Advantage of 30-s-Updating Numerical Weather Prediction With a Phased-Array Weather Radar Over Operational Nowcast for a Convective Precipitation System

Convective precipitation systems in the summer often cause sudden heavy precipitation and largely affect various human activities, but the rapid evolution limits our predicting capability. Phased-array weather radars (PAWRs) with a high spatiotemporal resolution are useful for observing such precipitation system. A recently developed numerical weather prediction (NWP) system assimilates PAWR observations with a 500-m mesh NWP model. It initiates 30-min extended forecasts every 30 s, much more frequently than the operational NWP and nowcasting systems. This study investigates the benefits of the 30-s-updating NWP system in a single but representative convective precipitation event in which a convective cloud developed within 10 min, and its evolution was not well predicted by operational precipitation nowcasting. The rapidly updating NWP system successfully predicts the evolution of the convective cloud. Assimilating the PAWR observations every 30 s continuously modifies the moisture and dynamical fields and improves the forecast accuracy consistently.

Automated summary

This study investigates the benefits of a 30-second-updating NWP system in predicting convective precipitation events, and shows that continuously assimilating PAWR observations can improve forecast accuracy by consistently modifying moisture and dynamical fields.