Wind prediction enhancement by exploiting data non-stationarity

The short term forecasting of wind speed and direction has previously been improved by adopting a cyclo-stationary multichannel linear prediction approach which incorporat ed seasonal cycles into the estimation of statistics. This pap er expands previous analysis by also incorporating diurnal va ri- ation and time-dependent window lengths. Based on a large data set from the UK’s Met Office, we demonstrate the impact of this proposed approach