Improved near surface wind speed predictions using Gaussian process regression combined with numerical weather predictions and observed meteorological data

This study presents a hybrid numerical weather prediction model (NWP) and a Gaussian process regression (GPR) model for near surface wind speed prediction up to 72 h ahead using data partitioned on atmospheric stability class to improve model performance. NWP wind speed data from the UK meteorological office was corrected using a GPR model, where the data was subdivided using the atmospheric stability class calculated using the...