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dc.contributor.authorTrucchia, Andrea
dc.contributor.authorEgorova, Vera 
dc.contributor.authorButenko, Anton
dc.contributor.authorKaur, Inderpreet
dc.contributor.authorPagnini, Gianni
dc.date.accessioned2020-02-03T16:53:02Z
dc.date.available2020-02-03T16:53:02Z
dc.date.issued2019-01-03
dc.identifier.issn1991-959X
dc.identifier.issn1991-9603
dc.identifier.otherMTM2013-40824-Pes_ES
dc.identifier.otherMTM2016-76016-Res_ES
dc.identifier.urihttp://hdl.handle.net/10902/18057
dc.description.abstractFire spotting is often responsible for dangerous flare-ups in wildfires and causes secondary ignitions isolated from the primary fire zone, which lead to perilous situations. The main aim of the present research is 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 parameterisation 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 is simulated and discussed. Moreover, the results from different simulations with a simple model based on the level set method, namely LSFire+, highlight the response of the parameterisation to varying fire intensities, wind conditions and different firebrand radii. The contribution of the firebrands to 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 the literature to model firebrand transport and distribution, the approach presented here proves to be simple yet versatile for application to operational large-scale fire spread models.es_ES
dc.description.sponsorshipThis research was supported by the Basque Government through the BERC 2014–2017 and BERC 2018–2021 programs. It was also funded by the Spanish Ministry of Economy and Competitiveness MINECO via the BCAM Severo Ochoa SEV-2013-0323 and SEV-2017-0718 accreditations, the MTM2013-40824-P “ASGAL” and MTM2016-76016-R “MIP” projects, and the PhD grant “La Caixa 2014”.es_ES
dc.format.extent19 p.es_ES
dc.language.isoenges_ES
dc.publisherCopernicus Publ. para European Geosciences Uniones_ES
dc.rightsAttribution 4.0 Internationales_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.sourceGeoscientific Model Development, 2019, 12, 69-87es_ES
dc.titleRandomFront 2.3: a physical parameterisation of fire spotting for operational fire spread models-implementation in WRF-SFIRE and response analysis with LSFire+es_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.5194/gmd-12-69-2019
dc.type.versionpublishedVersiones_ES


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Attribution 4.0 InternationalExcepto si se señala otra cosa, la licencia del ítem se describe como Attribution 4.0 International