Spatial and temporal patterns of large fire (>100 ha) incidence in Portugal over the period 1984–2004 were modeled using extreme value statistics, namely the Peaks Over Threshold approach, which uses the Generalized Pareto Distribution (GPD) as a model. The original dataset includes all fires larger than 5 ha (30 616 fires) that were observed in Portugal during the study period, mapped from Landsat satellite imagery. The country was divided into eight regions, considered internally homogeneous from the perspective of their fire regimes and respective environmental correlates. The temporal analysis showed that there does not appear to be any trend in the incidence of very large fires, but revealed a cyclical behavior in the values of the GPD shape parameter, with a period in the range of 3 to 5 years. Spatial analysis highlighted strong regional differences in the incidence of large fires, and allowed the calculation of return levels for a range of fire sizes. This analysis was affected by the presence of a few outlying observations, which may correspond to clusters of contiguous fire scars, resulting in artificially large burned areas. We discuss some of the implications of our findings in terms of consequences for fire management aimed at preventing the occurrence of extremely large fires, and present ideas for extending the present study.

Here we present a procedure that allows the operational generation of daily maps of fire danger over Mediterranean Europe. These are based on integrated use of vegetation cover maps, weather data and fire activity as detected by remote sensing from space. The study covers the period of July–August 2007 to 2009. It is demonstrated that statistical models based on two-parameter generalised Pareto (GP) distributions adequately fit the observed samples of fire duration and that these models are significantly improved when the Fire Weather Index (FWI), which rates fire danger, is integrated as a covariate of scale parameters of GP distributions. Probabilities of fire duration exceeding specified thresholds are then used to calibrate FWI leading to the definition of five classes of fire danger. Fire duration is estimated on the basis of 15-min data provided by Meteosat Second Generation (MSG) satellites and corresponds to the total number of hours in which fire activity is detected in a single MSG pixel during one day. Considering all observed fire events with duration above 1 h, the relative number of events steeply increases with classes of increasing fire danger and no fire activity was recorded in the class of low danger. Defined classes of fire danger provide useful information for wildfire management and are based on the Fire Risk Mapping product that is being disseminated on a daily basis by the EUMETSAT Satellite Application Facility on Land Surface Analysis.

We present a procedure that allows the operational generation of daily forecasts of fire danger over Mediterranean Europe. The procedure combines historical information about radiative energy released by fire events with daily meteorological forecasts, as provided by the Satellite Application Facility for Land Surface Analysis (LSA SAF) and the European Centre for Medium-Range Weather Forecasts (ECMWF). Fire danger is estimated based on daily probabilities of exceedance of daily energy released by fires occurring at the pixel level. Daily probability considers meteorological factors by means of the Canadian Fire Weather Index (FWI) and is estimated using a daily model based on a generalized Pareto distribution. Five classes of fire danger are then associated with daily probability estimated by the daily model. The model is calibrated using 13 years of data (2004–2016) and validated against the period of January–September 2017. Results obtained show that about 72 % of events releasing daily energy above 10 000 GJ belong to the “extreme” class of fire danger, a considerably high fraction that is more than 1.5 times the values obtained when using the currently operational Fire Danger Forecast module of the European Forest Fire Information System (EFFIS) or the Fire Risk Map (FRM) product disseminated by the LSA SAF. Besides assisting in wildfire management, the procedure is expected to help in decision making on prescribed burning within the framework of agricultural and forest management practices.