Connections between stratospheric ozone and climate: Radiative forcing, climate variability, and change
Bibliographic record
Abstract
Quantifying the combined effects of ozone depletion and changes in other greenhouse gases and radiatively and chemically active atmospheric constituents is of great importance to human welfare. Achieving this goal requires evaluating the impact of stratospheric ozone depletion and its recovery on the tropospheric climate as well as elucidating the effects of climate change on the evolution of ozone itself. This, in turn, requires the understanding and quantification of the long‐term sensitivity of the climate system to significant perturbations in the radiation budget of the atmosphere associated with human activities. Detecting and quantifying such effects also requires a quantitative understanding of the role of natural events, such as volcanoes and solar variability, on the composition and evolution of the atmosphere and ultimately of the effects of such events on the climate change signal throughout the active atmosphere and at the surface. With the advent of climate modelling as a key tool for studying and predicting the evolution of the climate system, the linked concepts of radiative forcing and climate sensitivity have come into wide use as a means to understand and quantify key aspects of modelling results. These concepts are reviewed and their relevance to understanding and quantifying the radiative impact of ozone and ozone depleting substances on the radiative forcing of the climate system are discussed. Recent observational, theoretical, and modelling studies have revealed many new features of stratosphere‐troposphere coupling that are relevant to understanding the role of stratospheric processes in climate variability and change. Aspects of these studies are reviewed briefly.
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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 | 0.001 |
| 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".