Mesoscale boundaries and storm development in Southwestern Ontario during ELBOW 2001
Bibliographic record
Abstract
The Effects of Lake Breezes on Weather (ELBOW) 2001 project was conducted in Southwestern Ontario, during summer 2001. Project goals included: understanding how lake breezes interact with one another, other mesoscale boundaries and synoptic fronts, understanding how lake breezes affect storm development, and helping to improve regional forecasts by transferring findings to forecasters.\n\nRadar, Satellite, Mesonet and Integrated (considering all data sets) analyses were each used to identify the mesoscale boundaries that occurred during the study period. A contingency table approach, for lake breeze occurrence, was used to evaluate each of the analyses against a Final 'Truth' Set. Findings showed that the Integrated analysis performed the best. Advantages and drawbacks of each analysis became apparent.\n\nEvaluation of the analyses was also done by studying the in land penetration distances of the lake breeze fronts. This revealed that most the analyses had good correlation to the Final 'Truth' Set. The Mesonet analysis was the least accurate for pinpointing lake breeze fronts, due to lack of information between surface stations.\n\nThe boundary analysis showed that lake breeze fronts, originating from one or more of the surrounding lakes, occurred in the study area on 73 out of 86 days, or 85% of the days (for 1800 UTC).\n\nExeter radar data (CAPPI and MAXR) were run through URP cell identification and tracking algorithms. The locations of storm cells, when they reached a 40 dBZ level, were measured relative to the closest boundary. Considering study days without warm front influence, 70.4% of the 40 dBZ CAPPI cell initiations and 68.5% of the 40 dBZ MAXR cell initiations occurred at a distance of 20 km or less from a boundary. Cell distribution plots were created to show the locations of the 40 dBZ cell initiations in front or behind a specified boundary type or boundary classification.\n\nNowcasting techniques considering cumulus cloud development and Lifted Index values in the 'lifting zone' of the boundary, the convergence strength and updraft orientation along the boundary, and the boundary relative cell speed, were utilized in case studies. Reasons for the development, or the lack thereof, became apparent in cases presented.
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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 | 0.003 |
| 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".