Interhemispheric asymmetry of climate change projections of boreal winter surface winds in CanESM5 large ensemble simulations
Bibliographic record
Abstract
Abstract A recent study of global wind power using an ensemble of ten CMIP5 climate simulations indicated an interhemispheric asymmetry of wind power changes over the twenty-first century, featured by power decreases across the Northern Hemisphere mid-latitudes and increases across the tropics and subtropics of the Southern Hemisphere. Here we analyze future projections of surface mean and extreme winds by means of a single-model initial-condition 50-member ensemble of climate simulations generated with CanESM5, the Canadian model participated in CMIP6. We analyze the ensemble mean and spread of boreal winter mean and extreme wind trends over the next half-century (2021–2070) and explore the contribution of internal climate variability to these trends. Surface wind speed is projected to mostly decrease in northern mid-low latitudes and southern mid-latitudes and increase in northern high latitudes and southern tropical and subtropical regions, with considerable regional variations. Large ensemble spreads are apparent, especially with remarkable differences over northern parts of South America and northern Russia. The interhemispheric asymmetry of wind projections is found in most ensemble members, and can be related to large-scale changes in surface temperature and atmospheric circulation. The extreme wind has similar structure of future projections, whereas its reductions tend to be more consistent over northern mid-latitudes. The projected mean and extreme wind changes are attributed to changes in both externally anthropogenic forced and internal climate variability generated components. The spread in wind projections is partially due to large-scale atmospheric circulation variability.
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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 | 0.000 |
| 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".