Evaluation of forest fire models on a large observation database

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.