Forest fires are a major concern in Europe, particularly in Portugal where large forest fires are responsible for negative environmental, social and economic effects. In this work, a long time series of daily area burned in 18 Portuguese districts (north, coastal areas and inner–south) from 1980 to 2010 are analysed to characterise extreme area burned and regional variability. The analysis combines the peak-over-threshold method and classification techniques to cluster the time series on the basis either of their corresponding tail indices or their predictive distributions for 5- and 15-year return values, that is, the level that is exceeded on average once every 5 or 15 years. As previously reported in other wildfire studies, the results show that the distributions of area burned (1980–2010) are heavy tailed for all Portuguese districts, with considerable density in the tail, indicating a non-negligible probability of occurrence of days with very large area burned. Moreover, clustering based on tail indices identified three distinct groups with spatial pattern closely related to the percentage of shrub cover within each district. Finally, clustering based on return values shows that the largest return levels of area burned are expected to occur in districts located in the centre and south of Portugal.
Extreme value analysis for the sample autocovariance matrices of heavy-tailed multivariate time series
