Statistics of bivariate extreme wind speeds by the ACER method

Abstract

The paper focuses on the extension of the average conditional exceedance rate (ACER) method for estimation of extreme wind speed statistics to the case of bivariate wind speed time series. Using the ACER method, it is often possible to provide an estimate of the exact extreme value distribution of a univariate time series. This is obtained by introducing a cascade of conditioning approximations to the exact extreme value distribution. The cascade is expressed in terms of the ACER functions, which can be estimated from the given data time series. When the cascade has converged, an empirical estimate of the extreme value distribution has been obtained. In the paper it is shown how the univariate ACER method can be extended in a natural way to also cover the case of bivariate data. Application of the bivariate ACER method will be demonstrated for simultaneous wind speed measurements from two separate locations.