Record-breaking fire weather in North America in 2021 was initiated by the Pacific northwest heat dome
Bibliographic record
Abstract
Abstract The 2021 North American wildfire season was marked by record breaking fire-conducive weather and widespread synchronous burning, extreme fire behaviour, smoke and evacuations. Relative to 1979–2021, the greatest number of temperature and vapor pressure deficit records were broken in 2021, and in July alone, 3.2 million hectares burned in Canada and the United States. These events were catalyzed by an intense heat dome that formed in late June over western North America that synchronized fire danger, challenging fire suppression efforts. Based on analysis of persistent positive anomalies of geopotential heights, the heat dome accounted for 21–34% of the total area burned in 2021. The event was 59% longer, 34% larger and had 6% higher maximum amplitude than the same event would have been without a warming climate. Climate change will continue to magnify heat dome events, increase fire danger, and enable extreme synchronous wildfire in forested areas of North America.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".