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Volume 10, issue 12 | Copyright
Geosci. Model Dev., 10, 4443-4476, 2017
https://doi.org/10.5194/gmd-10-4443-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Model description paper 06 Dec 2017

Model description paper | 06 Dec 2017

A data-driven approach to identify controls on global fire activity from satellite and climate observations (SOFIA V1)

Matthias Forkel et al.
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Andela, N., Liu, Y. Y., van Dijk, A. I. J. M., de Jeu, R. A. M., and McVicar, T. R.: Global changes in dryland vegetation dynamics (1988–2008) assessed by satellite remote sensing: comparing a new passive microwave vegetation density record with reflective greenness data, Biogeosciences, 10, 6657–6676, https://doi.org/10.5194/bg-10-6657-2013, 2013.
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Short summary
Wildfires affect infrastructures, vegetation, and the atmosphere. However, it is unclear how fires should be accurately represented in global vegetation models. We introduce here a new flexible data-driven fire modelling approach that allows us to explore sensitivities of burned areas to satellite and climate datasets. Our results suggest combining observations with data-driven and process-oriented fire models to better understand the role of fires in the Earth system.
Wildfires affect infrastructures, vegetation, and the atmosphere. However, it is unclear how...
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