For offshore wind energy assessment it is necessary to appropriately model and describe wind climate. In this connection, the Rayleigh and Weibull distributions are widely suggested for offshore wind speed modelling. Although the use of these distributions is theoretically consistent, in practice, they are often proved to be inadequate. In two recently published papers some, less known, multi-parameter distributions (Johnson SB, Kappa and Wakeby) were introduced and proved to describe more accurately the stochastic behaviour of wind speed measurements obtained from buoys located in entirely different sea areas of the world. In order to evaluate their fitting performance with reference to coastal wind speed data, in this paper we assessed long-term time series obtained from ten meteorological land-based stations across the Italian coasts. The obtained results confirmed that the Johnson SB, Kappa and Wakeby distributions are of general validity for any wind data set analysed, since they performed fairly well for the modelling of coastal wind speeds as well. These distributions adapted better than the Weibull and are suggested as reliable and prominent candidates for the modelling of offshore and coastal wind speed in any sea area.