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The status and challenge of global fire modelling

  • Stijn Hantson
  • , Almut Arneth
  • , Sandy P. Harrison
  • , Douglas I. Kelley
  • , I. Colin Prentice
  • , Sam S. Rabin
  • , Sally Archibald
  • , Florent Mouillot
  • , Steve R. Arnold
  • , Paulo Artaxo
  • , Dominique Bachelet
  • , Philippe Ciais
  • , Matthew Forrest
  • , Pierre Friedlingstein
  • , Thomas Hickler
  • , Jed O. Kaplan
  • , Silvia Kloster
  • , Wolfgang Knorr
  • , Gitta Lasslop
  • , Fang Li
  • Stephane Mangeon, Joe R. Melton, Andrea Meyn, Stephen Sitch, Allan Spessa, Guido R. Van Der Werf, Apostolos Voulgarakis, Chao Yue
  • Institute of Meteorology and Climate Research
  • University of Reading
  • Macquarie University
  • Imperial College London
  • Princeton University
  • University of the Witwatersrand, Johannesburg
  • Council for Scientific and Industrial Research
  • University of Montpellier (UMR MiVEGEC)
  • University of Leeds
  • University of São Paulo
  • Oregon State University
  • Conservation Biology Institute
  • Université Versailles-Saint Quentin
  • Senckenberg Biodiversity and Climate Research Centre
  • University of Exeter
  • Goethe University Frankfurt am Main
  • University of Lausanne
  • Max Planck Institute for Meteorology
  • Lund University
  • Institute of Atmospheric Physics Chinese Academy of Sciences
  • Meteorological Research Branch
  • Universität Karlsruhe/Forschungszentrum Karlsruhe
  • The Open University
  • Max Planck Institute for Chemistry
  • Vrije Universiteit Amsterdam

Résultats de recherche: Contribution à un journalArticleRevue par des pairs

Résumé

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. We indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.

langue originaleAnglais
Pages (de - à)3359-3375
Nombre de pages17
journalBiogeosciences
Volume13
Numéro de publication11
Les DOIs
étatPublié - 9 juin 2016
Modification externeOui

SDG des Nations Unies

Ce résultat contribue à ou aux Objectifs de développement durable suivants

  1. SDG 13 - Action climatique
    SDG 13 Action climatique

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