FireMAFS was led by Dr Martin Wooster (Kings College, London) with 9 co-investigators from UCL, University of Leister, University of Reading, ESSC, University of Bristol and CEH.
Fire is the most important disturbance agent worldwide in terms of area and variety of biomes affected, a major mechanism by which carbon is transferred from the land to the atmosphere, and a globally significant source of aerosols and many trace gas species. Despite such clear coupling between fire, climate, and vegetation, fire is not currently modelled as an interactive component of the climate/earth systems models of full complexity or intermediate complexity that are used to model terrestrial ecosystem processes principally for simulating CO2 exchanges.
The objective of FireMAFS was to resolve these limitations by developing a robust method to forecast fire activity (fire 'danger' indices, ignition probabilities, burnt area, fire intensity etc) via a process-based model of fire-vegetation interactions, tested, improved, and constrained using state-of-the-art EO data products and driven by seasonal weather forecasts issued with many months lead-time.
Much of the activity of FireMAFS was shaped by the research and technical priorities of QUEST-ESM. The development of sub-models has enabled fire to be well represented in the QUEST-ESM model, which has allowed progress towards a capability for fire risk forecasting in the context of global change.