Persistent Positive Anomalies in Geopotential Heights Promote Wildfires in Western North America
Bibliographic record
Abstract
Abstract During summer, persistent positive anomalies (PPAs) of midtropospheric geopotential heights in North America are often associated with extreme weather, including heatwaves. We evaluate the link between prolonged summertime PPAs in 500-hPa geopotential heights and wildfire activity across western North America and examine temporal trends in PPA characteristics. On average, 17% of May–September days experience PPA events over the study domain. Large fires (burned area > 500 ha) were 7 times as likely to start during a PPA, with approximately 40% of these fires’ ignitions coincident with PPA events. A positive correlation exists between the fraction of May–September PPA days and burned area for most of the study domain. Additionally, the presence of a PPA exerts greater influence on fire ignition and burned area in higher latitudes than lower latitudes of western North America. We find a statistically significant expansion in the spatial extent of PPA events during 1979–2020. The observed expansion of the PPAs is likely due to thermodynamic changes in midlatitude synoptic patterns. These findings may improve our understanding of the connections between PPA events and wildfires in western North America, enhance the short-term predictability of wildfire events, and have important implications for increased fire risk in a warming climate. Significance Statement Persistent positive anomalies (PPAs) of the upper air atmospheric flow, a slow progression of planetary waves, are synoptic-scale patterns that cause heatwaves and contribute to wildfire activity. We seek to understand how these events relate to fire weather and fire activity over western North America. The presence of PPA events increases the likelihood of fire ignition by a factor of 7, with higher likelihood over northern regions. The mean area of the PPA events has grown significantly in recent decades, exposing larger areas and populations to increased fire risks. These results improve our understanding of the connections between upper air atmospheric patterns and wildfires, signal how it may change in future warmer climate and scenarios, and enhance the near-future predictability of fire events in this 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 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".