Optimization of the Canadian Fire Weather Index (FWI) for the Mediterranean region
Notice bibliographique
Résumé
Fire weather prognosis tools are of great importance for mitigating the catastrophic impacts of wildfires posed on human lives, valuable resources and assets. Their importance is getting higher if we reflect on the side effects of climate change such as rising temperatures, extreme drought phenomena and shifting precipitation patterns. These factors contribute to the heightened frequency and severity of wildfires. The Canadian Fire Weather Index (FWI) System stands out as one of the most extensively used tools for fire weather prognosis. Its reliability has been demonstrated across various forest types worldwide. Nevertheless, the FWI equations were initially developed within Canadian boreal forests, which posses different characteristics compared to other forest types, like Mediterranean forests, in terms of their vegetation and climatic conditions. The goal of this project is to refine the already effective Canadian Fire Danger System (FWI) and tailor it for the different characteristics of the Mediterranean climate reference region in order to get improved fire weather prognosis for that particular geographical region. The first part of the study is finding constants in the equations of the FWI that result from empirical calculations or laboratory tests with region specific characteristics and altering them so as to get different FWI values, that give better or worse fire weather prognosis. Each alteration is rated as better or worse depending on its correlation yield between the corresponding FWI values and Burned Area. The second part of the study is correlating the variables mentioned above using two methods. The first method is the correlation of all the grid boxes of the study region with Burned Area data and the second is the correlation on each grid box by itself providing that enough data of Burned Area is available for it. Firstly, this study indicates that an underlying positive correlation exists between the average monthly FWI values and the logBA values, which confirms the reliability of the Canadian FWI System. Secondly, using the first method of correlation, the altered FWI codes showed an increase in correlation of up to 10%, suggesting that optimizating the FWI for the Mediterranean climate refernce region is feasible. However, it is noticed that despite accomplishing the goal of increased correlation, there is a noteable difference between the FWI values of the optimized and original FWI code. Special attention should be given on this observation, since certain FWI values are associated with certain fire risk thresholds for different regions. Moreover, using the second method of correlation, from the Figures of Correlation Map and Correlation Map Difference, no clear pattern of increase or decrease in correlation was observed, throughout the study region. This pattern could be cleared out, either by using a broader study period or by accounting for the land use and vegetation type of each gridbox.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».