The wildFire cLimate impacts and Adaptation Model (FLAM) is able to capture complex impact of climate, population, and fuel availability on burned areas. FLAM uses a process-based fire parameterization algorithm that was originally developed to link a fire model with dynamic global vegetation models. The key features implemented in FLAM include fuel moisture computation based on the Canadian Fine Fuel Moisture Code (FFMC) index, and a procedure to calibrate regional fire suppression efficiency.
FLAM is based on a state-of-the-art large scale mechanistic fire modelling algorithm. Currently FLAM operates on a European scale with a daily time step and a spatial resolution of 25×25 km. All inputs in the FLAM are adjusted to fit this resolution. The FLAM uses daily climate data for temperature, precipitation, wind, and relative humidity. When calculating the human ignition probability, a gridded population density is used. Fuel available for burning is defined as a combination of litter and coarse woody debris (CWD) pools, excluding stem biomass. The fire suppression efficiency is implemented in FLAM as the probability of extinguishing a fire on a given day.
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Last edited: 24 May 2017
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Krasovskii A, Khabarov N, Migliavacca M, Kraxner F, & Obersteiner M (2016). Regional aspects of modelling burned areas in Europe. International Journal of Wildland Fire 25 (8): 811-818. DOI:10.1071/WF15012.
Khabarov N, Krasovskii AA, Obersteiner M, Swart R, Dosio A, San-Miguel-Ayanz J, Durrant T, Camia A, et al. (2016). Forest fires and adaptation options in Europe. Regional Environmental Change 16 (1): 21-30. DOI:10.1007/s10113-014-0621-0.
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