Climate predictions tailored to the wind energy sector represent an innovation to better understand the future variability of wind energy resources. In this work an illustration of the downstream impact of the forecasts as a source of climate information, the post-processed seasonal predictions of wind speed and temperature will be used as input in a transfer model that translates climate information into capacity factor. This transfer model is based on multivariate regression that assumes a linear relationship between wind speed and temperature with the capacity factor