The study of weather extremes is critical because of their great impact on the environment, economy and society. The identification of areas at greater risk of extreme conditions, and of meteorological situations that give rise to such conditions, enhances the understanding of climate risks and helps establish measures to reduce adverse impacts. In the current paper, precipitation extreme events (PEEs) in Spain between 1960 and 2011 were analysed. Thresholds for determining event severity were defined using 99th percentiles. First, regions of extreme weather risk were identified and then trends of extreme precipitation index were analysed using the Mann–Kendall test. To better understand atmospheric processes associated with extreme weather events in each season, synoptic‐scale fields of events exceeding the 99th percentile were analysed. By applying non‐hierarchical K‐means clustering, we defined six large‐scale atmospheric patterns that largely explain the spatiotemporal distribution of PEEs in the study area. PEEs on the western Iberian Peninsula mainly occurred with zonal flow, with a long Atlantic fetch generating moisture advection towards that area. On the eastern peninsula, the most important pattern for PEE production is characterized by a cutoff low at mid‐levels together with easterly moisture flow. The relationship of PEEs with teleconnection patterns, such as the North Atlantic Oscillation (NAO), Mediterranean Oscillation (MO) and Western Mediterranean Oscillation (WeMO), showed that nearly all the events over the southwestern peninsula were during the NAO‐ and MO‐negative phases. However, on the Mediterranean coast, the negative WeMO phase had greater influence. By contrast, the northwestern peninsula and eastern Cantabrian coast showed weaker relationships between these indices and PEEs. The results show a clear ability to identify regions exposed to extreme precipitation hazards. The correct identification of synoptic patterns associated with each type of weather extreme will assist the prediction of such events, thereby providing useful information for decision making and warning systems.

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Abstract. The Iberian Peninsula presents the highest number of wildfires in Europe. In the NW of Spain in particular, wildfires are the natural risk with the greatest economic impact in this region. Wildfires caused by lightning are closely related to the triggering of convective phenomena. The prediction of thunderstorms is a very complex task because these weather events have a local character and are highly dependent on mesoscale atmospheric conditions. The development of convective storms is directly linked to the existence of a synoptic environment favoring convection. The aim of this study is to classify the atmospheric patterns that provide favorable environments for the occurrence of wildfires caused by lightning in the region of Castile and Leon, Spain. The database used for the study contains 376 wildfire days from the period 1987-2006. NCEP data reanalysis has been used. The atmospheric fields used to characterise each day were: geopotential heights and temperatures at 500 hPa and 850 hPa, relative humidity and the horizontal wind at 850 hPa. A Principal Component Analysis in T-mode followed by a Cluster Analysis resulted in a classification of wildfire days into five clusters. The characteristics of these clusters were analysed and described, focusing particularly on the study of those wildfire days in which more than one wildfire was detected. In these cases the main feature observed was the intensification of the disturbance typical of the cluster to which the wildfire belongs.