Spatiotemporal analysis of the FWI over Europe and North Africa: Historical trends and climate projections under RCP4.5 and RCP8.5
Bibliographic record
Abstract
• FWI trends analyzed over Europe & N. Africa from 1979 to 2098. • Extreme fire danger increases under both RCP4.5 and RCP8.5 scenarios. • Strong agreement (r > 0.8) between reanalysis and GCMs in fire-prone areas. • Southern regions show significant increasing trends in FWI. Wildfires represent an escalating environmental threat across Europe and North Africa, increasingly exacerbated by climate-driven shifts in temperature, precipitation, and drought patterns. However, there is still limited large-scale, methodologically consistent research that simultaneously assesses historical patterns and future projections of fire danger across these regions, particularly in terms of both frequency and duration of risk under different climate scenarios. This study addresses this gap by providing a high-resolution, spatiotemporal assessment of fire weather conditions, with the aim of offering critical insights to support climate-adaptive fire management strategies, extended preparedness frameworks, and the integration of future fire weather projections into land-use and risk governance policies. To achieve this, we investigate historical (1979–2021) and projected (2000–2098) trends in fire danger using the Canadian Fire Weather Index (FWI), based on ERA5 reanalysis data and outputs from five Global Climate Models (GCMs) under RCP4.5 and RCP8.5 scenarios. Over 50,000 land grid cells were analyzed to assess the frequency and duration of six FWI danger classes. Different metrics were used to quantify the agreement between historical reanalysis data and GCM outputs, while the Seasonal Kendall (SK) test was applied to detect trends. Results reveal a substantial decline in the duration of the very low FWI class, from 36 to 23 months, and significant increases in both the duration and frequency of the extreme FWI class, reaching up to 6.38 months and 14.42 % under the RCP8.5 scenario. Correlation coefficients exceed 0.8 across much of Southern Europe and North Africa, indicating strong temporal agreement. Trend analyses reveal statistically significant increases in fire danger across southern latitudes, while Northern Europe shows mixed or decreasing trends. These findings project a dramatic intensification and expansion of fire-prone conditions, particularly under high-emission scenarios.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".