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.