Forecasting wind power in the short-term usually involves the use of numerical weather prediction models. These models need to run at very high resolutions to provide the best forecasts possible. Producing high resolution forecasts is resource and time consuming, which can be a problem when the forecasts need to be available for the grid operator on the day-ahead. This paper introduces a novel approach for short-term wind power prediction by combining the Weather Research and Forecasting - Advanced Research WRF model (WRF- ARW) with genetic programming, using the latter one for final downscaling and prediction technique, estimating the total hourly power output on the day ahead at a wind farm located in Galicia, Spain.