  All numerical weather prediction models used for the wind industry need to
produce their forecasts starting from the main synoptic hours 00, 06, 12, and
18 UTC, once the analysis becomes available. The six-hour latency time between
two consecutive model runs calls for strategies to fill the gap by providing
new accurate predictions having, at least, hourly frequency. This is done to
accommodate the request of frequent, accurate and fresh information from
traders and system regulators to continuously adapt their work strategies.
Here, we propose a strategy where quasi-real time observed wind speed and
weather model predictions are combined by means of a novel Ensemble Model
Output Statistics (EMOS) strategy. The success of our strategy is measured by
comparisons against observed wind speed from SYNOP stations over Italy in the
years 2018 and 2019.
