The Evolution of Lake-Effect Convection during Landfall and Orographic Uplift as Observed by Profiling Radars
Bibliographic record
Abstract
Abstract A pronounced snowfall maximum occurs about 30 km downwind of Lake Ontario over the 600-m-high Tug Hill Plateau (hereafter Tug Hill), a region where lake-effect convection is affected by mesoscale forcing associated with landfall and orographic uplift. Profiling radar data from the Ontario Winter Lake-effect Systems field campaign are used to characterize the inland evolution of lake-effect convection that produces the Tug Hill snowfall maximum. Four K-band profiling Micro Rain Radars (MRRs) were aligned in a transect from the Ontario coast onto Tug Hill. Additional observations were provided by an X-band profiling radar (XPR). Analysis is presented of a major lake-effect storm that produced 6.4-cm liquid precipitation equivalent (LPE) snowfall over Tug Hill. This event exhibited strong inland enhancement, with LPE increasing by a factor of 1.9 over 15-km horizontal distance. MRR profiles reveal that this enhancement was not due to increases in the depth or intensity of lake-effect convection. With increasing inland distance, echoes transitioned from a convective toward a stratiform morphology, becoming less intense, more uniform, more frequent, and less turbulent. An inland increase in echo frequency (possibly orographically forced) contributes somewhat to snowfall enhancement. The XPR observations reproduce the basic vertical structure seen by the MRRs while also revealing a suppression of snowfall below 600 m AGL upwind of Tug Hill, possibly associated with subcloud sublimation or hydrometeor advection. Statistics from 29 events demonstrate that the above-described inland evolution of convection is common for lake-effect storms east of Lake Ontario.
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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) | 0.000 | 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".