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Abstract. The characteristics of the cyclone tracks that caused precipitation events of variable intensity for the period 1979-2011 over the island of Crete are presented. The data set used for cyclone identification is the 0.5 • × 0.5 • , 30 years European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim mean sea-level pressure. Cyclone characteristics are calculated with the aid of the Melbourne University algorithm (MS scheme). Daily precipitation data from a dense gauging network over the island of Crete are also used for the classification of the precipitation events in terms of rain accumulation (intensity). Daily precipitation is classified in three categories and the associated cyclones are chosen according to their distance from Crete island. The seasonal and annual cycle of the physical characteristics of the cyclone tracks are investigated with respect to the cyclones' relative position to the island of Crete. It was found that cyclones affecting Crete most frequently approach from the western side of the island and the actual cyclone centers associated with precipitation events are usually located northwest and southeast of the Crete domain. Cycloneinduced rainfall increases in function to cyclones' depth, radius and propagation velocity increase as well as cyclones' pressure decrease. Spring cyclones that affect Crete with rainfall present lower pressures and higher cyclone propagation velocity in contrast to the ones associated with winter and autumn precipitation events. The examination of the relation between cyclone characteristics and precipitation occurrence provides valuable information related to forecasting potential and management of the water resources and the rainfall extremes.

Data from a dense network of 69 daily precipitation gauges over the island of Crete and cyclone climatological analysis over middle-eastern Mediterranean are combined in a statistical approach to develop a rain diagnostic model. Regarding the dataset, 0.5 × 0.5, 33-year (1979–2011) European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA-Interim) is used. The cyclone tracks and their characteristics are identified with the aid of Melbourne University algorithm (MS scheme). The region of interest is divided into a grid mesh and for each grid the probability of rain occurrence from passing cyclones is estimated. Such probability maps are estimated for three rain intensity categories. The probability maps are evaluated for random partitions of the data as well as for selected rain periods. Cyclones passing south of Italy are found to have greater probability of producing light rain events in Crete in contrast to medium and heavy rain events which are mostly triggered by cyclones of southern trajectories. The performance of the probability maps is very satisfactory, recognizing the majority of “affecting” cyclones and rejecting most cyclones that do not trigger rain events. Statistical measures of sensitivity and specificity range between 0.5 and 0.8 resulting in effective forecasting potential.

Over the past few years there has been an increased interest in studying the underlying neural mechanism of cognitive brain activity related to memory. In this direction, we study the brain activity based on its independent components instead of the EEG signal itself aiming towards identifying and analyzing induced responses being attributed to oscillatory bursts from local or distant neural assemblies, with variable latency and frequency, in an auditory working memory paradigm. The contribution and functional coupling of independent components to evoked and/or induced oscillatory activities is investigated through the concept of the recently introduced partial directed coherence method, which can also reveal the direction of the statistically significant relationships. The results on read data from an oddball experiment are in accordance with previous psychophysiology studies suggesting increased phase locked activity most prominently in the delta/ theta band, while alpha is also apparent in measures of non phase-locked activity. Dynamic synchronization is inferred between the alpha and delta bands, whereas some influence of the theta band is also detected. This study indicates that functional connectivity during cognitive processes may be successfully assessed using spectral power measures applied on independent components, which reflect distinct spatial patterns of activity.