Explaining Pan‐Atlantic Cold and Windy Extremes Using an Analog‐Based Approach
Bibliographic record
Abstract
Abstract The occurrence of cold spells over different regions of North America has been previously linked to windy extremes over Western Europe. These so‐called pan‐Atlantic extremes are necessarily mediated by the North Atlantic circulation. It is known that the Atlantic storm track modulates European windstorm occurrence, but it is unclear whether the American cold spells directly influence the storm track, or whether the cooccurrence of extremes is indirect—a result of a common large‐scale driver. In this study, cold spells over both central North America and northeast Canada are clustered with respect to the evolution of the large‐scale circulation over the North Atlantic. The direct contribution of cold spells to the European wind extremes is then ascertained using circulation analogs, so that different states of the North Atlantic storm track can be compared for days with and without cold spells. Consistent with previous work, two main pathways emerge from the analysis, called “zonal” and “wavy” for simplicity. For a wavy pathway, North American cold spell occurrence is directly associated with more frequent European wind extremes than expected from the Euro‐Atlantic flow, as a result of Rossby wave trains. For the other pathways, the common driver of storm track variability linked to the anomalous Atlantic circulation was sufficient to explain more frequent wind extremes across Europe, with no or little ascertainable contribution from the cold spells. This analysis clarifies that the causality of wintertime pan‐Atlantic extremes is flow‐dependent—either direct or indirect depending on the active dynamical pathway.
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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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".