1Centre National de la Recherche Scientifique, Sciences Pour l'Environnement, Université di Corsica, BP 52, 20250 Corte, France
2Institut National de Recherche en Informatique et en Automatique, BP 105, 78 153 Le Chesnay CEDEX, France
3Centre d'Enseignement et de Recherche en Environnement Atmosphérique (joint laboratory \'Ecole des Ponts ParisTech & EDF R & D, Université Paris Est), Marne-la-Vallée, France
1Centre National de la Recherche Scientifique, Sciences Pour l'Environnement, Université di Corsica, BP 52, 20250 Corte, France
2Institut National de Recherche en Informatique et en Automatique, BP 105, 78 153 Le Chesnay CEDEX, France
3Centre d'Enseignement et de Recherche en Environnement Atmosphérique (joint laboratory \'Ecole des Ponts ParisTech & EDF R & D, Université Paris Est), Marne-la-Vallée, France
Correspondence: J. B. Filippi (filippi@univ-corse.fr)
Received: 16 Apr 2014 – Discussion started: 08 May 2014 – Revised: 30 Sep 2014 – Accepted: 01 Oct 2014 – Published: 27 Nov 2014
Abstract. This paper presents the evaluation of several fire propagation models using a large set of observed fires. The observation base is composed of 80 Mediterranean fire cases of different sizes, which come with the limited information available in an operational context (burned surface and approximative ignition point). Simulations for all cases are carried out with four different front velocity models. The results are compared with several error scoring methods applied to each of the 320 simulations. All tasks are performed in a fully automated manner, with simulations run as first guesses with no tuning for any of the models or cases. This approach leads to a wide range of simulation performance, including some of the bad simulation results to be expected in an operational context. Disregarding the quality of the input data, it is found that the models can be ranked based on their performance and that the most complex models outperform the more empirical ones. Data and source codes used for this paper are freely available to the community.
A set of 80 Mediterranean fire cases is used as an observation database for model evaluation. Simulations are carried out with 4 different front velocity models. The results are compared with several error scoring methods. All simulations are performed as automatic first guesses with no tuning, as an operational use. Regardless of the quality of the input data, it is found that the models can be ranked based on their performance and that the most complex models outperform the more empirical one.
A set of 80 Mediterranean fire cases is used as an observation database for model evaluation....
