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Projection of fire potential to future climate scenarios in the Alpine area: some methodological considerations
Authors:D Cane  C Wastl  S Barbarino  L A Renier  C Schunk  A Menzel
Institution:1. Regional Agency for Environmental Protection - Arpa Piemonte, Torino, Italy
2. Chair of Ecoclimatology, Technische Universit?t München, Freising, Germany
Abstract:In Europe, wildfires are an issue not only for the Mediterranean area, but also in the Alpine regions in terms of increasing number of events and severity. In this study we evaluate the impact of climate change on the fire potential in the Alps in the past and in future scenarios. The Fine Fuel Moisture Code (FFMC) of the Canadian Forest Fire Danger Rating System, which successfully distinguishes among recorded fire/no fire events, is applied to projections of Regional Climate Models (RCMs) calculated on the SRES scenario A1B. We compare two different techniques: 1) a single model run of the COSMO-CLM RCM at 18 km resolution, and 2) a combination of 25-km resolution RCMs from the ENSEMBLES project, combined with the Multimodel SuperEnsemble technique and a new probabilistic Multimodel SuperEnsemble Dressing. The single-model RCM allows for a greater coherence among the input parameters, while the Multimodel techniques permit to reduce the model biases and to downscale to a higher resolution where long term records of observations are available. The projected changes with the Multimodel in the scenario give an estimation of increasing wildfire potential in the mid XXI century. In particular the frequency of severe wildfire potential days is shown to increase dramatically. The single (independent) COSMO model gives a weaker signal and in some regions of the study area the predicted changes are opposite to the ones by the Multimodel. This is mainly due to increasing precipitation amounts simulated especially in the northern parts of the Alps. However, there are also some individual models included in the Multimodel ensemble that show a similar signal. This confirms the ambiguity of any impact study based on a single climate model due to the uncertainty of the projections of the climate models.
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