Impact of Assimilating C-Band Phased-Array Radar Data With EnKF on the Forecast of Convection Initiation: A Case Study in Beijing, China

This study used a Weather Research and Forecasting (WRF)-based Ensemble Kalman Filter (EnKF) system to assimilate reflectivity (Z) and radial velocity (Vr) data in precipitating and clear-air regions from the Beijing Daxing International Airport C-band phased-array radar (C-PAR) to improve the forecasts of a convective initiation (CI) case occurred on 18 June 2020. The results showed that high-frequency assimilating the C-PAR Vr in clear-air region is conducive to increase the forecast lead time of CI by significantly improving the initial dynamic and thermodynamic fields, which creates a more accurate pre-CI environment. After assimilating the C-PAR clear-air Vr, the CI case can be accurately predicted with a 20 min forecast lead time in the best-case scenario. This is the first real-case study to demonstrate the benefits of assimilating high spatiotemporal resolution PAR clear-air radial velocity data for the CI process.