Assimilating FY-4A Lightning and Radar Data for Improving Short-Term Forecasts of a High-Impact Convective Event with a Dual-Resolution Hybrid 3DEnVAR Method

A dual-resolution, hybrid, three-dimensional ensemble-variational (3DEnVAR) data assimilation method combining static and ensemble background error covariances is used to assimilate radar data, pseudo-water vapor observations improve short-term severe weather forecasts with the Weather Research Forecast (WRF) model. The higher-resolution deterministic forecast lower-resolution members have 3 9 km horizontal resolution, respectively. water pseudo-observations are derived from combined use of total lightning cloud top height Fengyun-4A(FY-4A) geostationary satellite. First, a set single-analysis experiments conducted provide preliminary performance evaluation effectiveness hybrid for assimilating multisource observations; second, cycling analysis evaluate in convective-scale high-frequency analysis; finally, different coefficients tested both single experiments. results show that able generate reasonable vertical velocity, hydrometeor adjustments, which help trigger convection earlier forecast/analysis reduce spin-up time. dual-resolution 3DEnVAR adjust wind fields variables helps maintain triggered longer partially suppress spurious cells compared variational (3DVAR) method. introduced large number more frequent small adjustments better resolve observed convective events than approach. Different can affect results, either or Overall, we found coefficient 0.4 an 0.6 yields best skill this event.