Assessment and optimisation of SPITFIRE using EO data, and Bayesian probability and Markov Chain...
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Transcript of Assessment and optimisation of SPITFIRE using EO data, and Bayesian probability and Markov Chain...
![Page 1: Assessment and optimisation of SPITFIRE using EO data, and Bayesian probability and Markov Chain Monte Carlo (MCMC) techniques FireMAFS project: Gomez-Dans,](https://reader036.fdocuments.us/reader036/viewer/2022081605/5a4d1b987f8b9ab0599c47ca/html5/thumbnails/1.jpg)
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
![Page 2: Assessment and optimisation of SPITFIRE using EO data, and Bayesian probability and Markov Chain Monte Carlo (MCMC) techniques FireMAFS project: Gomez-Dans,](https://reader036.fdocuments.us/reader036/viewer/2022081605/5a4d1b987f8b9ab0599c47ca/html5/thumbnails/2.jpg)
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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.
![Page 3: Assessment and optimisation of SPITFIRE using EO data, and Bayesian probability and Markov Chain Monte Carlo (MCMC) techniques FireMAFS project: Gomez-Dans,](https://reader036.fdocuments.us/reader036/viewer/2022081605/5a4d1b987f8b9ab0599c47ca/html5/thumbnails/3.jpg)
![Page 4: Assessment and optimisation of SPITFIRE using EO data, and Bayesian probability and Markov Chain Monte Carlo (MCMC) techniques FireMAFS project: Gomez-Dans,](https://reader036.fdocuments.us/reader036/viewer/2022081605/5a4d1b987f8b9ab0599c47ca/html5/thumbnails/4.jpg)
Improved PFT densities and distribution
![Page 5: Assessment and optimisation of SPITFIRE using EO data, and Bayesian probability and Markov Chain Monte Carlo (MCMC) techniques FireMAFS project: Gomez-Dans,](https://reader036.fdocuments.us/reader036/viewer/2022081605/5a4d1b987f8b9ab0599c47ca/html5/thumbnails/5.jpg)
Improved fuel load magnitudes and distribution
![Page 6: Assessment and optimisation of SPITFIRE using EO data, and Bayesian probability and Markov Chain Monte Carlo (MCMC) techniques FireMAFS project: Gomez-Dans,](https://reader036.fdocuments.us/reader036/viewer/2022081605/5a4d1b987f8b9ab0599c47ca/html5/thumbnails/6.jpg)
uncalibrated
calibratedMODISsatellite
![Page 7: Assessment and optimisation of SPITFIRE using EO data, and Bayesian probability and Markov Chain Monte Carlo (MCMC) techniques FireMAFS project: Gomez-Dans,](https://reader036.fdocuments.us/reader036/viewer/2022081605/5a4d1b987f8b9ab0599c47ca/html5/thumbnails/7.jpg)
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.