Abstract:The disastrous nature of severe convective weather and the need for its accurate monitoring and forecasting have garnered widespread attention. This paper summarizes the main characteristics, environments, formation mechanisms, and dual-polarization Doppler weather radar observation features of various typical types of convective storms and severe convective weather. It presents fundamental concepts and understanding, briefly outlines forecasting approaches and monitoring techniques for severe convective weather, and provides prospects for future work. In recent years, main advances are as follows. Gravity waves are an important type of trigger mechanisms of nocturnal convective storms. The key formation mechanisms of severe convective weather in low convective available potential energy environments with strong vertical wind shear are on meso-γ scale vortices, which have been significantly understood. The sorting effect of supercell updrafts on precipitation particles results in highly distinctive dual-polarization radar signatures, and the signatuers such as ZDR column, ZDR arc, KDP foot have revealed more charatericstics of microphysical processes and dynamical structure of supercells. Most bow echoes in South China are formed through the merger of quasi-linear convective systems with pre-existing convective cells ahead of them. Mesovortices develop through multiple complex mechanisms. The intensification of updrafts by meso-γ scale vortices such as mesocylones and mesovortices is an important aspect of heavy rainfall formation mechanism. The meso-γ scale vortices, combined with rear-inflow jets of bow echoes, play a crucial role in extreme severe thunderstorm gale. A great many convective storms producing short-duration heavy rainfall often exhibit hybrid characteristics between continental and tropical maritime types, and it has been found that the heavier the instaneous extreme rainfall intensity in South China, the more the liquid and ice water content in convective storms. Hailstones with diameters ≥5.0 cm are primarily generated by supercells, and their growth rarely follows spiral trajectories or cyclic growth paths. Tornadogenesis hinges on the formation, concentration, and intensification of near-surface vertical vorticity. High-resolution numerical forecasting and deep learning techniques have significantly improved the accuracy of severe convective weather monitoring, forecasting, and warning systems. Future efforts should focus on the “about-100-m” fine-scale mechanisms and super-high-resolution numerical models, and deep learning models with fully integrating physical laws for comprehensive severe convective weather forecasting.