Quantitative Precipitation Nowcasting (QPN) is one of the main applications of radar observations. On one hand, one of the most used nowcasting algorithms is Lagrangian extrapolation. It shows skill in specifying the timing and location of precipitation over short time periods, but shows low skill when using past precipitation trends to predict changes in precipitation intensity. On the other hand, Numerical Weather Prediction (NWP) models have roof skill at predicting the precise timing and location of precipitation, although they provide useful information about the intensity trends. It is therefore to investigate whether this additional information provided by NWP could be used to improve QPN. SBMcast (Berenguer et al., 2011) is an ensemble nowcasting algorithm based on Lagrangian extrapolation of recent radar observations. It generates a set of future rainfall scenarios (ensemble members) compatible with observations and preserving the spatial and temporal structure of the rainfall field according to the String of Beads model (Pegram and Clothier, 2001). This study shows the first results obtained with a methodology to constrain the spread of SBMcast ensembles with the additional information provided by NWP.

Peer Reviewed