Preliminary Assessment of Seasonal Weather Forecasts for Water Resources Management

The focus of this activity is on seasonal meteorological forecasts (time horizon greater than one month), which are crucial for implementing strategies to manage hydroelectric reservoirs, especially for large-capacity plants where water resources can be stored during wetter seasons to ensure availability during dry periods.

Seasonal forecasts are a cutting-edge product, consisting of a statistical synthesis of meteorological information up to seven months ahead. Since the atmosphere is a chaotic system, forecast evolution is sensitive to errors in initial conditions, limiting the ability to predict weather variations beyond 15 days. However, longer-term forecasts are possible by considering components of the Earth system that evolve more slowly than the atmosphere, such as the oceans. Seasonal forecasts rely on an ensemble of different atmospheric evolutions, from which average values and expected anomalies for upcoming seasons can be derived, compared to historical periods with available reference climatology.

Currently, there is limited evidence in the literature of using seasonal forecasts in the hydroelectric context. In this activity, their performance is assessed at the national scale of Italy for the ensemble mean of key meteorological variables: 2-meter temperature and precipitation. For temperature, results show a fair level of performance in the early months, suggesting added value compared to simple climatology, with degradation as the forecast horizon extends. For precipitation, performance is generally lower than for temperature, and the model struggles to provide more useful information than climatology at longer horizons. Snow is also considered, revealing a significant underestimation by the forecast model, and a simple correction method is proposed.