Climatic drivers of the Canadian wildfire episode in 2023
Bibliographic record
Abstract
Extreme wildfires broke out in Canada from May 2023 and persisted four months. Tremendous fire emissions posed significant impacts on the air quality in both local and downwind regions. Here, we explored the meteorological factors driving this wildfire episode and the associated large-scale circulation. Relative to the mean value of 2001–2022, the 2023 Canadian fires released 0.37 Gt more CO2 (527.1%) during May–August. Such enhancement was strongly associated with the anomalous surface warming, especially in May–June, when the daily maximum temperature on average increased by 8.11°C, with regional hotspots up to 10°C in central and eastern Canada. Consistent with the surface warming, positive anomalies of geopotential height were observed at high levels in central and western Canada. The dispersion of Rossby waves led to the long-lasting dominance of high-pressure systems and the consequent warming through anomalous subsidence. The phase-locked wave pattern induced by favorable topography and the strong warming tendency in the pan-Arctic regions are expected to jointly escalate the probability of extreme wildfires over central and western Canada in the future.
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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 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".