The $3.25 billion Calgary, Alberta Hailstorm: a Meteorological Case Study and In-Situ Observations from the Northern Hail Project
Bibliographic record
Abstract
A destructive hailstorm hit Calgary, Alberta, Canada on August 5th, 2024, resulting in $3.25 billion CAD of insured losses – this made it the second costliest natural hazard event in Canadian history, in terms of insured losses. The storm caused widespread damage to the northern areas of the city. We will present results on the storm’s evolution, meteorological environment, and behaviour, to better understand the mechanisms behind its intensity and to inform the forecasting and mitigation of future hailstorms. On this day, the Northern Hail Project (NHP) field teams also collected in-situ data along the storm’s track; the largest hailstone that was found measured 52 mm in diameter. Hail was recorded at four NHP hail-monitoring stations located in the affected areas of the city. Colleagues from the Insurance Institute for Business & Home Safety (IBHS) also captured high-resolution data from an array of hail disdrometers deployed ahead of the storm. Synoptic conditions on the day were broadly supportive for the development of severe thunderstorms, although the environment did not suggest conditions were in place to support an exceptionally damaging hailstorm. Examination of ERA5 reanalysis data revealed a favourable kinematic profile, characterized by 20 m/s of 0-6 km bulk wind shear, as well as surface-based CAPE near 1,200 J/kg and 19 mm of precipitable water. The storm initiated over a zone of enhanced surface convergence and upslope flow along the front range of the Rocky Mountains northwest of Calgary. Once away from the terrain, the storm rapidly intensified and began producing large quantities of damaging hail. Just prior to entering the city limits, the storm became outflow dominant, producing measured wind gusts up to 65 km/h. These winds significantly increased the level of hail damage. The storm continued to produce severe hail after leaving the city. Ultimately, it was the combination of an outflow-driven storm, over an urban area, which produced such extensive damage. Therefore, insights gained from this investigation, particularly the detailed in-situ observations and environmental analysis by the NHP, underscore the importance of high-resolution monitoring to advance hailstorm forecasting and impact mitigation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".