| Popis: |
Recently, projects such as the S2S (Sub-seasonal to Seasonal) have surfaced with the goal of investigating the potential benefits of operational applications of medium- to long-term weather forecasts from two weeks to three months. Key challenges are to quantify forecast uncertainty and verify these predictions considering the downstream users. This work evaluates the meteorological lead-time performance and 5-years skill evolution of nine models of the S2S project alongside discharge predictions from a coupled hydrological model. Moreover, an analysis of the predictors of Numerical Weather Prediction (NWP) quality and an evaluation of the correlation between meteorological and hydrological quality improvement over time is carried out. Results show that the S2S models have skill at the catchment-scale, particularly for lower threshold levels, and that ensemble size is the main predictor of NWP performance. Discharge simulations forced with S2S predictions remain skilful up to one month. The quality of the S2S has increased over time, and there is a strong correlation between meteorological and hydrological improvements. We conclude that S2S products may provide added value to end-users of water resources applications. |
