Climatology and trend analysis (1987–2016) of fire weather in the <scp>Euro‐Mediterranean</scp>
Bibliographic record
Abstract
Abstract High‐resolution regional climate simulations were conducted for the past 30 years (1987–2016), focusing on the Euro‐Mediterranean region. The numerical simulations were used for computing the Canadian Fire Weather Index, for deriving the climatology of fire weather in the study area and investigating the presence of long‐term trends, with particular emphasis on extremes during the May to September period. Results suggest that the Euro‐Mediterranean fire weather follows a zonal pattern, characterized by adverse conditions occurring most frequently in the southern parts. Air temperature and relative humidity are the key drivers of fire weather in the study area, with precipitation and wind exerting less influence. Based on the conducted spatial trend analysis, extreme fire weather conditions have become more prevalent in the Iberian Peninsula and eastern Balkans, whereas declining trends occur in the Southeast Mediterranean basin. For both cases, the trends in fire weather extremes appear to coincide with trends in the input meteorological variables. Overall, the results of this study provide a new insight on the recent climatology and trends of fire weather in the Euro‐Mediterranean. Our dataset is publicly available on the Zenodo platform (DOI: 10.5281/zenodo.3713531 ).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.002 | 0.001 |
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".