Interannual Variability of the North American Cold Air Stream and Associated Synoptic Circulations
Bibliographic record
Abstract
In boreal winter, the cold air mass (CAM) flux of air with a potential temperature below 280 K forms climatological mean CAM streams in East Asia and North America (NA). This study diagnoses the interannual variability of the NA stream by an analysis of the CAM flux across 60°N between Greenland and the Rocky Mountains. The first empirical orthogonal function (EOF) represents the variations in intensity of the NA stream. When the first principal component (PC1) is highly positive, the central part of the NA stream is intensified, with cold anomalies east of the Rocky Mountains. At the same time, a stratospheric polar vortex tends to split or displace toward NA. PC1 is highly correlated with the tropical Northern Hemisphere pattern, implying that this pattern is associated with the intensity of the NA stream. The second EOF shows a longitudinal shift of the NA stream toward Greenland or the Rocky Mountains. A highly negative PC2 results in a cold anomaly from western Canada to the Midwestern United States and anomalous heavy snowfall in the northeastern United States. PC2 is positively correlated with the Arctic Oscillation, which suggests that the longitudinal position of the NA stream varies with the Arctic Oscillation. These results illustrate how the intensity and location of cold air outbreaks vary with large-scale modes of atmospheric variability, with corresponding implications for the predictability of winter severity in NA.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".