Characterization of the climatology in the Mediterranean Sea

The main aim of this research thesis is to find and study new methodologies in order to derive an enhanced knowledge of meteorological conditions and in particular of the sea wave climatology. This applies at first locally and then to the whole extension of the Mediterranean basin. Thanks to the large amount of information stored in databases with high temporal and spatial resolution of time series of wind and wave characteristics, it is possible to improve the knowledge of marine climate. In this way, it is possible to make more accurate assessments that may concern, for example, the planning of offshore operations to be carried out safely, a study of the dispersion of pollutants in case of accident to perform rapid and targeted interventions, an accurate design of "ad hoc" structures to protect coastlines or port areas, proper functioning of measuring instruments or energy production to avoid encountering intense storm events during navigation that can create dangerous situations. Using the hindcast of MeteOcean group at DICCA (Univeristy of Genoa), four main topics have been explored. First, the study of the main tool that allows the definition of wave conditions, namely the energy wave spectrum, is addressed, including the development of the procedure of the reconstruction of the bi-dimensional spectrum, defined in the frequency-direction space. Based on the spectral data, in the second chapter a climatological analysis of the Mediterranean Sea is addressed with the aim of identifying and characterizing the major systems in the spectrum. The study of the climatology of the sea continues by exploring another point of view. In the third chapter, the aim is to select significant climatological scenarios of sea states to effectively summarise the local marine climate, introducing clustering algorithms. Using the capabilities of clustering, the fourth chapter of this research thesis concerns climatology from a spatial point of view. The aim is to divide the Mediterranean basin into climatological areas through the help of k-Means.