Storm clustering and classification for the port of Rethymno in Greece

Abstract

Storm events are one of the most destructive natural hazards which affect low lying coastal areas and they are responsible for urban coastal flooding and damages in ports and coastal structures. Storm analysis and classification is fundamental for understanding these extreme and violent coastal processes especially nowadays when the frequency and the severity of coastal storms are increased due to climate change and climate variability. In this work an extended analysis of storm events in Rethymno, city of Crete Island, is attempted, for wave climate projections of 1960 to 2100, under the frames of PEARL (Preparing for Extreme And Rare events in coastaL regions), an undergoing EU funded project. Based on the methodology of Dolan-Davis and Saffir-Simpson for storm and hurricane classification, the aim of this work is firstly to present an integrated analysis of storm events and their thresholds thus enhancing the storm definition for this location and secondly to classify them by means of clustering methods. A storm is usually considered as a violent hydro-meteorological phenomenon which can cause damage to the surrounding coastal zone; it starts when the significant wave height exceeds a given minimum threshold and it remains above this for a certain duration. However, the thresholds for the wave height, the duration and the calm phase between two successive storms vary depending on the area of interest. Investigating extreme historical storm events and their future projections, the thresholds’ selection is examined, checking also the independence between of two successive events. Consequently, the definition of a storm is created for this region and the storm events are classified into five classes, depending on their severity. The classification is accomplished with cluster analysis based on the storm energy and the storm period. The different clustering algorithms and methods (hierarchical, k-means, partitioning around medoids and fuzzy clustering) are validated via appropriate indices and the results are presented, checked after all the wave propagation and the variation of significant wave height close to the port structures.