Fire is an integral part of the Earth system, interacting in complex ways with humans, vegetation
and climate. Global fire activity is an important driver of the carbon cycle and could have important
feedback effects on climate in a climate change context. Despite its potential importance, fire
modelling as an integral part of global vegetation-climate models has only been developed in the
past two decades, following the availability of global fire activity satellite products. This research
aims to parameterize wildfire in an intermediate complexity earth system climate model coupled to
a dynamic global vegetation model. I used a mechanistic fire model which simulates a burned area
per grid cell based on a number of fires and the average burned area per fire. The fire
parametrization was originally designed and calibrated for more realistic weather with more
variability. Due to the simplicity of the atmosphere module of the climate model used, I explored
the effect smaller modelling timesteps as well as prescribing natural variability to the simulated
climatology. The simulations show no effect of timestep, while adding natural variability to the
simulated climatology improves the global spatial correlation (R) of burnt fraction with
observations. The best model (R=0,36; global burned area underestimated by 63%), however, does
not capture the crucial difference of fire regime between the highly burning tropical savannas and
the unburnt rainforests. This research shows the essential role of simulated weather variability
rather than modelling timestep in generating realistic fire patterns in the context of this earth system
climate model of intermediate complexity. Additional calibration could potentially improve the
simulated fire and would allow the simulation of potential feedbacks within the fire-climatevegetation system in a climate change context.