Future Climate Change Impact on Wildfire Danger over the Mediterranean: the case of Greece
Bibliographic record
Abstract
The Canadian Fire Weather Index (FWI) is a meteorologically based index designed initially to be used in Canada but it can also be used worldwide, including the Mediterranean, to estimate fire danger in a generalized fuel type based solely on weather observations. The four weather variables are measured and used as inputs to the FWI (rain accumulated over 24 h, temperature, relative humidity, and wind speed) are generally taken daily at noon local standard time. Recent studies have shown that temperature and precipitation in the Mediterranean, and more specifically in Greece are expected to change, indicating longer and more intense summer droughts that even extend out of season. In connection to this, the frequency of forest fire occurrence and intensity is on the rise. In the present study, the FWI index is used in order to assess changes in future fire danger conditions. To represent meteorological conditions, regional EURO-CORDEX climate model simulations over the Mediterranean and mainly Greece at a spatial resolution of 11 km, were utilized. In order to assess the impact of future climate change, we used two Representative Concentration Pathway (RCP) scenarios consisting of an optimistic emission scenario where emissions peak and decline beyond 2020 (RCP2.6) and a pessimistic scenario where emissions continue to rise throughout the century (RCP8.5). We compare the FWI projections for two future time periods, 2021-2050 and 2071-2100 with reference to the historical time period 1971-2000. Based on the critical fire risk threshold values that have been established in previous studies for the area of Greece, the days with critical fire risk were calculated for different Greek domains.
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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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".