Arctic Ozone Depletion in 2019/20: Roles of Chemistry, Dynamics and the Montreal Protocol
Bibliographic record
Abstract
Abstract We use a three‐dimensional chemical transport model and satellite observations to investigate Arctic ozone depletion in winter/spring 2019/20 and compare with earlier years. Persistently, low temperatures caused extensive chlorine activation through to March. March‐mean polar‐cap‐mean modeled chemical column ozone loss reached 78 DU (local maximum loss of ∼108 DU in the vortex), similar to that in 2011. However, weak dynamical replenishment of only 59 DU from December to March was key to producing very low (<220 DU) column ozone values. The only other winter to exhibit such weak transport in the past 20 years was 2010/11, so this process is fundamental to causing such low ozone values. A model simulation with peak observed stratospheric total chlorine and bromine loading (from the mid‐1990s) shows that gradual recovery of the ozone layer over the past 2 decades ameliorated the polar cap ozone depletion in March 2020 by ∼20 DU.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 teacher head, 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".