Abstract: The FY-4B Geostationary High-speed Imager (GHI), featuring a maximum temporal resolution of 1 minute and a spatial resolution of 250 m, enables real-time monitoring of convective evolution. A convection downslope intensification event that caused severe wind and hail disasters in the Beijing plain on June 12, 2022, under the influence of a Northeast China cold vortex, was investigated. Utilizing spatiotemporally matched GHI visible imagery, black body temperature (TBB) data, and Doppler weather radar data, this study compared the capabilities of satellite and radar in monitoring CI and convective merger features, ¹with a particular focus on the ability of GHI to detect precursor signals. The results show that for CI monitoring, GHI visible imagery detected precursor signals over mountainous regions—cumulus cloud lines—approximately 30 minutes earlier than radar , and fully captured the transition from shallow to deep convection along these lines. During the downslope merging stage, the cloud merger time identified by GHI based on TBB was 18 minutes earlier than the echo merger time detected by radar,showcasing its early detection capability for system integration. A comprehensive analysis of GHI observations and data from the Rapid-refresh Multi-scale Analysis and Prediction System-nowcasting revealed that weak low-level convergent uplift over Beijing’s steep terrain was identified as a key dynamical factor for cumulus cloud line formation.This research confirms that high-resolution FY-4B GHI data can significantly improve the timeliness of precursor signal identification for severe convective weather, providing valuable observational evidence for enhancing the forecast and warning of downslope convective processes.