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. Plain Language Summary: Convection initiation is the beginning stage of severe convective weather. Accurate prediction of its location and timing is very important for monitoring and early warning of severe convective weather. However, CI forecast is still a great challenge worldwide. The good news is that newly deployed phased‐array radar (PAR) with high spatiotemporal resolution can capture the much needed small‐scale information of the preconvective environment and the whole CI process. This study combines the new PAR observation and numerical weather prediction model through Ensemble Kalman Filter (EnKF), one of the most popular data assimilation techniques, to improve forecast of a CI event. With the improved data, we successfully forecast CI process mainly thanks to the PAR that help improved three‐dimensional winds, temperature, and humidity analysis, particularly in the clear‐air regions. Key Points: First real‐case assimilation of C‐band phased‐array radar clear‐air data on convection initiation using Ensemble Kalman FilterAssimilating clear‐air radial velocity plays a key role in successful forecast of convective initiation (CI)Assimilating clear‐air radial velocity has the potential to accurately forecast CI with a lead time up to 20 min [ABSTRACT FROM AUTHOR]