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Title: The status and challenge of global fire modelling

Abstract

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. In conclusion, 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.

Authors:
 [1];  [1];  [2];  [2];  [3];  [4];  [5];  [6];  [7];  [8];  [9];  [10];  [11];  [12];  [13];  [14];  [15];  [16];  [15];  [17] more »;  [18];  [19];  [20];  [12];  [21];  [22];  [18];  [10] « less
  1. Karlsruhe Institute of Technology, Garmisch-Partenkirchen (Germany)
  2. Univ. of Reading, Reading (United Kingdom); Macquarie Univ., North Ryde, NSW (Australia)
  3. Macquarie Univ., North Ryde, NSW (Australia); Imperial College, Ascot (United Kingdom)
  4. Princeton Univ., Princeton, NJ (United States)
  5. Univ. of the Witwatersrand, Johannesburg (South Africa); Natural Resources and the Environment, Pretoria (South Africa)
  6. Univ. Paul-Valery, Montpellier Cedex (France)
  7. Univ. of Leeds, Leeds (United Kingdom)
  8. Univ. of Sao Paulo, Sao Paulo (Brazil)
  9. Oregon State Univ., Corvallis, OR (United States); Conservation Biology Institute, Corvallis, OR (United States)
  10. Univ. Paris-Saclay, Gif-sur-Yvette (France)
  11. Senckenberg Biodiversity and Climate Research Institute (BiK-F), Frankfurt am Main (Germany)
  12. Univ. of Exeter, Exeter (United Kingdom)
  13. Senckenberg Biodiversity and Climate Research Institute (BiK-F), Frankfurt am Main (Germany); Goethe Univ., Frankfurt am Main (Germany)
  14. Univ. of Lausanne, Lausanne (Switzerland)
  15. Max Planck Institute for Meteorology, Hamburg (Germany)
  16. Lund Univ., Lund (Sweden)
  17. Chinese Academy of Sciences (CAS), Beijing (China)
  18. Imperial College, London (United Kingdom)
  19. Environment Canada, Victoria, BC (Canada)
  20. Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen (Germany)
  21. Open Univ., Milton Keynes (United Kingdom); Max Planck Institute for Chemistry, Mainz (Germany)
  22. VU Univ. Amsterdam, Amsterdam (The Netherlands)
Publication Date:
Research Org.:
Karlsruhe Institute of Technology, Garmisch-Partenkirchen (Germany). Institute of Meteorology and Climate research, Atmospheric Environmental Research
Sponsoring Org.:
USDOE
OSTI Identifier:
1375423
Grant/Contract Number:  
603445; 603542
Resource Type:
Accepted Manuscript
Journal Name:
Biogeosciences (Online)
Additional Journal Information:
Journal Name: Biogeosciences (Online); Journal Volume: 13; Journal Issue: 11; Journal ID: ISSN 1726-4189
Publisher:
European Geosciences Union
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES

Citation Formats

Hantson, Stijn, Arneth, Almut, Harrison, Sandy P., Kelley, Douglas I., Prentice, I. Colin, Rabin, Sam S., Archibald, Sally, Mouillot, Florent, Arnold, Steve R., Artaxo, Paulo, Bachelet, Dominique, Ciais, Philippe, Forrest, Matthew, Friedlingstein, Pierre, Hickler, Thomas, Kaplan, Jed O., Kloster, Silvia, Knorr, Wolfgang, Lasslop, Gitta, Li, Fang, Mangeon, Stephane, Melton, Joe R., Meyn, Andrea, Sitch, Stephen, Spessa, Allan, van der Werf, Guido R., Voulgarakis, Apostolos, and Yue, Chao. The status and challenge of global fire modelling. United States: N. p., 2016. Web. doi:10.5194/bg-13-3359-2016.
Hantson, Stijn, Arneth, Almut, Harrison, Sandy P., Kelley, Douglas I., Prentice, I. Colin, Rabin, Sam S., Archibald, Sally, Mouillot, Florent, Arnold, Steve R., Artaxo, Paulo, Bachelet, Dominique, Ciais, Philippe, Forrest, Matthew, Friedlingstein, Pierre, Hickler, Thomas, Kaplan, Jed O., Kloster, Silvia, Knorr, Wolfgang, Lasslop, Gitta, Li, Fang, Mangeon, Stephane, Melton, Joe R., Meyn, Andrea, Sitch, Stephen, Spessa, Allan, van der Werf, Guido R., Voulgarakis, Apostolos, & Yue, Chao. The status and challenge of global fire modelling. United States. doi:10.5194/bg-13-3359-2016.
Hantson, Stijn, Arneth, Almut, Harrison, Sandy P., Kelley, Douglas I., Prentice, I. Colin, Rabin, Sam S., Archibald, Sally, Mouillot, Florent, Arnold, Steve R., Artaxo, Paulo, Bachelet, Dominique, Ciais, Philippe, Forrest, Matthew, Friedlingstein, Pierre, Hickler, Thomas, Kaplan, Jed O., Kloster, Silvia, Knorr, Wolfgang, Lasslop, Gitta, Li, Fang, Mangeon, Stephane, Melton, Joe R., Meyn, Andrea, Sitch, Stephen, Spessa, Allan, van der Werf, Guido R., Voulgarakis, Apostolos, and Yue, Chao. Thu . "The status and challenge of global fire modelling". United States. doi:10.5194/bg-13-3359-2016. https://www.osti.gov/servlets/purl/1375423.
@article{osti_1375423,
title = {The status and challenge of global fire modelling},
author = {Hantson, Stijn and Arneth, Almut and Harrison, Sandy P. and Kelley, Douglas I. and Prentice, I. Colin and Rabin, Sam S. and Archibald, Sally and Mouillot, Florent and Arnold, Steve R. and Artaxo, Paulo and Bachelet, Dominique and Ciais, Philippe and Forrest, Matthew and Friedlingstein, Pierre and Hickler, Thomas and Kaplan, Jed O. and Kloster, Silvia and Knorr, Wolfgang and Lasslop, Gitta and Li, Fang and Mangeon, Stephane and Melton, Joe R. and Meyn, Andrea and Sitch, Stephen and Spessa, Allan and van der Werf, Guido R. and Voulgarakis, Apostolos and Yue, Chao},
abstractNote = {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. In conclusion, 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.},
doi = {10.5194/bg-13-3359-2016},
journal = {Biogeosciences (Online)},
number = 11,
volume = 13,
place = {United States},
year = {2016},
month = {6}
}

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    Climate Change Penalty to Ozone Air Quality: Review of Current Understandings and Knowledge Gaps
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    Lightning as a major driver of recent large fire years in North American boreal forests
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    Climate Change Penalty to Ozone Air Quality: Review of Current Understandings and Knowledge Gaps
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    Lightning as a major driver of recent large fire years in North American boreal forests
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    • Nature Climate Change, Vol. 7, Issue 7
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    Substantial large-scale feedbacks between natural aerosols and climate
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    Deep learning and process understanding for data-driven Earth system science
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    Competing consumers: contrasting the patterns and impacts of fire and mammalian herbivory in Africa
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    Resilience of tropical tree cover: The roles of climate, fire, and herbivory
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    A data-driven approach to identify controls on global fire activity from satellite and climate observations (SOFIA V1)
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