A multivariable analysis of the influence of the North Atlantic Oscillation (NAO) on the climate of the North Atlantic and European sectors is presented using the 40 yr consistent data set from NCEP. Using high and low NAO index composites, anomaly fields of climate variables are then interpreted based on physical mechanisms associated with the anomalous mean flow (characterised by the surface wind field) and the anomalous eddy activity (characterised by the surface vorticity and the 500 hPa storm track fields). It is shown that NAO-related temperature patterns are mainly controlled by the advection of heat by the anomalous mean flow. However, large asymmetries between minimum and maximum temperatures, and more significantly, between positive and negative phases of NAO imply the importance of a different mechanism, namely, the modulation of short wave and long wave radiation by cloud cover variations associated with the NAO. Furthermore, NAO influence on 2 different precipitation-related variables -precipitation rate and precipitable water -displays different patterns. Precipitable water is shown to be strongly related to the corresponding anomaly fields of temperature while precipitation rate appears to be controlled by the surface vorticity field and associated strength of the tropospheric synoptic activity. KEY WORDS: NAO · Storm tracks · Surface wind · Maximum and minimum temperatures · Precipitation rate · Precipitable waterResale or republication not permitted without written consent of the publisher

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).

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