The OWLeS IOP2b Lake-Effect Snowstorm: Dynamics of the Secondary Circulation
Bibliographic record
Abstract
Intense lake-effect snowfall results from a long-lake-axis-parallel (LLAP) precipitation band that often forms when the flow is parallel to the long axis of an elongated body of water, such as Lake Ontario. The intensity and persistence of the localized precipitation along the downwind shore and farther inland suggests the presence of a secondary circulation that helps organize such a band, and maintain it for some time as the circulation is advected inland. Unique airborne vertical-plane dual-Doppler radar data are used here to document this secondary circulation in a deep, well-organized LLAP band observed during intensive observing period (IOP) 2b of the Ontario Winter Lake-effect Systems (OWLeS) field campaign. The circulation, centered on a convective updraft, intensified toward the downwind shore and only gradually weakened inland. The question arises as to what sustains such a circulation in the vertical plane across the LLAP band. WRF Model simulations indicate that the primary LLAP band and other convergence zones observed over Lake Ontario during this IOP were initiated by relatively shallow airmass boundaries, resulting from a thermal contrast (i.e., land-breeze front) and differential surface roughness across the southern shoreline. Airborne radar data near the downwind shore of the lake indicate that the secondary circulation was much deeper than these shallow boundaries and was sustained primarily by rather symmetric solenoidal forcing, enhanced by latent heat release within the updraft region.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".