Human assessment of hydrometeorological forecasts and communication of their uncertainties in a decision making context

In operational conditions, the actual quality of meteorological and hydrological forecasts do not allow decision-making in a certain future. In this context, meteorological and hydrological probabilistic forecasts allow a better representation of forecasts uncertainties. Compared to classical deterministic forecasts, probabilistic forecasts improve the human expertise of hydrological forecasts, which is essential to synthesize available information coming from different meteorological and hydrological models and human experience. Probabilistic forecasts and its human expertise are also necessary to ensure a good communication of hydrometeorological forecasts uncertainties to end-users. However, Probabilistic forecasts must be statistically calibrated and our experienced have revealed that forecasters tend to under-estimate forecasts uncertain ties. To achieve a better statistical calibration of ensemble forecasts, recent development made at EDF try to take into account the automatic generation of meteorological ensembles and rainfall-runoff uncertainties.