Snowband Characteristics Associated With Lake‐Effect Misovortices During the OWLeS Project
Bibliographic record
Abstract
Abstract Vortices of diameters 100 m to 10 km have been observed during lake‐effect snowstorms. Lines of misovortices (diameters = 40–4,000 m) have recently been documented forming over Lake Ontario during long lake‐axis‐parallel (LLAP)‐type lake‐effect storms. Using National Weather Service Weather Surveillance Radar—1988 Doppler (WSR‐88D) and Doppler on Wheels radar data from the Ontario Winter Lake‐effect Systems (OWLeS) project, lines of misovortices (also referred to as “misovortex lines” in this study) were investigated for intensive observation period (IOP)7 (7 January 2014) and IOP9 (9 January 2014). Results revealed that the misovortex lines formed on the southern or northern side of the west‐to‐east‐oriented LLAP band, whichever was closest to a low‐level boundary nearest the corresponding south or north shoreline (northern part in IOP7, southern part in IOP9). Examination of these two IOPs in the context of a total of 23 OWLeS IOPs, 11 of which had predominantly LLAP band morphology, showed that, in 4 of the 11 LLAP IOPs, horizontal shear zones/reflectivity bands formed in preferred regions over Lake Ontario and nearby land areas where low‐level boundaries (e.g., land breeze fronts) have been noted to develop near shoreline irregularities. Horizontal shear zones were predominant in approximately half of the OWLeS LLAP IOPs and were associated with storms having a well‐organized, solid banded reflectivity structure. Misovortices occurred when horizontal shear zones were prevalent, supporting the idea that horizontal shearing instability was important to their formation.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".