|Title:||Reducing errors of wind speed forecasts by an optimal combination of post-processing methods.
|Authors:||Conor Sweeney, Peter Lynch, Paul Nolan, 2011|
|Abstract:|| Seven adaptive approaches to post-processing wind speed forecasts are discussed and compared. Forecasts of the wind speed over 48 h are run at horizontal resolutions of 7 and 3 km for a domain centred over Ireland. Forecast wind speeds over a 2 year period are compared to observed wind speeds at seven synoptic stations around Ireland and skill scores calculated. Two automatic methods for combining forecast streams are applied. The forecasts produced by the combined methods give bias and root mean squared errors that are better than the numerical weather prediction forecasts at all station locations. One of the combined forecast methods results in skill scores that are equal to or better than all of its component forecast streams. This method is straightforward to apply and should prove beneficial in operational wind forecasting. Copyright © 2011 Royal Meteorological Society|
|ICHEC Project:||ZEPHYR: Dynamical and statistical down-scaling of ensemble forecasts for wind energy applications in Ireland.|
|Publication:||Meteorological Applications, DOI, 10.1002/met.294|
|Keywords:|| adaptive post-processing; numerical weather prediction; Kalman filter; artificial neural network|