The role of extratropical cyclones in flooding in Quebec, Canada, from 1990-202
Bibliographic record
Abstract
Out of all weather-related hazards, flooding has the most widespread impact globally, and the province of Quebec is no exception. In the past decades, dozens of riverside municipalities have felt the socio-economic consequences of flooding firsthand. Most of Quebec is characterised by a cold and humid continental climate, with precipitation year-round. Here, river flooding often takes place in the spring, due to snowmelt. Although important, snowmelt alone is not the only factor influencing flooding in the mid-latitudes. By bringing heavier than normal precipitation with them, extratropical cyclones are also known to be key contributors. The relationship between extratropical cyclones and flooding have been extensively studied on the West Coast of North America, but remains largely unexplored in eastern Canada. Thus, this study aims to link flooding events that have happened in the past 30 years in Quebec to their triggering extratropical cyclones and identify possible characteristics (genesis locations, trajectories, lifetime, progression speed, or precipitation intensity) that set these systems apart. Coupled with financial aid claims data, highlighting the differences between regular vs flood-inducing extratropical cyclones coming through Quebec can help describe the region’s flooding history and better prepare for future events. We also explore the involvement of atmospheric rivers in these extreme events. This analysis is performed using three databases. First, the Quebec Floods Financial Aid Claims Database provides the 14360 financial aid claims filed by individuals or businesses for material loss following flooding, from 1990-2022. Each claim contains the location of the damaged infrastructures, watershed involved, and closest river section. Second, the North American Extratropical Cyclone Catalogue provides extratropical cyclone tracks derived from the ERA5 reanalysis, available every hour from 1979-2020, and includes variables of interest such as precipitation and near surface wind-speeds. Third, the Global Atmospheric River Scale Database gives the occurrence and scale (based on integrated water vapor transport and duration of event) of atmospheric rivers every 6 hours from 1979-2020. By grouping the financial aid claims by location and date, 385 events were identified. Through this analysis, 550 extratropical cyclones (storms) of interest were identified and ranked according to their associated percentage of cumulated rain during the event. Five zones of storm genesis locations were identified: western Canada, Great Lakes and Ontario, US Northern East Coast and Quebec, Central US, and US East Coast. The genesis location of weaker storms was uniformly distributed among the five regions. However, most of the remaining 108 more intense storms were coming from two genesis locations: Central US (48%), and US East Coast (25%). For these two genesis zones, trajectories of stronger storms were found to be different from those of weaker storms. For example, tracks were more likely to move over land going up the US East Coast and go over the Great Lakes when coming from Central US. As for atmospheric rivers, their involvement in flood-events was found to be very high in the winter, and minimal in the summer. The combination of data used in this method offers new insights for investigating flooding events.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".