Tropospheric temperature response to stratospheric ozone recovery in the 21st century
Bibliographic record
Abstract
Abstract. Recent simulations predicted that the stratospheric ozone layer will likely return to pre-1980 levels in the middle of the 21st century, as a result of the decline of ozone depleting substances under the Montreal Protocol. Since the ozone layer is an important component in determining stratospheric and tropospheric-surface energy balance, the recovery of stratospheric ozone may have significant impact on tropospheric-surface climate. Here, using multi-model results from both the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC-AR4) models and coupled chemistry-climate models, we show that as ozone recovery is considered, the troposphere is warmed more than that without considering ozone recovery, suggesting an enhancement of tropospheric warming due to ozone recovery. It is found that the enhanced tropospheric warming is mostly significant in the upper troposphere, with a global and annual mean magnitude of ~0.41 K for 2001–2050. We also find that relatively large enhanced warming occurs in the extratropics and polar regions in summer and autumn in both hemispheres, while the enhanced warming is stronger in the Northern Hemisphere than in the Southern Hemisphere. Enhanced warming is also found at the surface. The global and annual mean enhancement of surface warming is about 0.16 K for 2001–2050, with maximum enhancement in the winter Arctic.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".