Lake-Effect Mode and Precipitation Enhancement over the Tug Hill Plateau during OWLeS IOP2b
Bibliographic record
Abstract
Improved understanding of the influence of orography on lake-effect storms is crucial for weather forecasting in many lake-effect regions. The Tug Hill Plateau of northern New York (hereafter Tug Hill), rising 500 m above eastern Lake Ontario, experiences some of the most intense snowstorms in the world. Herein the authors investigate the enhancement of lake-effect snowfall over Tug Hill during IOP2b of the Ontario Winter Lake-effect Systems (OWLeS) field campaign. During the 24-h study period, total liquid precipitation equivalent along the axis of maximum precipitation increased from 33.5 mm at a lowland (145 m MSL) site to 62.5 mm at an upland (385 m MSL) site, the latter yielding 101.5 cm of snow. However, the ratio of upland to lowland precipitation, or orographic ratio, varied with the mode of lake-effect precipitation. Strongly organized long-lake-axis parallel bands, some of which formed in association with the approach or passage of upper-level short-wave troughs, produced the highest precipitation rates but the smallest orographic ratios. Within these bands, radar echoes were deepest and strongest over Lake Ontario and the coastal lowlands and decreased in depth and median intensity over Tug Hill. In contrast, nonbanded broad-coverage periods exhibited the smallest precipitation rates and the largest orographic ratios, the latter reflecting an increase in the coverage and frequency of radar echoes over Tug Hill. These findings should aid operational forecasts and, given the predominance of broad-coverage lake-effect periods during the cool season, help explain the climatological snowfall maximum found over the Tug Hill Plateau.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.004 | 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 teacher head, 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".