Modelling the daily probability of lightning-caused ignition in the Iberian Peninsula
Rodrigues, Marcos (Universidad de Zaragoza) ; Jiménez-Ruano, Adrián ; Gelabert, Pere Joan ; de Dios, Víctor Resco ; Torres, Luis ; Ribalaygua, Jaime ; Vega-García, Cristina
Resumen: Background. Lightning is the most common origin of natural fires, being strongly linked to specific synoptic conditions associated with atmospheric instability, such as dry thunderstorms; dry
fuels are required for ignition to take place and for subsequent propagation. Aims. The aim was to predict the daily probability of ignition by exploiting a large dataset of lightning and fire data to anticipate ignition over the entire Iberian Peninsula. Methods. We trained and tested a machine learning model using lightning strikes (>17 million) in the period 2009–2015. For each lightning
strike, we extracted information relating to fuel condition, structural features of vegetation, topography, and the specific characteristics of the strikes (polarity, intensity and flash density).
Key results. Naturally triggered ignitions are typically initiated at higher elevations (above 1000 m above sea level) under conditions of low dead fuel moisture (<10–13%) and moderate live moisture
content (Drought Code > 300). Negative-polarity lightning strikes (−10 kA) appear to trigger fires more frequently. Conclusions and implications. Our approach was able to provide ignition forecasts at multiple temporal and spatial scales, thus enhancing forest fire risk assessment systems.
Idioma: Inglés
DOI: 10.1071/WF22123
Año: 2023
Publicado en: International Journal of Wildland Fire (2023), 22123 [12 pp.]
ISSN: 1049-8001
Factor impacto JCR: 2.9 (2023)
Categ. JCR: FORESTRY rank: 14 / 89 = 0.157 (2023) - Q1 - T1
Factor impacto CITESCORE: 5.5 - Forestry (Q1) - Ecology (Q1)
Factor impacto SCIMAGO: 0.819 - Forestry (Q1) - Ecology (Q1)
Financiación: info:eu-repo/grantAgreement/EC/H2020/101003890/EU/FIREURISK - DEVELOPING A HOLISTIC, RISK-WISE STRATEGY FOR EUROPEAN WILDFIRE MANAGEMENT/FirEUrisk
Financiación: info:eu-repo/grantAgreement/ES/MICINN/PID2020-116556RA-I00
Tipo y forma: Article (Published version)
Área (Departamento): Área Análisis Geográfico Regi. (Dpto. Geograf. Ordenac.Territ.)
You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. You may not use the material for commercial purposes. If you remix, transform, or build upon the material, you may not distribute the modified material.
Exportado de SIDERAL (2024-11-22-12:00:42)
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fuels are required for ignition to take place and for subsequent propagation. Aims. The aim was to predict the daily probability of ignition by exploiting a large dataset of lightning and fire data to anticipate ignition over the entire Iberian Peninsula. Methods. We trained and tested a machine learning model using lightning strikes (>17 million) in the period 2009–2015. For each lightning
strike, we extracted information relating to fuel condition, structural features of vegetation, topography, and the specific characteristics of the strikes (polarity, intensity and flash density).
Key results. Naturally triggered ignitions are typically initiated at higher elevations (above 1000 m above sea level) under conditions of low dead fuel moisture (<10–13%) and moderate live moisture
content (Drought Code > 300). Negative-polarity lightning strikes (−10 kA) appear to trigger fires more frequently. Conclusions and implications. Our approach was able to provide ignition forecasts at multiple temporal and spatial scales, thus enhancing forest fire risk assessment systems.
Idioma: Inglés
DOI: 10.1071/WF22123
Año: 2023
Publicado en: International Journal of Wildland Fire (2023), 22123 [12 pp.]
ISSN: 1049-8001
Factor impacto JCR: 2.9 (2023)
Categ. JCR: FORESTRY rank: 14 / 89 = 0.157 (2023) - Q1 - T1
Factor impacto CITESCORE: 5.5 - Forestry (Q1) - Ecology (Q1)
Factor impacto SCIMAGO: 0.819 - Forestry (Q1) - Ecology (Q1)
Financiación: info:eu-repo/grantAgreement/EC/H2020/101003890/EU/FIREURISK - DEVELOPING A HOLISTIC, RISK-WISE STRATEGY FOR EUROPEAN WILDFIRE MANAGEMENT/FirEUrisk
Financiación: info:eu-repo/grantAgreement/ES/MICINN/PID2020-116556RA-I00
Tipo y forma: Article (Published version)
Área (Departamento): Área Análisis Geográfico Regi. (Dpto. Geograf. Ordenac.Territ.)
You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. You may not use the material for commercial purposes. If you remix, transform, or build upon the material, you may not distribute the modified material. Exportado de SIDERAL (2024-11-22-12:00:42)
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Record created 2023-03-23, last modified 2024-11-25