Skilful forecasting of global fire activity using seasonal climate predictions

Societal exposure to large fires has been increasing in recent years. Estimating the expected fire activity a few months in advance would allow reducing environmental and socio-economic impacts through short-term adaptation and response to climate variability and change. However, seasonal prediction...

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Detalles Bibliográficos
Autores: Turco, Marco, Jerez, Sonia, Doblas-Reyes, Francisco|||0000-0002-6622-4280, AghaKouchak, Amir, Llasat, Maria Carmen, Provenzale, Antonello
Tipo de recurso: artículo
Fecha de publicación:2018
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/119384
Acceso en línea:https://hdl.handle.net/2117/119384
https://dx.doi.org/10.1038/s41467-018-05250-0
Access Level:acceso abierto
Palabra clave:Climate science
Seasonal prediction (Meteorology)
Season prediction
Skilful predictions of fire
Previsió del temps
Clima--Observacions
Àrees temàtiques de la UPC::Energies
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spelling Skilful forecasting of global fire activity using seasonal climate predictionsTurco, MarcoJerez, SoniaDoblas-Reyes, Francisco|||0000-0002-6622-4280AghaKouchak, AmirLlasat, Maria CarmenProvenzale, AntonelloClimate scienceSeasonal prediction (Meteorology)Season predictionSkilful predictions of firePrevisió del tempsClima--ObservacionsÀrees temàtiques de la UPC::EnergiesSocietal exposure to large fires has been increasing in recent years. Estimating the expected fire activity a few months in advance would allow reducing environmental and socio-economic impacts through short-term adaptation and response to climate variability and change. However, seasonal prediction of climate-driven fires is still in its infancy. Here, we discuss a strategy for seasonally forecasting burned area anomalies linking seasonal climate predictions with parsimonious empirical climate–fire models using the standardized precipitation index as the climate predictor for burned area. Assuming near-perfect climate predictions, we obtained skilful predictions of fire activity over a substantial portion of the global burnable area (~60%). Using currently available operational seasonal climate predictions, the skill of fire seasonal forecasts remains high and significant in a large fraction of the burnable area (~40%). These findings reveal an untapped and useful burned area predictive ability using seasonal climate forecasts, which can play a crucial role in fire management strategies and minimise the impact of adverse climate conditions.This work was partially funded by the EU H2020 Project 641762 “ECOPOTENTIAL: Improving Future Ecosystem Benefits through Earth Observations” and the SERVFORFIRE project of the ERA-NET for Climate Services, ERA4CS. M. Turco was supported by the Spanish Juan de la Cierva Programme (IJCI-2015-26953). F.J. Doblas- Reyes was supported by the H2020 IMPREX (GA 641811) and EUCP (GA 776613) projects. A.A. was partially supported by the National Oceanic and Atmospheric Administration (NOAA) award NA14OAR4310222, National Aeronautics and Space Administration (NASA) award NNX15AC27G, and National Science Foundation (NSF) INFEWS grant EAR 1639318. Special thanks to Esteve Canyameras and Xavier Castro for helpful discussions on the study.Peer ReviewedNature Publishing Group20182018-07-1320182018-07-16journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/119384https://dx.doi.org/10.1038/s41467-018-05250-030006529reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)InglésengEuropean Commission http://doi.org/10.13039/100010661 Horizon 2020 Framework Programme 641762 ECOPOTENTIAL: IMPROVING FUTURE ECOSYSTEM BENEFITS THROUGH EARTH OBSERVATIONSEuropean Commission http://doi.org/10.13039/100010661 Horizon 2020 Framework Programme 641811 IMproving PRedictions and management of hydrological EXtremesEuropean Commission http://doi.org/10.13039/100010661 Horizon 2020 Framework Programme 776613 European Climate Prediction systemMinisterio de Economía y Competitividad http://doi.org/10.13039/501100003329 IJCI-2015-26953 IJCI-2015-26953open accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivs 4.0 Spainhttp://creativecommons.org/licenses/by-nc-nd/4.0/es/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/1193842026-05-27T15:37:01Z
dc.title.none.fl_str_mv Skilful forecasting of global fire activity using seasonal climate predictions
title Skilful forecasting of global fire activity using seasonal climate predictions
spellingShingle Skilful forecasting of global fire activity using seasonal climate predictions
Turco, Marco
Climate science
Seasonal prediction (Meteorology)
Season prediction
Skilful predictions of fire
Previsió del temps
Clima--Observacions
Àrees temàtiques de la UPC::Energies
title_short Skilful forecasting of global fire activity using seasonal climate predictions
title_full Skilful forecasting of global fire activity using seasonal climate predictions
title_fullStr Skilful forecasting of global fire activity using seasonal climate predictions
title_full_unstemmed Skilful forecasting of global fire activity using seasonal climate predictions
title_sort Skilful forecasting of global fire activity using seasonal climate predictions
dc.creator.none.fl_str_mv Turco, Marco
Jerez, Sonia
Doblas-Reyes, Francisco|||0000-0002-6622-4280
AghaKouchak, Amir
Llasat, Maria Carmen
Provenzale, Antonello
author Turco, Marco
author_facet Turco, Marco
Jerez, Sonia
Doblas-Reyes, Francisco|||0000-0002-6622-4280
AghaKouchak, Amir
Llasat, Maria Carmen
Provenzale, Antonello
author_role author
author2 Jerez, Sonia
Doblas-Reyes, Francisco|||0000-0002-6622-4280
AghaKouchak, Amir
Llasat, Maria Carmen
Provenzale, Antonello
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Climate science
Seasonal prediction (Meteorology)
Season prediction
Skilful predictions of fire
Previsió del temps
Clima--Observacions
Àrees temàtiques de la UPC::Energies
topic Climate science
Seasonal prediction (Meteorology)
Season prediction
Skilful predictions of fire
Previsió del temps
Clima--Observacions
Àrees temàtiques de la UPC::Energies
description Societal exposure to large fires has been increasing in recent years. Estimating the expected fire activity a few months in advance would allow reducing environmental and socio-economic impacts through short-term adaptation and response to climate variability and change. However, seasonal prediction of climate-driven fires is still in its infancy. Here, we discuss a strategy for seasonally forecasting burned area anomalies linking seasonal climate predictions with parsimonious empirical climate–fire models using the standardized precipitation index as the climate predictor for burned area. Assuming near-perfect climate predictions, we obtained skilful predictions of fire activity over a substantial portion of the global burnable area (~60%). Using currently available operational seasonal climate predictions, the skill of fire seasonal forecasts remains high and significant in a large fraction of the burnable area (~40%). These findings reveal an untapped and useful burned area predictive ability using seasonal climate forecasts, which can play a crucial role in fire management strategies and minimise the impact of adverse climate conditions.
publishDate 2018
dc.date.none.fl_str_mv 2018
2018-07-13
2018
2018-07-16
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/119384
https://dx.doi.org/10.1038/s41467-018-05250-0
30006529
url https://hdl.handle.net/2117/119384
https://dx.doi.org/10.1038/s41467-018-05250-0
identifier_str_mv 30006529
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv European Commission http://doi.org/10.13039/100010661 Horizon 2020 Framework Programme 641762 ECOPOTENTIAL: IMPROVING FUTURE ECOSYSTEM BENEFITS THROUGH EARTH OBSERVATIONS
European Commission http://doi.org/10.13039/100010661 Horizon 2020 Framework Programme 641811 IMproving PRedictions and management of hydrological EXtremes
European Commission http://doi.org/10.13039/100010661 Horizon 2020 Framework Programme 776613 European Climate Prediction system
Ministerio de Economía y Competitividad http://doi.org/10.13039/501100003329 IJCI-2015-26953 IJCI-2015-26953
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 4.0 Spain
http://creativecommons.org/licenses/by-nc-nd/4.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 4.0 Spain
http://creativecommons.org/licenses/by-nc-nd/4.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Nature Publishing Group
publisher.none.fl_str_mv Nature Publishing Group
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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