Interhemispheric asymmetry of surface mean and extreme wind projections in CanESM5 climate change simulations
Bibliographic record
Abstract
The internal climate variability contributes to various aspects of climate change projections. This presentation will report results of the ensemble mean and spread of future projections of globally surface mean and extreme winds in boreal winter, based on single model initial-condition simulations forced by the SSP5-8.5 high-emissions scenario from a 50-member ensemble of CanESM5 models. Over the next half century, surface wind is projected to increase in the Northern Hemisphere mid-latitudes and increase in the Southern Hemisphere low-latitudes, an interhemispheric asymmetry feature relevant to large-scale changes in surface temperature and atmospheric circulation. Decreases in the surface extreme wind are clearer than the mean wind in the northern mid-latitudes. Large ensemble spreads are apparent in the mean and extreme wind changes, including spatial pattern and magnitude of the projected trends over the next half century. The internal climate variability generated components of the mean and extreme wind trends exhibit large-scale spatial coherences, and are comparable to the externally anthropogenic forced components of the trends.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".