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SPITFIRE within the MPI Earth system model: Model development and evaluation

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Lasslop,  Gitta
Emmy Noether Junior Research Group Fire in the Earth System, The Land in the Earth System, MPI for Meteorology, Max Planck Society;

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Kloster,  Silvia
Emmy Noether Junior Research Group Fire in the Earth System, The Land in the Earth System, MPI for Meteorology, Max Planck Society;

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Citation

Lasslop, G., Thonicke, K., & Kloster, S. (2014). SPITFIRE within the MPI Earth system model: Model development and evaluation. Journal of Advances in Modeling Earth Systems, 6, 740-755. doi:10.1002/2013MS000284.


Cite as: https://hdl.handle.net/11858/00-001M-0000-001A-328E-E
Abstract
Quantification of the role of fire within the Earth system requires an adequate representation of fire as a climate-controlled process within an Earth system model. To be able to address questions on the interaction between fire and the Earth system, we implemented the mechanistic fire model SPITFIRE, in JSBACH, the land surface model of the MPI Earth system model. Here, we document the model implementation as well as model modifications. We evaluate our model results by comparing the simulation to the GFED version 3 satellite-based data set. In addition, we assess the sensitivity of the model to the meteorological forcing and to the spatial variability of a number of fire relevant model parameters. A first comparison of model results with burned area observations showed a strong correlation of the residuals with wind speed. Further analysis revealed that the response of the fire spread to wind speed was too strong for the application on global scale. Therefore, we developed an improved parametrization to account for this effect. The evaluation of the improved model shows that the model is able to capture the global gradients and the seasonality of burned area. Some areas of model-data mismatch can be explained by differences in vegetation cover compared to observations. We achieve benchmarking scores comparable to other state-of-theart fire models. The global total burned area is sensitive to the meteorological forcing. Adjustment of parameters leads to similar model results for both forcing data sets with respect to spatial and seasonal patterns