Response of simulated burned area to historical changes in environmental and anthropogenic factors: a comparison of seven fire models

<p>Understanding how fire regimes change over time is of major importance for understanding their future impact on the Earth system, including society. Large differences in simulated burned area between fire models show that there is substantial uncertainty associated with modelling global cha...

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Main Authors: L. Teckentrup, S. P. Harrison, S. Hantson, A. Heil, J. R. Melton, M. Forrest, F. Li, C. Yue, A. Arneth, T. Hickler, S. Sitch, G. Lasslop
Format: Article
Language:English
Published: Copernicus Publications 2019-10-01
Series:Biogeosciences
Online Access:https://www.biogeosciences.net/16/3883/2019/bg-16-3883-2019.pdf
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author L. Teckentrup
S. P. Harrison
S. Hantson
A. Heil
J. R. Melton
M. Forrest
F. Li
C. Yue
A. Arneth
T. Hickler
S. Sitch
G. Lasslop
G. Lasslop
author_facet L. Teckentrup
S. P. Harrison
S. Hantson
A. Heil
J. R. Melton
M. Forrest
F. Li
C. Yue
A. Arneth
T. Hickler
S. Sitch
G. Lasslop
G. Lasslop
author_sort L. Teckentrup
collection DOAJ
description <p>Understanding how fire regimes change over time is of major importance for understanding their future impact on the Earth system, including society. Large differences in simulated burned area between fire models show that there is substantial uncertainty associated with modelling global change impacts on fire regimes. We draw here on sensitivity simulations made by seven global dynamic vegetation models participating in the Fire Model Intercomparison Project (FireMIP) to understand how differences in models translate into differences in fire regime projections. The sensitivity experiments isolate the impact of the individual drivers on simulated burned area, which are prescribed in the simulations. Specifically these drivers are atmospheric <span class="inline-formula">CO<sub>2</sub></span> concentration, population density, land-use change, lightning and climate.</p> <p>The seven models capture spatial patterns in burned area. However, they show considerable differences in the burned area trends since 1921. We analyse the trajectories of differences between the sensitivity and reference simulation to improve our understanding of what drives the global trends in burned area. Where it is possible, we link the inter-model differences to model assumptions.</p> <p>Overall, these analyses reveal that the largest uncertainties in simulating global historical burned area are related to the representation of anthropogenic ignitions and suppression and effects of land use on vegetation and fire. In line with previous studies this highlights the need to improve our understanding and model representation of the relationship between human activities and fire to improve our abilities to model fire within Earth system model applications. Only two models show a strong response to atmospheric <span class="inline-formula">CO<sub>2</sub></span> concentration. The effects of changes in atmospheric <span class="inline-formula">CO<sub>2</sub></span> concentration on fire are complex and quantitative information of how fuel loads and how flammability changes due to this factor is missing. The response to lightning on global scale is low. The response of burned area to climate is spatially heterogeneous and has a strong inter-annual variation. Climate is therefore likely more important than the other factors for short-term variations and extremes in burned area. This study provides a basis to understand the uncertainties in global fire<span id="page3884"/> modelling. Both improvements in process understanding and observational constraints reduce uncertainties in modelling burned area trends.</p>
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spelling doaj.art-6a343e53dc314a6d9e7396c9b4db98cc2022-12-22T00:09:16ZengCopernicus PublicationsBiogeosciences1726-41701726-41892019-10-01163883391010.5194/bg-16-3883-2019Response of simulated burned area to historical changes in environmental and anthropogenic factors: a comparison of seven fire modelsL. Teckentrup0S. P. Harrison1S. Hantson2A. Heil3J. R. Melton4M. Forrest5F. Li6C. Yue7A. Arneth8T. Hickler9S. Sitch10G. Lasslop11G. Lasslop12Max Planck Institute for Meteorology, Land in the Earth System, Bundesstraße 53, Hamburg, GermanySchool of Archaeology, Geography and Environmental Sciences (SAGES), University of Reading, Whiteknights, Reading, UKKarlsruhe Institute of Technology, Institute of Meteorology and Climate Research, Atmospheric Environmental Research, 82467 Garmisch-Partenkirchen, GermanyMax Planck Institute for Meteorology, Land in the Earth System, Bundesstraße 53, Hamburg, GermanyClimate Research Division, Environment Canada, Victoria, BC, V8W 2Y2, CanadaSenckenberg Biodiversity and Climate Research Institute (BiK-F), 60325 Frankfurt am Main, GermanyInternational Center for Climate and Environment Sciences, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, ChinaLaboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL,CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, FranceKarlsruhe Institute of Technology, Institute of Meteorology and Climate Research, Atmospheric Environmental Research, 82467 Garmisch-Partenkirchen, GermanySenckenberg Biodiversity and Climate Research Institute (BiK-F), 60325 Frankfurt am Main, GermanyCollege of Life and Environmental Sciences, University of Exeter, Exeter, UKMax Planck Institute for Meteorology, Land in the Earth System, Bundesstraße 53, Hamburg, GermanySenckenberg Biodiversity and Climate Research Institute (BiK-F), 60325 Frankfurt am Main, Germany<p>Understanding how fire regimes change over time is of major importance for understanding their future impact on the Earth system, including society. Large differences in simulated burned area between fire models show that there is substantial uncertainty associated with modelling global change impacts on fire regimes. We draw here on sensitivity simulations made by seven global dynamic vegetation models participating in the Fire Model Intercomparison Project (FireMIP) to understand how differences in models translate into differences in fire regime projections. The sensitivity experiments isolate the impact of the individual drivers on simulated burned area, which are prescribed in the simulations. Specifically these drivers are atmospheric <span class="inline-formula">CO<sub>2</sub></span> concentration, population density, land-use change, lightning and climate.</p> <p>The seven models capture spatial patterns in burned area. However, they show considerable differences in the burned area trends since 1921. We analyse the trajectories of differences between the sensitivity and reference simulation to improve our understanding of what drives the global trends in burned area. Where it is possible, we link the inter-model differences to model assumptions.</p> <p>Overall, these analyses reveal that the largest uncertainties in simulating global historical burned area are related to the representation of anthropogenic ignitions and suppression and effects of land use on vegetation and fire. In line with previous studies this highlights the need to improve our understanding and model representation of the relationship between human activities and fire to improve our abilities to model fire within Earth system model applications. Only two models show a strong response to atmospheric <span class="inline-formula">CO<sub>2</sub></span> concentration. The effects of changes in atmospheric <span class="inline-formula">CO<sub>2</sub></span> concentration on fire are complex and quantitative information of how fuel loads and how flammability changes due to this factor is missing. The response to lightning on global scale is low. The response of burned area to climate is spatially heterogeneous and has a strong inter-annual variation. Climate is therefore likely more important than the other factors for short-term variations and extremes in burned area. This study provides a basis to understand the uncertainties in global fire<span id="page3884"/> modelling. Both improvements in process understanding and observational constraints reduce uncertainties in modelling burned area trends.</p>https://www.biogeosciences.net/16/3883/2019/bg-16-3883-2019.pdf
spellingShingle L. Teckentrup
S. P. Harrison
S. Hantson
A. Heil
J. R. Melton
M. Forrest
F. Li
C. Yue
A. Arneth
T. Hickler
S. Sitch
G. Lasslop
G. Lasslop
Response of simulated burned area to historical changes in environmental and anthropogenic factors: a comparison of seven fire models
Biogeosciences
title Response of simulated burned area to historical changes in environmental and anthropogenic factors: a comparison of seven fire models
title_full Response of simulated burned area to historical changes in environmental and anthropogenic factors: a comparison of seven fire models
title_fullStr Response of simulated burned area to historical changes in environmental and anthropogenic factors: a comparison of seven fire models
title_full_unstemmed Response of simulated burned area to historical changes in environmental and anthropogenic factors: a comparison of seven fire models
title_short Response of simulated burned area to historical changes in environmental and anthropogenic factors: a comparison of seven fire models
title_sort response of simulated burned area to historical changes in environmental and anthropogenic factors a comparison of seven fire models
url https://www.biogeosciences.net/16/3883/2019/bg-16-3883-2019.pdf
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