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© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 08 Mar 2019

Research article | 08 Mar 2019

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This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Chemistry and Physics (ACP).

Historical (1700–2012) Global Multi-model Estimates of the Fire Emissions from the Fire Modeling Intercomparison Project (FireMIP)

Fang Li1, Maria Val Martin2, Stijn Hantson3,4, Meinrat O. Andreae5, Almut Arneth4, Gitta Lasslop6, Chao Yue7,8, Dominique Bachelet9, Matthew Forrest6, Johannes W. Kaiser10,5, Erik Kluzek11, Xiaohong Liu12, Joe R. Melton13, Daniel S. Ward14, Anton Darmenov15, Thomas Hickler6,16, Charles Ichoku17, Brian I. Magi18, Stephen Sitch19, Guido R. van der Werf20, and Christine Wiedinmyer21 Fang Li et al.
  • 1International Center for Climate and Environment Sciences, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
  • 2Leverhulme Center for Climate Change Mitigation, Department of Animal & Plant Sciences, Sheffield University, Sheffield, UK
  • 3Geospatial Data Solutions Center, University of California, Irvine, CA, USA
  • 4Karlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate research, Atmospheric Environmental Research, Garmisch-Partenkirchen, Germany
  • 5Max Planck Institute for Chemistry, Mainz, Germany
  • 6Senckenberg Biodiversity and Climate Research Institute (BiK-F), Senckenberganlage, Germany
  • 7Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
  • 8State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling, Shanxi, China
  • 9Biological and Ecological Engineering, Oregon State University, Corvallis, OR, USA
  • 10Deutscher Wetterdienst, Offenbach, Germany
  • 11National Center for Atmospheric Research, Boulder, CO, USA
  • 12Department of Atmospheric Science, University of Wyoming, Laramie, WY, USA
  • 13Climate Research Division, Environment and Climate Change Canada, Victoria, BC, Canada
  • 14Karen Clark and Company, Boston, MA, USA
  • 15Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
  • 16Department of Physical Geography, Goethe University, Frankfurt am Main, Germany
  • 17Howard University, NW, Washington, DC, USA
  • 18Department of Geography and Earth Sciences, University of North Carolina at Charlotte, Charlotte, NC, USA
  • 19College of Life and Environmental Sciences, University of Exeter, Exeter, UK
  • 20Faculty of Science, Vrije Universiteit, Amsterdam, The Netherlands
  • 21University of Colorado Boulder, Boulder, CO, USA

Abstract. Fire emissions are critical for carbon and nutrient cycles, climate, and air quality. Dynamic Global Vegetation Models (DGVMs) with interactive fire modeling provide important estimates for long-term and large-scale changes of fire emissions. Here we present the first multi-model estimates of global gridded historical fire emissions for 1700–2012, including carbon and 33 species of trace gases and aerosols. The dataset is based on simulations of nine DGVMs with different state-of-the-art global fire models that participated in the Fire Modeling Intercomparison Project (FireMIP), using the same and standardized protocols and forcing data, and the most up-to-date fire emission factor table from field and laboratory studies over various land cover types. We evaluate the simulations of present-day fire emissions by comparing them with satellite-based products. Evaluation results show that most DGVMs simulate present-day global fire emission totals within the range of satellite-based products, and can capture the high emissions over the tropical savannas, low emissions over the arid and sparsely vegetated regions, and the main features of seasonality. However, most of the models fail to simulate the interannual variability, partly due to a lack of modeling peat fires and tropical deforestation fires. Historically, all models show only a weak trend in global fire emissions before ~ 1850s, consistent with multi-source merged historical reconstructions. The long-term trends among DGVMs are quite different for the 20th century, with some models showing an increase and others a decrease in fire emissions, mainly as a result of the discrepancy in their simulated responses to human population density change and land-use and land-cover change (LULCC). Our study provides a basic dataset for developing regional and global multi-source merged historical reconstructions and merging methods, and analyzing historical changes of fire emissions and their uncertainties as well as their role in the Earth system. It also highlights the importance of accurately modeling the responses of fire emissions to LULCC and population density change in reducing uncertainties in historical reconstructions of fire emissions and providing more reliable future projections.

Fang Li et al.
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Fang Li et al.
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Short summary
Fire emissions are critical for atmospheric composition, climate, carbon cycle, and air quality. We provide the first global multi-model fire emission reconstructions for 1700–2012, including carbon and 33 species of trace gases and aerosols, based on the nine state-of-the-art global fire models that participated in FireMIP. We also provide information on recent status and limitations of the model-based reconstructions and identify the main uncertainty sources in their long-term changes.
Fire emissions are critical for atmospheric composition, climate, carbon cycle, and air quality....