when this proxy is included in the MLR model. The higher R2 (0.93–0.95) and the minimum residuals are observed for the second classification method for both datasets and months periods. Trends in September are statistically significant at 2 sigma level over 2001–2016 period with values ranging between 1.85 and 2.67 DU yr−1 depending on the methods and data sets. This result confirms the recent studies of Antarctic ozone healing during that month. Trends after 2001 are 2 to 3 times lower than before the turnaround year as expected from the response to the slowly ozone-depleting substances decrease in Polar regions. Estimated trends in the 15 Sept–15 Oct period are smaller than in September. They vary from 1.15 to 1.78 DU yr−1 and are hardly significant at 2σ level. Ozone recovery is also confirmed by a steady decrease of the relative area of total ozone values lower than 150 DU within the vortex in the 15 Sept–15 Oct period since 2010. Comparison of the evolution of the ozone hole area in September and October shows a decrease in September, confirming the later formation of the ozone hole during that month.
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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 | 0.001 | 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".