Midlatitude cyclones in the southeastern United States: frequency and structure differences by cyclogenesis region
Bibliographic record
Abstract
ABSTRACT Midlatitude cyclones that affected the Southeast (SE) United States between 1998 and 2010 were classified into five types according to their region of origin: (1) Continental United States, (2) Canadian, (3) Gulf Low, (4) Hatteras Low, or (5) Stationary. A composite analysis was used to examine differences in the structure, evolution, and propagation of these cyclones during boreal winter, when the largest number of cyclones affect the SE United States. Most of the midlatitude cyclones that affect the SE in the wintertime formed within the continental United States (∼11 events/winter), followed by Gulf Lows (∼4 events/winter) and Canadian cyclones (∼4 events/winter). Hatteras Lows were relatively rare (∼1 events/winter), and Stationary events did not occur during winter. While Canadian and Continental US cyclones occurred year‐round the frequency of Gulf Low events peaked in the boreal winter when the upper‐level jet was strongest and located further south. Hatteras Lows peaked in the boreal fall and winter, and Stationary events occurred almost exclusively during the boreal summer. Overall, Gulf Low and Continental US cyclones were the only cyclones that brought wintertime precipitation to the SE United States. When integrated over the season, Continental US cyclones made the largest contribution to the wintertime precipitation in the SE United States. On a per‐event basis, however, Gulf Lows were the biggest wintertime precipitation makers in the SE United States while Canadian cyclones and Hatteras Lows did not bring much precipitation to the SE United States. Gulf Lows were more common during El Niño than La Niña years and tended to occur back‐to‐back with either another Gulf Low or with a Hatteras 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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".