Increasing fire danger in the Netherlands due to climate change
Bibliographic record
Abstract
Background Temperatures and extreme weather events in Northwestern Europe are expected to increase due to climate change. As a result, longer and more intense water deficits are expected, resulting in weather conditions conducive to wildfires. Aims We assessed the impact of recent and future climate change on fire danger in the Netherlands. Methods Historical weather data and climate scenarios in combination with the Canadian Fire Weather Index (FWI) and Fine Fuel Moisture Code (FFMC) were used to assess historical and future trends in fire danger. Key results Our analyses showed that, especially during the last decade (2011–2020), the number of days at elevated fire danger has increased. The number of days with elevated fire danger is projected to double by mid-century compared to the reference period 1981–2010 for high emission scenarios. The days at elevated fire danger during the last decade were already comparable to predictions for 2085, indicating that the climate change scenarios may underestimate future fire danger. Conclusions Days at elevated fire danger increased over the last four decades and will continue to do so under future climate scenarios. Implications The Netherlands needs to prepare for more days with weather conducive to wildfires.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".