Author(s)

G Rodríguez

Abstract

Long-term wind climate in a large oceanic island harbour G. Rodriguez Departamento de Fisica, Universidad de Las Palmas de G.C., Las Palmas, Spain. Abstract Knowledge of wind climate is of great importance for the adequate design and construction of harbours and for operational considerations. Statistical properties of wind climate at Las Palmas Port, a large harbour located in an small oceanic island, are studied by using an incomplete data set of maximum daily wind speed covering a period of 10 years. Annual and seasonal variabilities, as well as probability of extreme values occurrence are examined. Additionally, a time-frequency representation of this nonstationary time series is developed. 1 Introduction Wind climate is an essencial input for many engineering practices related to ports and marinas design and functioning. Harbour facilities should be designed to sustain extreme wind forcing during their lifetime. Furthermore, while in general the wind loads on ships constitute a relatively small part of the total environmental load, the accurate knowledge of the magnitude and character of the wind loads plays an important role in connection with harbour and near harbour operations, such as manoeuvring, mooring, stability, and dynamic positioning, among others. The problem of wind loads on berthing structures is more complex because of loads can be exerted directly on the structure and indirectly through the forces on moored ships, which are transmited to the structure along the mooring lines. A detailed description of wind effects on structures can be found in [1], while mathematical models to estimate the wind forces and moments on a vessel have been described in [2]. It is well known that wind is a phenomenon of random nature. Furthermore, wind characteristics in coastal zones are the result of interacting meteorological, oceano- graphic and topographic factors. Consequently, meteorological flows in coastal zones display a very complex stochastic behaviour and their practical study must rely on probabilistic methodologies. Additionally, it is also well known that, in general, wind

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