Assessment and optimisation of SPITFIRE using EO data, and Bayesian probability and Markov
Chain Monte Carlo (MCMC) techniques
FireMAFS project: Gomez-Dans, Spessa, Wooster, Lewis
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* By-passing the vegetation dynamics and soil hydrology
components of LPJ.
LPJ: Lund Potsdam Dynamic Vegetation Model
SPITFIRE: Spread and Intensity of Fire and Emissions
Model
LPJ SPITFIRE… Above-ground fuel load.
SPITFIRE LPJ… Post-fire plant mortality and above-
ground biomass unburnt.
Improved PFT densities and distribution
Improved fuel load magnitudes and distribution
uncalibrated
calibratedMODISsatellite
White = 0% disparity
Light pink ~ 1% disparity
Dark red ~ 20% disparity
This gives a basis to further investigate structural and parameterisation problems with the fire model without having to worry too much about errors emanating from the vegetation model itself.
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