GNSS/PWV在一次梅雨期暴雨中的模式预报应用OA北大核心CSTPCD

The monitoring of atmospheric precipitable water vapor(PWV)via the Global Navigation Satellite System(GNSS)is a potent technique for the continuous collection of atmospheric moisture data,which is vital for regional weather observation and forecasting,especially in the context of severe weather events.Based on the GNSS application demonstration network in the Yangtze River Delta,the present study conducted five three-dimensional variational assimilation experiments incorporating GNSS/PWV data in a numerical weather prediction model.The objective was to refine the mesoscale analysis of a Meiyu rainstorm event that occurred in July 2010 and evaluate the potential of regional ground-based GNSS/PWV to enhance the model's initial conditions and predictive accuracy for Meiyu precipitation events.The analysis showed that the assimilation of GNSS/PWV data into the numerical forecast model for this specific Meiyu rainstorm improved the accuracy of 24-hour precipitation forecast by over 20%,with a 12%improvement observed in the 48-hour forecast.These findings suggest that GNSS/PWV data may help effectively refine water vapor distribution in the observation area,provide water vapor information closely related to rainstorm weather,and significantly improve 48-hour forecast accuracy for the movement speed of mesoscale systems in numerical weather models,thereby enhancing precipitation area forecasts.