High-Resolution Paleo-Storm Reconstruction from Eastern Canada Aligns with Late-Holocene Northwestern Atlantic Hurricane Records
Bibliographic record
Abstract
Abstract. Atlantic Canada experiences frequent major storms, particularly tropical cyclones transitioning into post-tropical storms. Events such as Hurricane Fiona (2022), Dorian (2019), and Juan (2003) have caused significant damage, loss of life, and coastal erosion, exacerbated by sea level rise and warming waters. Despite this, centennial- to millennial-scale storm records in the region remain scarce. Existing studies in North America focus primarily on marine and coastal overwash records, with limited use of aeolian mineral inputs in ombrotrophic peatlands as storm proxies. Here, we address these gaps by analysing grain-size and geochemical data from two peatlands in Quebec, Canada’s Magdalen Islands. Our two peat records reveal consistent storm signals over the past 4000 years, with three key periods of heightened activity: 800–550 BCE, 600–800 BCE, and 1300–1700 CE. These signals align with marine and overwash records spanning the past 2000 years across eastern Canada, the US, and the Bahamas, indicating low storm activity during the Medieval Climate Anomaly, followed by increased activity during the Little Ice Age. Our findings suggest that storm records in these regions are influenced by local climatic factors. Negative phases of the Atlantic Multidecadal Variability, which typically suppress hurricane activity in the North Atlantic, are associated with conducive hurricane formation and intensification north of the Bahamas. Additionally, the position of the Bermuda High seems to play a more significant role in directing storm tracks during different climatic phases. Our findings highlight the potential antiphase relationship in storm activity between regions north of the Bahamas and those in the Gulf of Mexico, suggesting broader climatic mechanisms that warrant further investigations. Despite the similarities between our two sites, discrepancies in geochemistry and mineralogical profiles highlight the importance of site-specific conditions in interpreting the storm record from peatlands, namely the distance of the sites to the coast and source of aeolian sediment, as well as peatland size. Challenges also remain in calibrating peat-based proxies with historical storm records, as identifying specific events from the past 150 years remains difficult.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".