Articles | Volume 11, issue 2
https://doi.org/10.5194/gmd-11-815-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-11-815-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
02 Mar 2018
Model description paper |
| 02 Mar 2018
A fire model with distinct crop, pasture, and non-agricultural burning: use of new data and a model-fitting algorithm for FINAL.1
Department of Ecology & Evolutionary Biology, Princeton University, Princeton, NJ, USA
Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research/Atmospheric Environmental
Research, 82467 Garmisch-Partenkirchen, Germany
Daniel S. Ward
GFDL-Princeton University Cooperative Institute for Climate Science, Princeton, NJ, USA
now at: Karen Clark and Company, Boston, Massachusetts, USA
Sergey L. Malyshev
GFDL-Princeton University Cooperative Institute for Climate Science, Princeton, NJ, USA
Brian I. Magi
University of North Carolina at Charlotte, Geography and Earth Sciences Department, Charlotte, NC, USA
Elena Shevliakova
GFDL-Princeton University Cooperative Institute for Climate Science, Princeton, NJ, USA
Stephen W. Pacala
Department of Ecology & Evolutionary Biology, Princeton University, Princeton, NJ, USA
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- Modeling long-term fire impact on ecosystem characteristics and surface energy using a process-based vegetation–fire model SSiB4/TRIFFID-Fire v1.0 H. Huang et al. 10.5194/gmd-13-6029-2020
- Human Fire Use and Management: A Global Database of Anthropogenic Fire Impacts for Modelling J. Millington et al. 10.3390/fire5040087
- Abrupt loss and uncertain recovery from fires of Amazon forests under low climate mitigation scenarios I. Cano et al. 10.1073/pnas.2203200119
- Representation of the terrestrial carbon cycle in CMIP6 B. Gier et al. 10.5194/bg-21-5321-2024
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Latest update: 30 Mar 2025
Short summary
This paper describes a new fire model that for the first time simulates how fire is used on cropland and pasture in the modern day, as imposed using a recently developed dataset. A non-agricultural fire module is fit algorithmically against non-agricultural burned area. Fitting improves performance and the general global pattern of fire is represented, but some gaps remain. The novel separation of agricultural burning from other fire may necessitate new design thinking in the future.
This paper describes a new fire model that for the first time simulates how fire is used on...
