Forest fire danger projections in the Mediterranean using ENSEMBLES regional climate change scenarios
Proxy (statistics)
DOI:
10.1007/s10584-013-1005-z
Publication Date:
2013-11-22T13:21:05Z
AUTHORS (5)
ABSTRACT
The research leading to these results has received funding from the EXTREMBLES project (CGL2010-21869) funded by the Spanish R&D programme and from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement 243888 (FUME Project). The authors acknowledge the RCM data sets from the EU-FP6 project ENSEMBLES (http://ensemblesrt3.dmi.dk) and would also like to thank Erik van Meijgaard from the Royal Netherlands Meteorological Institute (KNMI) for making available ENSEMBLES RACMO2 climate model output verifying at 12:00 UTC. We are also grateful to Jesus Fernandez and three anonymous reviewers for their insightful comments that greatly contributed to the improvement of the original manuscript.<br/>We present future fire danger scenarios for the countries bordering the Mediterranean areas of Europe and north Africa building on a multi-model ensemble of state-of-the-art regional climate projections from the EU-funded project ENSEMBLES. Fire danger is estimated using the Canadian Forest Fire Weather Index (FWI) System and a related set of indices. To overcome some of the limitations of ENSEMBLES data for their application on the FWI System?recently highlighted in a previous study by Herrera et al. (Clim Chang 118:827?840, 2013)?we used an optimal proxy variable combination. A robust assessment of future fire danger projections is undertaken by disentangling the climate change signal from the uncertainty derived from the multi-model ensemble, unveiling a positive signal of fire danger potential over large areas of the Mediterranean. The increase in the fire danger signal is accentuated towards the latest part of the transient period, thus pointing to an elevated fire potential in the region with time. The fire-climate links under present and future conditions are further discussed building upon observed climate data and burned area records along a representative climatic gradient within the study region.<br/>
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