A statistical method based on the ensemble probability density function for the prediction of “Wind Days”

To reduce the systematic error, we test different thresholds and numbers of consecutive hours when the definition of WD is applied to model outputs. All the models show remarkably better performances after these parameters are changed. In particular, our method shows the best performance, with an accuracy of 94%. The analysis on test (leave-one-out strategy in 2016) and validation datasets (66 cases in 2017) confirms the previous outcomes. We test our procedures considering the forecast time intervals of 49-72 and 25-48 h, where similar performances are found. In conclusion, our analysis show that the proposed method presents better performances compared to the traditional approaches for different statistical performance indicators.