Increasing the skill of short-term wind speed ensemble forecasts combining forecasts and observations via a new dynamic calibration

This means that the contribution of wind power in power systems is becoming increasingly important. The downside is that detailed schedule plans and reserve capacity must be properly set by power system regulators (Impram et al., 2020) facing the intrinsic problem of the highly intermittent nature of wind, making this very hard to predict. The accuracy of wind forecasts thus becomes an issue of paramount importance for the wind industry. In a recent work by Casciaro et al. (2021), a novel accurate Ensemble Model Output Statistics (EMOS) strategy for calibrating wind speed/power forecasts from an Ensemble Prediction System (EPS) has been proposed and its superiority when compared against more parsimonious strategies in the 0-48 h look-ahead forecast horizon clearly emerged. However, because all global weather models start their run from analysis corresponding to the main synoptic hours 00, 06, 12, and 18 UTC, weather predictions (of any forecast horizons) necessarily remain frozen for six hours.