A radar‐based methodology for preparing a severe thunderstorm climatology in central Alberta
Bibliographic record
Abstract
Abstract The Radar data Analysis, Processing and Interactive Display (RAPID) system, developed by McGill University researchers, synthesizes spherical coordinate radar data onto Cartesian maps displaying Constant Altitude Plan Position Indicator (CAPPI) reflectivity, Vertically Integrated Liquid water content (VIL), and other radar‐based parameters. In this study, Carvel radar (53.34°N, 114.09°W) data from July 2000 were processed using McGill's RAPID software. Specifically, we compared observations of severe convection, as identified by selected radar‐based reflectivity parameters, with surface severe weather reports and atmospheric sounding data. July 2000 was characterized by frequent severe thunderstorm activity over central Alberta; there were seven days with golfball‐sized hail, and two days with confirmed tornadoes. The VIL, upper level VIL (UVIL), and the maximum reflectivity at 7 km (Z7) were employed to quantify the strength and frequency of storms within a 120‐km radial distance of Carvel. For each day, the intensity of the convection was quantified by counting the total number of 1‐km2 pixels in the study area that exceeded the severe thresholds for VIL, UVIL and Z7. The severe thunderstorm algorithms were found to be very effective at correctly identifying the observed severe thunderstorm events. All three radar parameters indicated a diurnal cycle, with severe convection starting after noon and peaking between 16:00 and 18:00 Local Daylight Time. A positive correlation was evident between the observed storm severity and the daily UVIL and Z7 pixel counts. The daily UVIL and Z7 pixel counts were also positively correlated with the Convective Available Potential Energy (CAPE) calculated from proximity soundings.
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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) | 0.001 | 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 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".