A Multi-Index Examination of Future Fire Season Length and Severity Over the United States
Bibliographic record
Abstract
Our goal is to better understand the potential effects of climate change on fire danger for the near (2030-2060) and far (2069-2099) future. We examine changes in fire season length and severity using multiple regional climate model (RCM) simulations and multiple fire indexes for the entire United States. As different fire indexes make different assumptions about fuel and soil conditions, and different fire indexes are favored for different applications in different regions, we use 8 indexes, with 2 variations on 3 of those, for 11 measures of fire behavior. We examine changes in the number of days above the 80th, 90th, and 97th percentiles of these indexes, corresponding to thresholds used to assign descriptors of fire danger as high, very high, and severe. To define fire season length, we use the number of days above the 80th percentile for each given index. We employ thirteen simulations produced for the North American component of the Coordinated Regional climate Downscaling Experiment (NA-CORDEX), leveraging RCP8.5 emission scenario simulations for the future projections. From these simulations, we calculate the KBDI (Keetch-Byram Drought Index), mFFWI (modified Fosberg Fire Weather Index), CFWI (Canadian Fire Weather Index), FM100 and FM1000 (100- and 1000-hour Fuel Moisture), ERC (Energy Release Component), BI (Burning Index), and SFDI (Severe Fire Danger Index). Two fuel scenarios, G and LAF, are input into ERC, BI, and SFDI. By mid-century, most regions are projected to see an increase in the length of fire season, though the magnitude of this projected change varies considerably by region and fire index (and the latter’s sensitivity to precipitation). Agreement on a lengthening of the season by up to 50% is strongest across simulations and fire indexes over the Southern Plains and Southwest U.S. Changes in fire season severity are largest and most consistent across indexes for the U.S. west of the Mississippi River, excluding the intermountain West, where uncertainty is higher across the indexes and RCMs. An approximately 2- to 6-fold increase in the number of days that reach the severe fire danger threshold is projected by mid-century. Simulations for the far future are qualitatively similar, but the projected changes are quantitatively worse and more widespread.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".