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Integrating fire spread patterns in fire modelling at landscape scale

Affiliation:	1. CEMFOR – CTFC, InForest Joint Research Unit, CSIC-CTFC-CREAF, Solsona 25280, Spain;2. Centre de Recerca Ecològica i Aplicacions Forestals (CREAF), Cerdanyola del Vallés 08193, Spain;3. Centre d’Étude de la Forêt, Université du Québec à Montréal, Montréal H2X 3Y7, Canada;4. CSIC, Cerdanyola del Vallès 08193, Spain;1. N.I. Lobatchevsky State University, Nizhni Novgorod, Russia;2. Architecture State University, Nizhni Novgorod, Russia;3. Institute of Applied Physics of Russian Academy of Science, Nizhni Novgorod, Russia;4. University of Calabria, Rende, Italy;5. Institute of High Performance Computing and Networking of the National Research Council of Italy, Italy;6. Hayakawa Institute of Seismo Electromagnetics Co. Ltd., UEC Incubation Center-508, 1-5-1 Chofugaoka, Chofu, Tokyo 182-8585, Japan;7. Advanced Wireless Communications Research Center and Research Station on Seismo Electromagnetics, The Univ. of Electro-Communications (UEC), 1-5-1 Chofugaoka, Chofu, Tokyo 182-8585, Japan;1. Université des Sciences et Technologie d’Oran, LEPM, BP 1505 El Mnaouer, Oran, Algeria;2. Aix Marseille Université, CNRS, IUSTI UMR 7343, 13453, Marseille, France;3. ADAI/CEIF, University of Coimbra, Rua Luis Reis dos Santos, Coimbra, 3030-788, Portugal;1. Forest Sciences Centre of Catalonia (CTFC-CEMFOR), Carretera vella de Sant Llorenç de Morunys km 2, 25280 Solsona, Lleida, Spain;2. CREAF, Edifici C, Autonomous University of Barcelona, 08193 Bellaterra, Barcelona, Spain;3. CSIC, Cerdanyola del Vallès 08193, Spain;1. Tecnosylva, León, 24009, Spain;2. Department of Natural Resources and Society, College of Natural Resources, University of Idaho, Moscow, ID, 83843, USA;3. Technosylva, La Jolla, CA, 92037, USA;1. InForest Jru (CREAF-CTFC), Crta. de Sant Llorenç de Morunys, Km. 2, 25280 Solsona, Spain;2. Centre for Forest Research (CFR), Université du Québec à Montréal (UQAM), C.P. 8888, succ. Centre-Ville, Montréal, QC, H3C 3P8, Canada;3. CREAF, Campus de Bellaterra (UAB), Edifici C 08193, Cerdanyola del Vallès, Spain;4. CSIC, 08193, Cerdanyola del Vallès, Spain

Abstract:	Fire spread modelling in landscape fire succession models needs to improve to handle uncertainty under global change processes and the resulting impact on forest systems. Linking fire spread patterns to synoptic-scale weather situations are a promising approach to simulating fire spread without fine-grained weather data. Here we present MedSpread—a model that evaluates the weights of five landscape factors in fire spread performance. We readjusted the factor weights for convective, topography-driven and wind-driven fires (n = 123) and re-assessed each fire spread group's performance against seven other control simulations. Results show that for each of the three fire spread patterns, some landscape factors exert a higher influence on fire spread simulation than others. We also found strong evidence that separating fires by fire spread pattern improves model performances. This study shows a promising link between relevant fire weather information, fire spread and fire regime simulation under global change processes.

Keywords:	Wind-driven fires Topography-driven fires Convective fires Landscape fire succession models Mediterranean ecosystems Synoptic weather situations
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