Downstream Evolution and Coastal-to-Inland Transition of Landfalling Lake-Effect Systems
Bibliographic record
Abstract
Abstract The distribution and intensity of lake- and sea-effect (hereafter lake-effect) precipitation are strongly influenced by the mode of landfalling lake-effect systems. Here, we used idealized large-eddy simulations to investigate the downstream evolution and coastal-to-inland transition of two lake-effect modes: 1) a long-lake-axis-parallel (LLAP) band generated by an oval body of water (hereafter lake; e.g., Lake Ontario) and 2) broad-coverage, open-cell convection generated by an open lake (e.g., Sea of Japan). Under identical atmospheric conditions and lake-surface temperatures, the oval lake generates a LLAP band with heavy precipitation along the midlake axis, whereas the open lake generates broad-coverage, open-cell convection with widespread, light accumulations. Over the oval lake, the LLAP band features a thermally forced and diabatically enhanced cross-band secondary circulation with convergence and ascent over the midlake axis. Downstream of the lake, flanking airstreams that avoid lake modification merge beneath the band where they experience sublimational cooling, producing a cold pool. At the upstream edge of the cold pool, a coastal baroclinic zone forms. Above this zone, ascent and hydrometeor mass growth are maximized, resulting in an inland precipitation maximum due to subsequent hydrometeor transport and fallout. Over the open lake, individual open cells grow larger and stronger with overwater extent, but a convective-to-stratiform transition begins at the coast. Here, convective vigor decays, mesoscale ascent begins, and enhanced hydrometeor growth results in an inland precipitation maximum. These results highlight variations in the coastal-to-inland transition of lake-effect systems that ultimately influence the distribution and intensity of lake-effect precipitation.
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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 | 0.000 | 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 | 0.000 | 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".