Evaluation of a conceptual rainfall forecasting model from observed and simulated rain events

Very short-term rainfall forecasting models designed for runoff analysis of catchments, particularly those subject to flash-floods, typically include one or more variables deduced from weather radars. Useful variables for def ining the state and evolution of a rain system include rainfall rate, verti cally integrated rainwater content and advection velocity. The forecast mod el proposed in this work complements recent dynamical formulations by focus ing on a formulation incorporating these variables using volumetric radar d ata to define the model state variables, determining the rainfall source te rm directly from multi-scan radar data, explicitly accounting for orographi c enhancement, and explicitly incorporating the dynamical model components in an advection-diffusion scheme. An evaluation of this model is presented for four rain events collected in the South of France and in the North-East of Italy. Model forecasts are compared with two simple methods: persistenc e and extrapolation. An additional analysis is performed using an existing monodimensional microphysical meteorological model to produce simulated rai n events and provide initialization data. Forecasted rainfall produced by t he proposed model and the extrapolation method are compared to the simulate d events. The results show that the forecast model performance is influence d by rainfall temporal variability and performance is better for less varia ble rain events. The comparison with the extrapolation method shows that th e proposed model performs better than extrapolation in the initial period o f the forecast lead-time. It is shown that the performance of the proposed model over the extrapolation method depends essentially on the additional v ertical information available from voluminal radar.