Climate-driven emergence of fire danger in South America under global warming
Bibliographic record
Abstract
Abstract This study assesses the capability of ten Coordinated Regional Climate Downscaling Experiment regional climate models to simulate the components of the Canadian fire weather index (FWI) system across South America. Model performance for the historical period (1951–2005) is evaluated against the Copernicus Emergency Management Service ERA5 reanalysis using correlation, root mean square error, bias, and inter-model variability as validation metrics. Future projections are analyzed using the time of emergence and global temperature of emergence frameworks under two representative concentration pathways (RCP4.5 and RCP8.5), to identify when and under which global warming levels fire-conducive conditions emerge beyond natural variability. Results show that FWI and the fine fuel moisture code reproduce observed variability most accurately ( r > 0.70), while cumulative indices such as the drought code and Duff moisture code exhibit larger uncertainties linked to precipitation biases and long-term moisture processes. Projections indicate that extreme fire weather conditions (represented by the frequency of days exceeding the 95th percentile of FWI, FWI95d) emerge earliest and most extensively, particularly under the high-emission RCP8.5 scenario, with large areas of northern and central South America crossing emergence thresholds during the early years of the 2030s decade. In contrast, indices related to fire-season length (FWIfwsl) and seasonal severity (FWIfs) show delayed and spatially fragmented emergence patterns, reflecting their stronger dependence on persistent warming trends. A critical finding is that several regions, including southern Brazil, Paraguay, northern Argentina, and Bolivia, have already exceeded emergence thresholds during the historical period, signaling that shifts in fire-weather regimes are already underway. These results highlight the urgent need to strengthen fire management and adaptation strategies across South America, while emphasizing that limiting global warming below 2 °C would significantly delay and reduce the extent of emerging fire danger in the region.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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; both teacher heads agree on what is shown here.
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".