Medium and long-term forecasts for assessing the danger of fires.
Authors: Santarsiero Valentina 
Published: March 2020

&lt;p&gt;&lt;strong&gt;Medium and long-term forecasts for assessing the danger of fires.&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;V.Santarsiero&lt;sup&gt;1,2&lt;/sup&gt;, A. Lanorte&lt;sup&gt;1&lt;/sup&gt;, G. Nol&amp;#232;&lt;sup&gt;1&lt;/sup&gt;, B. Murgante&lt;sup&gt;2&lt;/sup&gt;, B. Tucci&lt;sup&gt;1&lt;/sup&gt; e P. Baldantoni&lt;sup&gt;2&lt;/sup&gt;&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&amp;#160;&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&amp;#160;&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;Seasonal fire forecasts are a challenge made possible in recent years thanks to availability of better time series of climatic data and wider statistical databases on fires. In addition, the long-term fire risk estimate is considered an element crucial for the preparation of prevention activities (Mavsar et al., 2013). Many of the studies related to seasonal fire forecasts follow an approach empirical based on statistical correlations between fires and climatic variables antecedents. All relevant changes in local and / or weather conditions changes in the local socio-environmental context can influence the regimes of the climate-related fires. Recent advances in seasonal climate forecasting systems based on the analysis of ocean-atmosphere-earth processes make it possible to use prediction models for fire hazard prediction. Such models based on physical processes use models global climate together with human factors to predict the fire hazard on a scale monthly or seasonal (Roads et al. 2005, 2010; Spessa et al. 2015; Field et al. 2015). Seasonal fire hazard predictions in the USA (Roads et al., 2010) are recorded on the NCEP-CFS (National Center for Environmental Prediction's Coupled Forecasting System) (Saha et al., 2006, 2014). The NCEP-CFS system generates forecasts for ensembles of global and regional spectral models over a period of 3 to 7 months. &lt;br&gt;The forecasts generated by the NCEP-CFS system were used to derive precipitation and temperature anomaly maps. Forecasts are made starting from the initial conditions of the last 30 days, with four runs per day. The Forecast ensembles are made up of 40 members from an initial period of 10 days. To provide high resolution seasonal forecasts has been developed and a generalized empirical statistical downscaling system is applied. On this basis precipitation and temperature anomaly maps were extrapolated. The values &amp;#8203;&amp;#8203;of the precipitation and temperature anomalies in the various decades have been integrated in order to develop a meteorological index capable of highlighting the areas where these anomalies affect the increase or decrease in the fire hazard in relation to the average conditions for each specific decade. The index is built in a way such as to attribute a greater weight to the precipitation anomalies (70%) than the temperature anomalies (30%).&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;Keywords: fire hazard prediction, long-term forecasting.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&lt;sup&gt;1&lt;/sup&gt; IMAA-CNR C.da Santa Loja, zona Industriale, Tito Scalo, Potenza 85050, Italy;&lt;/p&gt;&lt;p&gt;&lt;sup&gt;2&lt;/sup&gt;School of Engineering, University of Basilicata, Viale dell'Ateneo Lucano 10, Potenza 85100, Italy.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;