A Radar-Based Investigation of Lake Breezes in Southern Manitoba, Canada
Bibliographic record
Abstract
Lake breezes are thermally direct circulations that form as a result of the differential heating of land and water and are important in modifying local climate and triggering convection; they have also been linked to tornadogenesis. Although lake breezes are generally well understood, studies of smaller lakes have been relatively scarce, and none have examined lake-breeze circulations in southern Manitoba even though they are seemingly apparent on weather radar. The objectives of this paper are to provide a radar-based analysis of lake-breeze frequency and characteristics in southern Manitoba, determine the detectability of lake-breeze fronts using the radar analysis with data collected in 2013, assess the types of lake-breeze circulations that occur, and examine the meteorological conditions in which they occur. Between 2008 and 2013, lake-breeze fronts were noted on 205 days using radar over the summer months, accounting for 37% of study days, with an average of 11–12 days with lake-breeze fronts each month. These findings agree fairly well with, and are only slightly less than, frequencies reported for Lake Michigan but are lower than the most recent findings for southern Ontario. In an effort to validate the results, a broad comparison between the radar analysis and a more complete analysis using satellite and surface stations is provided for 2013 demonstrating that radar is more useful for detecting lake breezes around Lake Manitoba than around Lake Winnipeg. Lake-breeze circulations originating on Lake Manitoba and the Shoal lakes were classified into three types. The distribution of types for the Shoal lakes was similar to previous findings by other authors with “moderate deformation” circulations being the most frequent. Finally, a brief meteorological analysis was completed for each month of this study. The results of the analysis were inconclusive with no single meteorological factor being consistently well correlated to higher or lower lake-breeze frequency.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".