Articles | Volume 13, issue 7
https://doi.org/10.5194/gmd-13-3299-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/gmd-13-3299-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Quantitative assessment of fire and vegetation properties in simulations with fire-enabled vegetation models from the Fire Model Intercomparison Project
Atmospheric Environmental Research, Institute of Meteorology and
Climate Research, Karlsruhe Institute of Technology,
Garmisch-Partenkirchen, Germany
Geospatial Data Solutions Center, University of California Irvine, Irvine, CA
92697, USA
Douglas I. Kelley
UK Centre for Ecology and Hydrology, Wallingford OX10 8BB, UK
Almut Arneth
Atmospheric Environmental Research, Institute of Meteorology and
Climate Research, Karlsruhe Institute of Technology,
Garmisch-Partenkirchen, Germany
Sandy P. Harrison
School of Archaeology, Geography and Environmental Science,
University of Reading, Reading, UK
Sally Archibald
Centre for African Ecology, School of Animal, Plant and Environmental
Sciences, University of the Witwatersrand, Private Bag X3, WITS,
Johannesburg, 2050, South Africa
Dominique Bachelet
Biological and Ecological Engineering, Oregon State University,
Corvallis, OR 97331, USA
Matthew Forrest
Senckenberg Biodiversity and Climate Research Institute (BiK-F),
Senckenberganlage 25,
60325 Frankfurt am Main, Germany
Thomas Hickler
Senckenberg Biodiversity and Climate Research Institute (BiK-F),
Senckenberganlage 25,
60325 Frankfurt am Main, Germany
Institute of Physical Geography, Goethe University,
Altenhöferallee 1, 60438 Frankfurt am Main, Germany
Gitta Lasslop
Senckenberg Biodiversity and Climate Research Institute (BiK-F),
Senckenberganlage 25,
60325 Frankfurt am Main, Germany
International Center for Climate and Environmental Sciences,
Institute of Atmospheric Physics,
Chinese Academy of Sciences, Beijing, China
Stephane Mangeon
Department of Physics, Imperial College London, London, UK
now at: Data 61, CSIRO, Brisbane, Australia
Joe R. Melton
Climate Research Division, Environment and Climate Change Canada,
Victoria, BC V8W 2Y2, Canada
Lars Nieradzik
Department of Physical Geography and Ecosystem Science, Lund
University, 22362 Lund, Sweden
Sam S. Rabin
Atmospheric Environmental Research, Institute of Meteorology and
Climate Research, Karlsruhe Institute of Technology,
Garmisch-Partenkirchen, Germany
I. Colin Prentice
AXA Chair of Biosphere and Climate Impacts, Grand Challenges in
Ecosystem and the Environment, Department of Life Sciences and Grantham
Institute – Climate Change and the Environment, Imperial College London,
Silwood Park Campus, Buckhurst Road, Ascot SL5 7PY, UK
Tim Sheehan
Biological and Ecological Engineering, Oregon State University,
Corvallis, OR 97331, USA
Stephen Sitch
College of Life and Environmental Sciences, University of Exeter,
Exeter EX4 4RJ, UK
Lina Teckentrup
ARC Centre of Excellence for Climate Extremes, University of New
South Wales, Sydney, NSW, Australia
Climate Change Research Center, University of New South Wales,
Sydney, NSW 2052, Australia
Apostolos Voulgarakis
Department of Physics, Imperial College London, London, UK
Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91198 Gif-sur-Yvette, France
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- Reviewing the links and feedbacks between climate change and air pollution in Europe U. Im et al. 10.3389/fenvs.2022.954045
- Investigation of fire regime dynamics and modeling of burn area over India for the twenty-first century S. Bar et al. 10.1007/s11356-024-32922-w
- Emergent vulnerability to climate-driven disturbances in European forests G. Forzieri et al. 10.1038/s41467-021-21399-7
- A fiery wake-up call for climate science B. Sanderson & R. Fisher 10.1038/s41558-020-0707-2
- Building a machine learning surrogate model for wildfire activities within a global Earth system model Q. Zhu et al. 10.5194/gmd-15-1899-2022
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Short summary
Global fire–vegetation models are widely used, but there has been limited evaluation of how well they represent various aspects of fire regimes. Here we perform a systematic evaluation of simulations made by nine FireMIP models in order to quantify their ability to reproduce a range of fire and vegetation benchmarks. While some FireMIP models are better at representing certain aspects of the fire regime, no model clearly outperforms all other models across the full range of variables assessed.
Global fire–vegetation models are widely used, but there has been limited evaluation of how well...
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