In this study, output of the Hadley Centre Regional Circulation Model (RCM) (HadRM3P, 0.44°× 0.44°resolution) was used as input to the Canadian Forest Fire Weather Index (FWI) for the present and 2 future IPCC climate scenarios (Special Report on Emissions Scenarios [SRES], A2 and B2 scenarios). The aim was to investigate the effects of climate change on fire risk (number of days with fire risk, length of fire risk season, etc.) for the EU Mediterranean countries. Results indicated a general increase in fire risk in both future scenarios over the whole study area. The increase in fire risk was mainly due to 3 components: (1) increase in the number of years with fire risk; (2) increase in the length of the season with fire risk; (3) increase of extreme events (e.g. total number of days with FWI > 45 and episodes with FWI > 45 for 7 consecutive days) during the fire season. As expected, A2 scenario showed a greater increase in risk than B2 scenario. These general increases in fire risk may have a very strong impact in areas where forest land cover is high (e.g. the Alps region in Italy, the Pyrenees in Spain and mountains of the Balkan region).

This paper provides an overview of the aims, objectives, research activities undertaken, and a selection of results generated in the European Commission-funded project entitled "Modelling the Impact of Climate Extremes" (MICE) -a pan-European end-to-end assessment, from climate model to impact model, of the potential impacts of climate change on a range of economic sectors important to the region. MICE focussed on changes in temperature, precipitation and wind extremes. The research programme had three main themes -the evaluation of climate model performance, an assessment of the potential future changes in the occurrence of extremes, and an examination of the impacts of changes in extremes on six activity sectors using a blend of quantitative modelling and expert judgement techniques. MICE culminated in a large stakeholder-orientated workshop, the aim of which was not only to disseminate project results but also to develop new stakeholder networks, whose expertise can be drawn on in future projects such as ENSEMBLES. MICE is part of a cluster of three projects, all related to European climate change and its impacts. The other projects in the cluster are PRUDENCE (Prediction of Regional Scenarios and Uncertainties for Defining European Climate Change Risks and Effects) and STARDEX (Statistical and Regional Dynamical Downscaling of Extremes for European Regions).

Most of the recent studies and projections of precipitation patterns, based on records observed in the past and climate change scenarios for the Mediterranean basin, suggest a relatively slow decrease in rainfall amounts over the years but an increase in the frequency of extreme precipitation events. These are key factors in desertification processes and these will cause social and environmental impacts in the short term, mainly because changes in heavy rainfall events may have severe implications and impacts on soil erosion, resulting in increased risk of soil degradation.The main objective of the present work is to evaluate the spatial-temporal dynamics of extreme precipitation events in southern Portugal, using a direct sequential simulation algorithm (DSS models) in order to assess the relationships between spatial and temporal extreme rainfall patterns. Local probability density functions (pdfs) and spatial uncertainty are evaluated by a set of equiprobable simulated images of the chosen extreme precipitation indices.The used dataset in this work comprises a set of 105 station records of observed daily precipitation within the period 1961-2000. Two indices of extreme precipitation were selected: one representing the frequency of extremely heavy precipitation events (R30) and another characterizing the occurrence of dry events (RL10), both obtained from observed daily precipitation series.Results show that the spatial continuity of extreme precipitation events has increased in the last 40 years in southern Portugal. It also demonstrates a decrease in spatial variability, implying that extreme precipitation events tend to be more spatially homogeneous, which may have a severe impact on water resources, agriculture and soil erosion, particularly when associated with desertification risks.

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