Abstract: This study conducted a comprehensive analysis of a severe convective weather event in Wuzhou, Guangxi, on 22 April 2022, utilizing multi-source satellite data from the Fengyun-4A (FY-4A) satellite. The research focused on investigating the application value of satellite remote sensing for severe convection early warning. Employing datasets including water vapor imagery, visible light, infrared enhanced cloud imagery, quantitative convective products, and equivalent blackbody brightness temperature (TBB), the study systematically revealed the evolutionary characteristics of severe convective cloud clusters and their linkage mechanisms with extreme weather. Results indicate that the development of convective cloud clusters is characterized by decreasing cloud-top brightness temperature, enhanced water vapor blocking, and the evolution of dynamic dry intrusions. Regions with low TBB values (≤230 K) correspond well with areas of heavy precipitation. A 5-minute TBB decrease rate exceeding -10 K serves as a precursor to short-term heavy rainfall, while a decrease rate exceeding -30 K corresponds to the maximum spatial extent of hail. Large-scale analysis using water vapor and other cloud imagery effectively complements dual-polarization radar observations. An early warning methodology based on cloud-top temperature gradients demonstrates superior timeliness compared to dual-polarization radar. However, its effectiveness in severe convective weather monitoring has certain limitations due to constraints imposed by the satellite's spatial and temporal resolution (2 km / 3 min).