Pathways to concurrent North American cold and European wind extremes
Bibliographic record
Abstract
We examine near-simultaneous occurrences of cold extremes in North America and wind extremes in Europe, referred to as pan-Atlantic compound extremes. Previous studies have established a robust spatial and temporal relationship between the location of cold extremes and the footprint of wind extremes. Individually, cold and wind extremes are highly impactful, but their coincident occurrence amplifies effects and exposes international actors to correlated losses. This study analyzes the large-scale circulations responsible for pan-Atlantic compound extremes through the lens of weather regimes and Fourier decomposition.Five distinct dynamical pathways are identified, which non-uniformly govern the occurrence of cold extremes across three regions of North America. Three of these pathways also engender European wind extremes, providing a mechanistic explanation for the observed spatial and temporal relationships of pan-Atlantic extremes. The pathways are as follows:(i) A persistent Atlantic low producing cold spells in eastern Canada and wind extremes in the British Isles.(ii) A wave train generating cold spells in the eastern United States, culminating in an Atlantic low and wind extremes in Iberia and the British Isles.(iii) A wave train producing cold spells in eastern Canada, culminating in Scandinavian blocking.(iv) A quasi-stationary wave-2 pattern driving cold spells in central Canada and Scandinavian blocking.(v) An Arctic high generating cold spells in the eastern United States and wind extremes in Iberia.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".