Chlorine Oxide as an Indicator of Ozone Destruction in the Winter–Spring Arctic Stratosphere Based on Aura MLS Observations
Bibliographic record
Abstract
Abstract The ozone behavior in the Arctic is a major recent concern. The ozone anomalies recur every five years on average. The last, record strong decrease of the ozone level in the stratosphere of the Arctic was recorded in March–April 2020. In February 2022, ozone destruction developed according to a scenario very similar to the anomaly of 2020. Like in 2020, in 2022 the ClO mixing ratio, which can be considered a reliable indicator of ozone destruction, strongly increased after the return of sunlight to the Arctic latitudes, but the subsequent ozone depletion process was halted by a sudden major stratospheric warming on March 20, 2022. In this work, we analyze the ozone destruction in 2020–2022 based on measurements of the total ozone content over 2003–2022 from the TEMIS service, profiles of the air temperature and ozone mixing ratio for 2005–2022 and of ClO mixing ratio for 2020–2022 from Aura MLS observations. The following sites are considered: Eureka, Canada; Ny-Ålesund, Norway; Thule, Greenland; and Resolute, Canada. A relationship is revealed between ozone and chlorine oxide contents. High coefficients of correlation between oscillations of the above parameters at about the same altitudes of their recording, as well as between the total O3 and ClO contents calculated from their profiles, indicate their close interrelation. Hence, the ClO concentration and total content can be used as indicators of ozone destruction in the Arctic stratosphere.
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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) | 0.000 | 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".