Atmospheric Chemistry and Physics Past and future conditions for polar stratospheric cloud formation simulated by the Canadian Middle Atmosphere Model
Bibliographic record
Abstract
Abstract. We analyze here the polar stratospheric temper-atures in an ensemble of three 150-year integrations of the Canadian Middle Atmosphere Model (CMAM), an interac-tive chemistry-climate model which simulates ozone deple-tion and recovery, as well as climate change. A key motiva-tion is to understand possible mechanisms for the observed trend in the extent of conditions favourable for polar strato-spheric cloud (PSC) formation in the Arctic winter lower stratosphere. We find that in the Antarctic winter lower stratosphere, the low temperature extremes required for PSC formation in-crease in the model as ozone is depleted, but remain steady through the twenty-first century as the warming from ozone recovery roughly balances the cooling from climate change. Thus, ozone depletion itself plays a major role in the Antarc-tic trends in low temperature extremes. The model trend in low temperature extremes in the Arc-tic through the latter half of the twentieth century is weaker and less statistically robust than the observed trend. It is not projected to continue into the future. Ozone depletion in the Arctic is weaker in the CMAM than in observations, which may account for the weak past trend in low temperature ex-tremes. In the future, radiative cooling in the Arctic winter due to climate change is more than compensated by an in-crease in dynamically driven downwelling over the pole. 1
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".