Evaluation of RadVil, a Radar-Based Very Short-Term Rainfall Forecasting Model

Abstract

Abstract A very short-term rainfall forecast model is tested on actual radar data. This model, called RadVil, takes advantages of voluminal radar data through vertically integrated liquid (VIL) water content measurements. The model is tested on a dataset collected during the intensive observation period of the Mesoscale Alpine Program (MAP). Five rain events have been studied during this experiment. The results confirm the interest of VIL for quantitative precipitation forecasting at very short lead time. The evaluation is carried out in qualitative and quantitative ways according to Nash and correlation criteria on forecasting times ranging from 10 to 90 min and spatial scales from 4 to 169 km2. It attempts to be consistent with the hydrological requirements concerning the rainfall forecasting, for instance, by taking account of the relation between the catchments' size, their response time, and the required forecasting time. Several versions of RadVil corresponding to several VIL measurement strategies have been tested. Improvements offered by RadVil depend on meteorological situations. They are related to the spatial and temporal evolution of the VIL field structure and the validity of the models assumptions. Finally, a relationship between the temporal structure of VIL fields and forecast quality is established.