Improving extreme wind speed prediction based on a short data sample, using a highly correlated long data sample

Abstract

This paper focuses on the problem of improving extreme wind speed estimates for locations with only a short time series of measured values available, given the opportunity to use a highly correlated long time series of wind speed data. For this purpose, an efficient transfer of information is necessary between two highly correlated stochastic processes. To illustrate the efficiency of the proposed technique, two sets of two highly correlated time series of wind speed data are used. The first set of data consists of two synthetic wind speed data sets. The second set of data was obtained from two Norwegian wind speed measurement stations. This paper intends to stimulate further research and fill a gap in the current literature on this important topic.