Drivers of fire in the boreal forests: Data constrained design of a prognostic model of burned area for use in dynamic global vegetation models
International audience Boreal regions are an important component of the global carbon cycle because they host large stocks of aboveground and belowground carbon. Since boreal forest evolution is closely related to fire regimes, shifts in climate are likely to induce changes in ecosystems, potentiall...
Published in: | Journal of Geophysical Research |
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Main Authors: | , , , , |
Other Authors: | , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
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HAL CCSD
2007
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Online Access: | https://hal.science/hal-04110165 https://hal.science/hal-04110165/document https://hal.science/hal-04110165/file/Journal%20of%20Geophysical%20Research%20Atmospheres%20-%202007%20-%20Crevoisier%20-%20Drivers%20of%20fire%20in%20the%20boreal%20forests%20Data%20constrained.pdf https://doi.org/10.1029/2006JD008372 |
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ftecoleponts:oai:HAL:hal-04110165v1 |
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record_format |
openpolar |
institution |
Open Polar |
collection |
École des Ponts ParisTech: HAL |
op_collection_id |
ftecoleponts |
language |
English |
topic |
Global Change: Biogeochemical cycles processes fire modeling boreal forest Earth Science [SDU]Sciences of the Universe [physics] |
spellingShingle |
Global Change: Biogeochemical cycles processes fire modeling boreal forest Earth Science [SDU]Sciences of the Universe [physics] Crevoisier, Cyril Shevliakova, Elena Gloor, Manuel Wirth, Christian Pacala, Steve Drivers of fire in the boreal forests: Data constrained design of a prognostic model of burned area for use in dynamic global vegetation models |
topic_facet |
Global Change: Biogeochemical cycles processes fire modeling boreal forest Earth Science [SDU]Sciences of the Universe [physics] |
description |
International audience Boreal regions are an important component of the global carbon cycle because they host large stocks of aboveground and belowground carbon. Since boreal forest evolution is closely related to fire regimes, shifts in climate are likely to induce changes in ecosystems, potentially leading to a large release of carbon and other trace gases to the atmosphere. Prediction of the effect of this potential climate feedback on the Earth system is therefore important and requires the modeling of fire as a climate driven process in dynamic global vegetation models (DGVMs). Here, we develop a new data-based prognostic model, for use in DGVMs, to estimate monthly burned area from four climate (precipitation, temperature, soil water content and relative humidity) and one human-related (road density) predictors for boreal forest. The burned area model is a function of current climatic conditions and is thus responsive to climate change. Model parameters are estimated using a Markov Chain Monte Carlo method applied to on ground observations from the Canadian Large Fire Database. The model is validated against independent observations from three boreal regions: Canada, Alaska and Siberia. Provided realistic climate predictors, the model is able to reproduce the seasonality, intensity and interannual variability of burned area, as well as the location of fire events. In particular, the model simulates well the timing of burning events, with two thirds of the events predicted for the correct month and almost all the rest being predicted 1 month before or after the observed event. The predicted annual burned area is in the range of various current estimates. The estimated annual relative error (standard deviation) is twelve percent in a grid cell, which makes the model suitable to study quantitatively the evolution of burned area with climate. |
author2 |
Laboratoire de Météorologie Dynamique (UMR 8539) (LMD) Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X) Institut Polytechnique de Paris (IP Paris)-Institut Polytechnique de Paris (IP Paris)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris École normale supérieure - Paris (ENS-PSL) Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-École normale supérieure - Paris (ENS-PSL) Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL) |
format |
Article in Journal/Newspaper |
author |
Crevoisier, Cyril Shevliakova, Elena Gloor, Manuel Wirth, Christian Pacala, Steve |
author_facet |
Crevoisier, Cyril Shevliakova, Elena Gloor, Manuel Wirth, Christian Pacala, Steve |
author_sort |
Crevoisier, Cyril |
title |
Drivers of fire in the boreal forests: Data constrained design of a prognostic model of burned area for use in dynamic global vegetation models |
title_short |
Drivers of fire in the boreal forests: Data constrained design of a prognostic model of burned area for use in dynamic global vegetation models |
title_full |
Drivers of fire in the boreal forests: Data constrained design of a prognostic model of burned area for use in dynamic global vegetation models |
title_fullStr |
Drivers of fire in the boreal forests: Data constrained design of a prognostic model of burned area for use in dynamic global vegetation models |
title_full_unstemmed |
Drivers of fire in the boreal forests: Data constrained design of a prognostic model of burned area for use in dynamic global vegetation models |
title_sort |
drivers of fire in the boreal forests: data constrained design of a prognostic model of burned area for use in dynamic global vegetation models |
publisher |
HAL CCSD |
publishDate |
2007 |
url |
https://hal.science/hal-04110165 https://hal.science/hal-04110165/document https://hal.science/hal-04110165/file/Journal%20of%20Geophysical%20Research%20Atmospheres%20-%202007%20-%20Crevoisier%20-%20Drivers%20of%20fire%20in%20the%20boreal%20forests%20Data%20constrained.pdf https://doi.org/10.1029/2006JD008372 |
genre |
Alaska Siberia |
genre_facet |
Alaska Siberia |
op_source |
ISSN: 2169-897X EISSN: 2169-8996 Journal of Geophysical Research: Atmospheres https://hal.science/hal-04110165 Journal of Geophysical Research: Atmospheres, 2007, 112, ⟨10.1029/2006JD008372⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1029/2006JD008372 hal-04110165 https://hal.science/hal-04110165 https://hal.science/hal-04110165/document https://hal.science/hal-04110165/file/Journal%20of%20Geophysical%20Research%20Atmospheres%20-%202007%20-%20Crevoisier%20-%20Drivers%20of%20fire%20in%20the%20boreal%20forests%20Data%20constrained.pdf BIBCODE: 2007JGRD.11224112C doi:10.1029/2006JD008372 |
op_rights |
http://hal.archives-ouvertes.fr/licences/copyright/ info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.1029/2006JD008372 |
container_title |
Journal of Geophysical Research |
container_volume |
112 |
container_issue |
D24 |
_version_ |
1810485918773018624 |
spelling |
ftecoleponts:oai:HAL:hal-04110165v1 2024-09-15T18:41:31+00:00 Drivers of fire in the boreal forests: Data constrained design of a prognostic model of burned area for use in dynamic global vegetation models Crevoisier, Cyril Shevliakova, Elena Gloor, Manuel Wirth, Christian Pacala, Steve Laboratoire de Météorologie Dynamique (UMR 8539) (LMD) Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X) Institut Polytechnique de Paris (IP Paris)-Institut Polytechnique de Paris (IP Paris)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris École normale supérieure - Paris (ENS-PSL) Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-École normale supérieure - Paris (ENS-PSL) Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL) 2007 https://hal.science/hal-04110165 https://hal.science/hal-04110165/document https://hal.science/hal-04110165/file/Journal%20of%20Geophysical%20Research%20Atmospheres%20-%202007%20-%20Crevoisier%20-%20Drivers%20of%20fire%20in%20the%20boreal%20forests%20Data%20constrained.pdf https://doi.org/10.1029/2006JD008372 en eng HAL CCSD American Geophysical Union info:eu-repo/semantics/altIdentifier/doi/10.1029/2006JD008372 hal-04110165 https://hal.science/hal-04110165 https://hal.science/hal-04110165/document https://hal.science/hal-04110165/file/Journal%20of%20Geophysical%20Research%20Atmospheres%20-%202007%20-%20Crevoisier%20-%20Drivers%20of%20fire%20in%20the%20boreal%20forests%20Data%20constrained.pdf BIBCODE: 2007JGRD.11224112C doi:10.1029/2006JD008372 http://hal.archives-ouvertes.fr/licences/copyright/ info:eu-repo/semantics/OpenAccess ISSN: 2169-897X EISSN: 2169-8996 Journal of Geophysical Research: Atmospheres https://hal.science/hal-04110165 Journal of Geophysical Research: Atmospheres, 2007, 112, ⟨10.1029/2006JD008372⟩ Global Change: Biogeochemical cycles processes fire modeling boreal forest Earth Science [SDU]Sciences of the Universe [physics] info:eu-repo/semantics/article Journal articles 2007 ftecoleponts https://doi.org/10.1029/2006JD008372 2024-08-13T23:47:27Z International audience Boreal regions are an important component of the global carbon cycle because they host large stocks of aboveground and belowground carbon. Since boreal forest evolution is closely related to fire regimes, shifts in climate are likely to induce changes in ecosystems, potentially leading to a large release of carbon and other trace gases to the atmosphere. Prediction of the effect of this potential climate feedback on the Earth system is therefore important and requires the modeling of fire as a climate driven process in dynamic global vegetation models (DGVMs). Here, we develop a new data-based prognostic model, for use in DGVMs, to estimate monthly burned area from four climate (precipitation, temperature, soil water content and relative humidity) and one human-related (road density) predictors for boreal forest. The burned area model is a function of current climatic conditions and is thus responsive to climate change. Model parameters are estimated using a Markov Chain Monte Carlo method applied to on ground observations from the Canadian Large Fire Database. The model is validated against independent observations from three boreal regions: Canada, Alaska and Siberia. Provided realistic climate predictors, the model is able to reproduce the seasonality, intensity and interannual variability of burned area, as well as the location of fire events. In particular, the model simulates well the timing of burning events, with two thirds of the events predicted for the correct month and almost all the rest being predicted 1 month before or after the observed event. The predicted annual burned area is in the range of various current estimates. The estimated annual relative error (standard deviation) is twelve percent in a grid cell, which makes the model suitable to study quantitatively the evolution of burned area with climate. Article in Journal/Newspaper Alaska Siberia École des Ponts ParisTech: HAL Journal of Geophysical Research 112 D24 |