Attribution of the 2022 extratropical storm Fiona
Bibliographic record
Abstract
In late September 2022, the Atlantic Hurricane Fiona transitioned to an extratropical cyclone making a landfall in the Canadian Atlantic provinces and setting a new national lowest pressure record. The insured damage from the resulting windstorm and flooding is estimated to be 800 million CAD (600 million USD).In this study, we analyze the maximum daily near-surface wind speeds in Atlantic Canada using reanalysis and CMIP6 HighResMIP data. According to our preliminary results from ERA5 reanalysis, the 2022 Fiona wind speeds were the highest in Atlantic Canada since 1950, with an estimated return period of 500 years. Additionally, using HighResMIP data from the models with a spatial resolution exceeding 56x56 km, we compare the wind speeds in the current climate with those from 1950-1969 and in 2031-2050 under the highres-future scenario, similar to RCP8.5. While currently in Atlantic Canada, there is no statistically significant increase in the maximum daily wind speeds in comparison to 1950-1969 climate, the increase in the mid-21st century wind speeds in comparison to the 1950-1969 period is statistically significant with the 2022 event being 3.8 times more likely. We apply similar analysis to the data from CAM5 model as well as to the CMIP6 precipitation data in the region.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".