Extreme value statistics of wind speed data by the ACER method

A novel method for estimating the extreme value statistics associated with a recorded time series of data is discussed in this paper. In particular, the focus is on recorded wind speed data at some chosen measurement stations along the Norwegian coast. The method, briefly referred to as the ACER method, is presented in some detail. It is pointed out that the ACER method, if properly implemented, will provide a statistical representation with error bounds of the exact extreme value distribution given by the data. It is also applicable to nonstationary time series. The estimated return level values obtained by the ACER method are compared to the corresponding values obtained by the annual maxima method and the peaks-over-threshold method. Based on the overall performance, it is concluded that the ACER method may indeed be the preferred choice over the other two methods tested.

► The method, briefly referred to as the ACER method, is presented in detail.
► The ACER method estimates the exact extreme value distribution given by the data.
► The ACER method gives consistent and accurate results compared to existing methods.
► The ACER method appears to be robust with respect to the choice of parameter values.
► Advantage of the ACER method is the lack of sensitivity to outliers.