The Ofidia Project: a Retrospective Fire Danger Forecast Analysis in Mediterranean Environment
Abstract:OFIDIA (Operational FIre Danger preventIon plAtform) is a two-year project started in May 2013 funded by the European Territorial Cooperation Programme Greece Italy (2007 – 2013). The project aims to improve the operational capability of forecasting, preventing, and fighting forest wildfires, and enhance the cross-border cooperation for fire danger assessment. More specifically, OFIDIA aims at developing an operational fire danger prevention platform, with the ability for near real-time fire danger forecast and fire behaviour analysis in Apulia (Italy) and Epirus (Greece) regions to help forest fires services in the effective prevention and response to forecasted danger.
One of the preliminary activities of the project was the evaluation of fire danger performances by analysing the relationship between the predicted daily fire danger and observed fire activity (number of fires and area burned). To achieve this task, fire activity and danger patterns were characterised and their relationships were investigated for the period 2000-2012. The Italian Forest Service (CFS, Corpo Forestale dello Stato) provided fire statistics at NUT03 level. The data were homogenized and uncertainties corrected, and then burned area and number of fires were analysed according to the main fire regime characteristics (seasonality, fire return interval, fire incidence, fire size distribution, etc). Then, three fire danger models (FFWI, FWI, and IFI) were selected and computed starting from the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) forecast.
Results showed a high inter- and intra-annual variability in fire activiy, also considering the different type of affected vegetation. As for other Mediterranean areas, a smaller number of large fires caused a high proportion of burned area. Furthermore, fire activity showed significant correlations with the outputs obtained by the applied models. High relationships were found between fire danger and fire occurrence, confirming the importance of the prediction to forecast fire occurrence in these areas.