## 1 Introduction
In this study, we dealt with the exponentiated Weibull distribution as an alternative to the widely used wind speed distributions, namely the two-parameter and three-parameter Weibull distributions. An exponentiated probability distribution was created by exponentiation of the classical distribution. Specifically, the cumulative distribution function of a probability distribution was raised to an additional parameter. It was studied in [38] where authors investigated several exponentiated probability distributions in detail. Exponentiated Weibull distribution as a generalization of the Weibull distribution was introduced by [PERSON] a [PERSON] in [39]. Its properties were studied in [40; 41; 42; 43; 44; 45; 46]. This distribution has been commonly used for modelling data in various fields, such as reliability, finance, medicine, and environmental studies [47; 48]. Considering the limitation of the two-parameter and three-parameter Weibull distributions in modelling the wind speed, here, it was investigated whether the exponentiated Weibull distribution is sufficiently flexible and adaptable to accommodate different shapes of the wind speed data. The number of papers dedicated to application of the exponentiated Weibull distribution on fitting the wind speed data is rather limited. [PERSON] and [PERSON] in [49] used the two-parameter Weibull and the exponentiated Weibull distribution, respectively, to model wind speeds in Southwestern Nigeria using long-term observations covering the period of years 1992-2012. Based on the values of the Akaike's information criterion, they demonstrated a much better fit of the exponentiated Weibull distribution as compared to the performance of the Weibull distribution. [PERSON] and [PERSON] in [50] modelled the wind speed in six stations located on the Aegean coast, Turkey. They compared nine different probability distributions, namely the Rayleigh, the inverse Weibull, the Burt Type III, the Extreme value, the Gamma, the inverse Gamma, the Marshall-Olkin extended Lindley, the generalized Extreme value, and the exponentiated Weibull distribution, since these distributions represent suitable alternatives to the Weibull distribution in modelling the wind speed. According to the values of the model evaluation criteria (the root mean square error, the coefficient of determination, the Akaike's information criterion, the Bayesian information criterion, and the Kolmogorov-Smirnov test statistic), the exponentiated Weibull distribution outperformed the rest of the considered distributions. Both of the mentioned papers focused on modelling the wind speed in stations located in the coastal area with low altitudes. To the best of our knowledge, there has not been published a paper focusing on the application of the exponentiated Weibull distribution to model the wind speed in a location with a higher altitude, laying inland. For this purpose, the hourly wind speed data from meteorological station Poprad, located at the Poprad-Tatry airport, Northern Slovakia, was modelled by two-parameter, three-parameter, and exponentiated Weibull distributions, respectively. The city of Poprad is the administrative, economic, and cultural centre of the region under the Tatras. With a population of 49,430 (31.12.2021), it is the second largest city in the Presov region and the tenth largest city in Slovakia. Thanks to its location, it was given the epithet \"The gateway to the High and Low Tatras\", where there are well-known centres for winter sports and summer tourism. The High Tatras are the only high mountains that are located on the territory of Slovakia and Poland and are also included in the UNESCO Biosphere Reserve. The highest peak of the High Tatras as well as of the entire Carpathians is the Gerlach peak (2654.4 m above sea level). The territory of the biosphere reserve includes two national parks, one of which is in Slovakia. The tourism sector in the Tatra Biosphere Reserve provides the main form of employment [51].