L. Dolcine et al., Evaluation of a conceptual rainfall forecasting model from observed and simulated rain events, HYDROL E S, 2(2-3), 1998, pp. 173-182
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.