The impact of extreme storms on coastal oceanographic conditions on the west coast of British Columbia: A case study of the 18-21 November 2024 Bomb Cyclone.
Bibliographic record
Abstract
Human-induced climate change is expected to increase the intensity and frequency of major storms. Explosive cyclogenesis (“bomb cyclone”) is among the most violent of atmospheric events and occurs when there is a rapid deepening of the pressure at the centre of a cyclonic system over a period of 24h. Bomb cyclones generally form over the ocean in winter and are relatively common on the Atlantic coast of North America, where they can be manifested in nor’easters in the form of blizzards up north and hurricanes down south – Hurricane Milton experienced explosive cyclogenesis.In this study, we examine the bomb cyclone that impacted the British Columbia (BC) coast of Canada during 18-21 November, 2024. This extreme weather event was accompanied by hurricane strength wind gusts of up to 170 km/h and extreme storm waves. Atmospheric pressure in the cyclone centre fell as low as 940 hPa and the storm caused large-scale power outages and strongly affected coastal infrastructure. The cyclone and associated storm produced a strong storm surge, significant seiches, infragravity waves and modified the oceanic circulation, impacting inlet and coastal ecological habitats. We examine real-time observations recorded by tide gauges along with simultaneous atmospheric microbarographs from the Canadian Hydrographic Service to provide estimates of the statistical and extreme parameters of the sea level and atmospheric pressure oscillations. Additional observations of water properties, oceanic circulation, acoustic backscatter and undersea video from the Ocean Networks Canada coastal sub-sea networks provide a comprehensive view of the impact on inlet and coastal habitat by this extreme weather event.
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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 | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".