• English 
  • Spanish 

Assessing the predictability of fire occurrence and area burned across phytoclimatic regions in Spain

Journal: Natural Hazards and Earth System Sciences
Year: 2014   Volume: 14
Initial page: 53   Last page: 66
Status: Published
In this status since: 7 Jan 2014
Link to PDF: http://www.nat-hazards-earth-syst-sci.net/14/53/2014/nhess-14-53-2014.pdf
DOI: 10.5194/nhess-14-53-2014

We address the predictability of daily fire occurrence using the components of the Canadian Fire Weather Index System (FWI) calculated from the ERA-Interim reanalysis. We develop daily fire occurrence models in peninsular Spain for the period 1990-2008 considering different minimum burned area thresholds for fire definition, and assess their ability to reproduce the inter-annual fire frequency variability. We then extend the analysis in order to assess the predictability of monthly burned areas. The sensitivity of the models to the level of spatial aggregation of the data is also evaluated. Additionally, we investigate the gain in model performance with the inclusion of socio-economic and land use/land cover (LULC) covariates in model formulation.

Fire occurrence models attained good performance in most of the phytoclimatic zones considered, being able to faithfully reproduce the inter-annual variability of fire frequency. Total area burned also exhibited some dependence on the meteorological drivers, although model performance was poor
in most cases. We identified temperature and some FWI system components as the most important explanatory variables, highlighting the adequacy of the FWI system for fire occurrence prediction in the study area. The results were improved when using aggregated data across regions than when data were sampled at the grid-box level. The inclusion of socioeconomic and LULC covariates contributed marginally to the improvement of the models, an in most cases attained no relevant contribution to total explained variance. Models of monthly fire counts performed better in the case of fires larger than 0.1 ha., but for the rest of thresholds (1, 10 and 100 ha) the daily occurrence models improved the predicted inter-annual variability, indicating the added value of daily models.

Fire frequency predictions may provide a preferable basis for past fire history reconstruction, long-term monitoring and the assessment of future climate impacts on fire regimes across regions, posing several advantages over burned area as response variable. Our results leave the door opened to the development a more complex modelling framework based on daily data from numerical climate model outputs based on the FWI system.