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In this contribution we identify storm time-clustering in the Mediterranean Sea through the analysis of the spatial distribution of the Allan Factor. This parameter is evaluated from long time series of wave height provided by means of oceanographic buoy measurements and hindcast re-analysis spanning in the period 1979–2014 and characterized by a horizontal resolution of about 0.1 degree in longitude and latitude and a temporal sampling of one hour (Mentaschi et a., 2015). Results reveal clustering mainly for two distinct ranges of time scales. The first range of time scales (12 hrs to 50 days) is associated to sequences of storms generated by the persistence of the same meteorological system. The second range, associated to timescales beteween 50 and 100 days, reveals seasonal fluctuations. Transitional regimes are present at some locations in the basin. The spatial distribution of the Allan Factor reveals that the clustering at smaller time scales is present in the North-West of the Mediterranean, while clustering at larger scales is observed in the whole basin. This analysis is believed to be important to assess the local increased flood and coastal erosion risks due to storm clustering.

Wind-generated ocean waves are key inputs for several studies and applications, both near the coast (coastal vulnerability assessment, coastal structures design, harbor operativity) and off-shore (a.o. oil and gas production, ship routes, and navigation safety). As such, the evaluation of trends in future wave climate is fundamental for the development of efficient policies in the framework of climate change adaptation and mitigation measures. This study focuses on the Mediterranean Sea, an area of primary interest, since it plays a crucial role in the worldwide maritime transport and it is highly populated along all its coasts. We perform an analysis of wave climate changes using an ensemble of 7 models under emission scenario RCP8.5, over the entire Mediterranean basin. Future projections of wave climate and their variability are analyzed taking into account annual statistics of wave parameters, such as significant wave height, mean period, and mean direction. The results show, on average, a decreasing trend of significant wave height and mean period, while the wave directions may be characterized by a slight eastward shift.

For this study, we analyzed the performance of the wave model Wavewatch III ® forced by a limited area atmospheric model in the Mediterranean Sea. The simulation results have been compared to buoy measurements through single point statistical indicators such as normalized bias and symmetrically normalized root mean square error. A performance evaluation of the growth-dissipation source terms and their reference parameterizations was carried out on seventeen case studies corresponding to storms in the Northern Tyrrhenian Sea and off the Mediterranean Spanish coast. The source terms introduced by Ardhuin et al. (2010) proved to be the best overall choice, although they led to an overestimation in the significant wave height under calm conditions and to an underestimation under severe conditions. A sensitivity analysis in the parameter space was performed within the neighborhood of the reference parameterization of Ardhuin et al. (2010), and a calibration was carried out to reduce the overall positive bias in the significant wave height. Furthermore, to investigate the effect from the wind forcing resolution, wind data with different resolutions was used in a sensitivity analysis. Because mesoscale features are relevant to the overall Mediterranean wave dynamics, we carried out a further investigation into the impact of the resolution on a different set of ten case studies characterized by strong mesoscale patterns. A comparison of the simulations with the measurements using single point statistical indicators shows that the high resolution results are affected by the so-called double penalty effect, although in some cases, they apparently provide a better qualitative description of the event. Finally, a hindcast covering 32 years (from 1979 to 2010) was developed using a reference parameterization from Ardhuin et al. (2010) and its calibrated variant. An analysis of the performance of the calibrated parameterization on the hindcast dataset reveals that it performs better than the reference parameterization over a wide range of wave heights, in seas that range from calm to moderate, whereas it increases the tendency to underestimate the significant wave height under severe conditions.

In this work a study of the performances of the WAVEWATCH III (WWIII) model in the Mediterranean basin is presented. Analysis is carried out referring to seventeen case studies corresponding to heavy storms in northern Tyrrhenian basin (Ligurian sea) in the last twenty five years. Simulation results are validated using buoy data provided by the Rete Ondametrica Nazionale (RON). An analysis of the usage and performances of different statistical error indicators is provided, showing that widespread NRMSE indicator is biased towards models that underestimate prediction. The well established source terms parameterization by Tolman and Chalikov (1996) has been compared with the one proposed by Ardhuin et al.( 2010), set up with the parameterization by Bidlot et al., (2005), and with the set known as ACC350. The obtained results reveal that the ACC350 parameterization works better in severe conditions, though tends to overestimate wave height and underestimate period. A further sensitivity analysis in the parameters space is carried out around ACC350 parameterization, finding that variations in the default set of parameters, involving small wave growth reduction or an increase of energy dissipation, lead to a slight improvement of the overall simulation performances. © Coastal Education & Research Foundation 2013.

By utilizing various statistical models to quantify the return levels of extreme significant wave height this study seeks to achieve two objectives: the updating of the state-of-the-art concerning extreme wave analysis along the Italian coast and the creation of a long-term predictive model. To these ends, four different methods widely used in the field of metocean engineering are employed to analyze both buoy data (Rete Ondametrica Nazionale, RON) and wave data obtained by means of dynamical hindcasting techniques such as the forecast/hindcast operational model chain in use at the University of Genoa ( www.dicca.unige.it/meteocean ). Return levels are estimated by the Goda method, the Generalized Extreme Value (GEV) and the Generalized Pareto Distribution–Poisson point process models and the Equivalent Triangular Storm (ETS) algorithm. All models follow the Peak-Over-Threshold (POT) approach which require an optimal threshold implementation, save for the GEV analysis, which is applied to model significant wave height maxima pertaining to time-blocks. The models exhibit different performance characteristics, presented here and treated in depth. In general, noteworthy versatility characterizes the GPD–Poisson model, which often recovers Goda results, while the GEV and ETS models exhibit limitations in assessment of a variety of wave fields, greatly diversified in a semi-closed basin such as the Mediterranean Sea. Long-term estimates have been provided by means of the most appropriate model selected, thus offering a complete overview of wave climate in the Mediterranean basin based on wave hindcast data.