Dynamical Mechanisms for the Recent Ozone Depletion in the Arctic Stratosphere Linked to the North Pacific Sea Surface Temperatures
Bibliographic record
Abstract
Abstract The ozone layer, which prevents solar ultraviolet radiation from reaching the surface and thereby protects life on earth, is expected to recover from past depletion during this century due to the impact of the Montreal Protocol. However, how the ozone column over the Arctic will evolve over the next few decades is still under debate. In this study, we found that the ozone level in the Arctic stratosphere during the period of 1998–2018 exhibits a decreasing trend of –0.12±0.07 ppmv decade–1 from MERRA2, suggesting a continued depletion during this century. This ozone depletion is contributed by the second leading mode of North Pacific sea surface temperature anomalies (SSTAs) with one month leading and therefore dynamical in origin. The North Pacific SSTAs associated with this mode tend to result in a weakened Aleutian low, a strengthened Western Pacific pattern and a weakened Pacific–North American pattern, which impede the upward propagation of planetary wavenumber-1 waves into the lower stratosphere. The changes in the stratospheric wave activity tend to result in decreased ozone in the Arctic lower stratosphere through weakening the Brewer-Dobson circulation. Our findings will provide new understanding of how dynamical processes control Arctic stratospheric ozone and will help to improve prediction of how Arctic ozone will evolve in the future.
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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 | 0.000 |
| 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".