How useful are teleconnection patterns for explaining variability in extratropical storminess?
Bibliographic record
Abstract
This empirical study relates the extratropical storminess in the Northern Hemisphere to the large-scale flow using gamma regression models. Time series of storminess are derived using the monthly mean variance of highpass filtered sea-level pressure from the 6-hourly NCEP/NCAR reanalysis data for the 54 extended winters (Oct-Mar) between 1950–2003. Five teleconnection patterns were found to be statistically significant factors at the 5% level for storminess in the Euro-Atlantic region: the North Atlantic Oscillation (NAO), the East Atlantic pattern, the Scandinavian pattern, the East-Atlantic/Western-Russia pattern and the Polar/Eurasian pattern. In the North Pacific the dominant factor is found to be the Pacific North American (PNA) pattern. It is also shown that the relationship between teleconnection patterns and storminess to a large extent is accounted for by a basic relation between storminess and the local mean SLP but with a few notable exceptions. In particular the East Atlantic pattern is identified as an important non-local factor for storminess over the Labrador Sea and the PNA pattern as an important non-local factor for storminess north of the Aleutian low.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".