Large‐scale climatic patterns control large lightning fire occurrence in Canada and Alaska forest regions
Bibliographic record
Abstract
Large lightning wildfires in Canada and Alaska account for most of the area burnt and are main determiners of the age mosaic of the landscape. Such fires occur when positive midtroposphere height anomalies persist > 10 days during the fire season. Midtroposphere anomalies are part of teleconnections which are created by atmospheric and coupled sea/air dynamics. Large lightning fire occurrence and area burnt data were used to define eight centers of large wildfire variability in Canada and Alaska during 1959–1999. Preferred positions of persistent positive midtroposphere anomalies correlated with the Fire Regions during large fire events. Active fire weather showed strong relations with Pacific Decadal Oscillation (PDO) at interdecadal timescales and with El Niño Southern Oscillation (ENSO) and Arctic Oscillation (AO) mostly at interannual (2 to 6 years) timescales. PDO and ENSO (AO) related large fires were more frequent in the western (eastern) regions. The mountain ranges in western Canada play a major role in the large‐scale patterns of large fire occurrence through retention of PDO‐related Pacific Ocean moisture, causing the dynamics of large fires each side of the ranges to be mostly in antiphase. The PDO/ENSO regime shift of 1976/1977, together with the strong and persistent positive phase of AO during the late 1980s and 1990s contributed to the increase in area burned in the study area except in British Columbia and Alaska. PDO‐ENSO‐AO interactions with active fire weather provide an explanation for changes in large fire occurrence frequency during the last centuries in the area.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".