On the projection of future fire danger conditions with various instantaneous/mean-daily data sources

Fire danger indices are descriptors of fire potential in a large area, and combine a few variables that affect the initiation, spread and control of forest fires. The Canadian Fire Weather Index (FWI) is one of the most widely used fire danger indices in the world, and it is built upon instantaneous values of temperature, relative humidity and wind velocity at noon, together with 24 hourly accumulated precipitation. However, the scarcity of appropriate data has motivated the use of daily mean values as surrogates of the instantaneous ones in several studies that aimed to assess the impact of global warming on fire. In this paper we test the sensitivity of FWI values to both instantaneous and daily mean values, analyzing their effect on mean seasonal fire danger (seasonal severity rating, SSR) and extreme fire danger conditions (90 percentile, FWI90, and FWI>30, FOT30), with a special focus on its influence in climate change impact studies. To this aim, we analyzed reanalysis and regional climate model (RCM) simulations, and compared the resulting instantaneous and daily mean versions both in the present climate and in a future scenario. In particular, we are interested in determining the effect of these datasets on the projected changes obtained for the mean and extreme seasonal fire danger conditions in future climate scenarios, as given by a RCM. Overall, our results warn against the use of daily mean data for the computation of present and future fire danger conditions. Daily mean data lead to systematic negative biases of fire danger calculations. Although the mean seasonal fire danger indices might be corrected to compensate for this bias, fire danger extremes (FWI90 and specially FOT30) cannot be reliably transformed to accommodate the S. Herrera Predictia Intelligent Data Solutions S.L. CDTUC Fase A, Planta 2-203. Avda. los Castros s/n 39005 Santander, Spain. E-mail: [email protected] J. Bedia, J.M. Gutiérrez Instituto de F́ısica de Cantabria (IFCA-CSIC) Universidad de Cantabria. 39005 Santander, Spain. J. Fernández Dpto. de Matemática Aplicada y CC de la computaciónUniversidad de Cantabria. 39005 Santander, Spain. J.M. Moreno Dpto. Ciencias Ambientales, Universidad de Castilla La Mancha. Av. Carlos III s/n, 45071 Toledo, Spain