RandomFront 2.3 A physical parametrisation of fire-spotting for operational fire spread models: Implementation in WRF-Sfire and response analysis with LSFire+

Fire-spotting is often responsible for a dangerous flare up in the wildfire and causes secondary ignitions isolated from the primary fire zone leading to perilous situations. The main aim of the present research to provide a versatile probabilistic model for fire-spotting that is suitable for implem...

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Detalles Bibliográficos
Autores: Trucchia, A., Egorova, V., Butenko, A., Kaur, I., Pagnini, G.
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2018
País:España
Institución:Basque Center for Applied Mathematics (BCAM)
Repositorio:BIRD. BCAM's Institutional Repository Data
OAI Identifier:oai:bird.bcamath.org:20.500.11824/907
Acceso en línea:http://hdl.handle.net/20.500.11824/907
Access Level:acceso abierto
Palabra clave:Wildfire propagation
Fire spotting
statistical modelling
WRF-Sfire
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spelling RandomFront 2.3 A physical parametrisation of fire-spotting for operational fire spread models: Implementation in WRF-Sfire and response analysis with LSFire+Trucchia, A.Egorova, V.Butenko, A.Kaur, I.Pagnini, G.Wildfire propagationFire spottingstatistical modellingWRF-SfireFire-spotting is often responsible for a dangerous flare up in the wildfire and causes secondary ignitions isolated from the primary fire zone leading to perilous situations. The main aim of the present research to provide a versatile probabilistic model for fire-spotting that is suitable for implementation as a post-processing scheme at each time step in any of the existing operational large-scale wildfire propagation models, without calling for any major changes in the original framework. In particular, a complete physical parametrisation of fire-spotting is presented and the corresponding updated model RandomFront 2.3 is implemented in a coupled fire-atmosphere model : WRF-Sfire. A test case has been simulated and discussed. More- over, the results from different simulations with a simple model based on the Level Set Method, namely LSFire+, highlight the response of the parametrisation to varying fire intensities, wind conditions and different firebrand radii. The contribution of the firebrands towards increasing the fire perimeter varies according to different concurrent conditions and the simulations show results in agreement with the physical processes. Among the many rigorous approaches available in literature to model the firebrand transport and distribution, the approach presented here proves to be simple yet versatile for application to operational large-scale fire spread models.PhD grant "La Caixa 2014"201920192018info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/20.500.11824/907reponame:BIRD. BCAM's Institutional Repository Datainstname:Basque Center for Applied Mathematics (BCAM)Ingléshttps://www.geosci-model-dev.net/12/69/2019/gmd-12-69-2019-discussion.htmlinfo:eu-repo/grantAgreement/MINECO//SEV-2017-0718info:eu-repo/grantAgreement/MINECO//SEV-2013-0323info:eu-repo/grantAgreement/MINECO//MTM2016-76016-Rinfo:eu-repo/grantAgreement/MINECO//MTM2013-40824-Pinfo:eu-repo/grantAgreement/Gobierno Vasco/BERC/BERC.2018-2021info:eu-repo/grantAgreement/Gobierno Vasco/BERC/BERC.2014-2017Reconocimiento-NoComercial-CompartirIgual 3.0 Españahttp://creativecommons.org/licenses/by-nc-sa/3.0/es/info:eu-repo/semantics/openAccessoai:bird.bcamath.org:20.500.11824/9072026-06-19T12:47:47Z
dc.title.none.fl_str_mv RandomFront 2.3 A physical parametrisation of fire-spotting for operational fire spread models: Implementation in WRF-Sfire and response analysis with LSFire+
title RandomFront 2.3 A physical parametrisation of fire-spotting for operational fire spread models: Implementation in WRF-Sfire and response analysis with LSFire+
spellingShingle RandomFront 2.3 A physical parametrisation of fire-spotting for operational fire spread models: Implementation in WRF-Sfire and response analysis with LSFire+
Trucchia, A.
Wildfire propagation
Fire spotting
statistical modelling
WRF-Sfire
title_short RandomFront 2.3 A physical parametrisation of fire-spotting for operational fire spread models: Implementation in WRF-Sfire and response analysis with LSFire+
title_full RandomFront 2.3 A physical parametrisation of fire-spotting for operational fire spread models: Implementation in WRF-Sfire and response analysis with LSFire+
title_fullStr RandomFront 2.3 A physical parametrisation of fire-spotting for operational fire spread models: Implementation in WRF-Sfire and response analysis with LSFire+
title_full_unstemmed RandomFront 2.3 A physical parametrisation of fire-spotting for operational fire spread models: Implementation in WRF-Sfire and response analysis with LSFire+
title_sort RandomFront 2.3 A physical parametrisation of fire-spotting for operational fire spread models: Implementation in WRF-Sfire and response analysis with LSFire+
dc.creator.none.fl_str_mv Trucchia, A.
Egorova, V.
Butenko, A.
Kaur, I.
Pagnini, G.
author Trucchia, A.
author_facet Trucchia, A.
Egorova, V.
Butenko, A.
Kaur, I.
Pagnini, G.
author_role author
author2 Egorova, V.
Butenko, A.
Kaur, I.
Pagnini, G.
author2_role author
author
author
author
dc.subject.none.fl_str_mv Wildfire propagation
Fire spotting
statistical modelling
WRF-Sfire
topic Wildfire propagation
Fire spotting
statistical modelling
WRF-Sfire
description Fire-spotting is often responsible for a dangerous flare up in the wildfire and causes secondary ignitions isolated from the primary fire zone leading to perilous situations. The main aim of the present research to provide a versatile probabilistic model for fire-spotting that is suitable for implementation as a post-processing scheme at each time step in any of the existing operational large-scale wildfire propagation models, without calling for any major changes in the original framework. In particular, a complete physical parametrisation of fire-spotting is presented and the corresponding updated model RandomFront 2.3 is implemented in a coupled fire-atmosphere model : WRF-Sfire. A test case has been simulated and discussed. More- over, the results from different simulations with a simple model based on the Level Set Method, namely LSFire+, highlight the response of the parametrisation to varying fire intensities, wind conditions and different firebrand radii. The contribution of the firebrands towards increasing the fire perimeter varies according to different concurrent conditions and the simulations show results in agreement with the physical processes. Among the many rigorous approaches available in literature to model the firebrand transport and distribution, the approach presented here proves to be simple yet versatile for application to operational large-scale fire spread models.
publishDate 2018
dc.date.none.fl_str_mv 2018
2019
2019
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.11824/907
url http://hdl.handle.net/20.500.11824/907
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv https://www.geosci-model-dev.net/12/69/2019/gmd-12-69-2019-discussion.html
info:eu-repo/grantAgreement/MINECO//SEV-2017-0718
info:eu-repo/grantAgreement/MINECO//SEV-2013-0323
info:eu-repo/grantAgreement/MINECO//MTM2016-76016-R
info:eu-repo/grantAgreement/MINECO//MTM2013-40824-P
info:eu-repo/grantAgreement/Gobierno Vasco/BERC/BERC.2018-2021
info:eu-repo/grantAgreement/Gobierno Vasco/BERC/BERC.2014-2017
dc.rights.none.fl_str_mv Reconocimiento-NoComercial-CompartirIgual 3.0 España
http://creativecommons.org/licenses/by-nc-sa/3.0/es/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Reconocimiento-NoComercial-CompartirIgual 3.0 España
http://creativecommons.org/licenses/by-nc-sa/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:BIRD. BCAM's Institutional Repository Data
instname:Basque Center for Applied Mathematics (BCAM)
instname_str Basque Center for Applied Mathematics (BCAM)
reponame_str BIRD. BCAM's Institutional Repository Data
collection BIRD. BCAM's Institutional Repository Data
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