Abstract
Wind-speed forecasts for a wind-farm in southwest Ireland were made for over one year using the operational HARMONIE mesoscale weather forecast model, and Bayes Model Averaging (BMA) for statistical post-processing to remove systematic local bias. The deterministic forecasts alone generated mean absolute errors of 1.7-2.0 ms(-1) out to 24hrs, when interpolated to the location of the met-mast. Application of BMA reduced these errors by about 15%, to 1.5-1.6 ms(-1), on average. Forecast errors do not degrade significantly as forecast lead-time increases, at least out to 24 hours. (C) 2013 The Authors. Published by Elsevier Ltd.