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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- Tripling of western US particulate pollution from wildfires in a warming climate Y. Xie et al. 10.1073/pnas.2111372119
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- Combining European Earth Observation products with Dynamic Global Vegetation Models for estimating Essential Biodiversity Variables M. Dantas de Paula et al. 10.1080/17538947.2019.1597187
- How contemporary bioclimatic and human controls change global fire regimes D. Kelley et al. 10.1038/s41558-019-0540-7
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- Modeling the short-term fire effects on vegetation dynamics and surface energy in southern Africa using the improved SSiB4/TRIFFID-Fire model H. Huang et al. 10.5194/gmd-14-7639-2021
- An improved combined vegetation difference index and burn scar index approach for mapping cropland burned areas using combined data from Landsat 8 multispectral and thermal infrared bands S. Liu et al. 10.1071/WF18146
- When do Farmers Burn Pasture in Brazil: A Model-Based Approach to Determine Burning Date M. Brunel et al. 10.1016/j.rama.2021.08.003
- Response of simulated burned area to historical changes in environmental and anthropogenic factors: a comparison of seven fire models L. Teckentrup et al. 10.5194/bg-16-3883-2019
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- Land-Cover Dependent Relationships between Fire and Soil Moisture A. Schaefer & B. Magi 10.3390/fire2040055
- A Global Analysis of Hunter-Gatherers, Broadcast Fire Use, and Lightning-Fire-Prone Landscapes M. Coughlan et al. 10.3390/fire1030041
- Emission Factors for Crop Residue and Prescribed Fires in the Eastern US During FIREX‐AQ K. Travis et al. 10.1029/2023JD039309
- 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
- Analysis fire patterns and drivers with a global SEVER-FIRE v1.0 model incorporated into dynamic global vegetation model and satellite and on-ground observations S. Venevsky et al. 10.5194/gmd-12-89-2019
- Representation of fire, land-use change and vegetation dynamics in the Joint UK Land Environment Simulator vn4.9 (JULES) C. Burton et al. 10.5194/gmd-12-179-2019
- Emergent relationships with respect to burned area in global satellite observations and fire-enabled vegetation models M. Forkel et al. 10.5194/bg-16-57-2019
1 citations as recorded by crossref.
Latest update: 14 Dec 2024
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...
