TY  - JOUR
PY  - 2023//
TI  - Modelling the daily probability of lightning-caused ignition in the Iberian Peninsula
JO  - International journal of wildland fire
A1  - Rodrigues, Marcos
A1  - Jiménez-Ruano, Adrián
A1  - Gelabert, Pere Joan
A1  - Dios, Víctor Resco de
A1  - Torres, Luis
A1  - Ribalaygua, Jaime
A1  - Vega-García, Cristina
SP  - 351
EP  - 362
VL  - 32
IS  - 3
N2  - 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.<br><br>METHODS We trained and tested a machine learning model using lightning strikes (>17million) 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 1000m above sea level) under conditions of low dead fuel moisture (<10-13%) and moderate live moisture content (Drought Code>300). Negative-polarity lightning strikes (−10kA) appear to trigger fires more frequently.<br><br>CONCLUSIONS and implications Our approach was able to provide ignition forecasts at multiple temporal and spatial scales, thus enhancing forest fire risk assessment systems.<p />  <p>Language: en</p>
LA  - en
SN  - 1049-8001
UR  - http://dx.doi.org/10.1071/WF22123
ID  - ref1
ER  -