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

Abstract

AbstractThis 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.