Abstract: To deepen the understanding of the microphysical characteristics of heavy precipitation associated with low vortices in the Guangxi region, this study analyzes the macro- and micro-scale characteristics of an extreme heavy rainfall event that occurred in Nanning, Guangxi on May 19, 2024. Observational data from Doppler weather radar, rain gauges, disdrometers, as well as ERA5 reanalysis data are utilized. The results are as follows. (1) This heavy precipitation event consisted of two stages: warm-sector rainfall and systematic rainfall. The former occurred in the southerly warm sector ahead of the low vortex, with its echo morphology evolving from initially isolated and scattered forms into organized clusters. The latter was triggered by the vortex shear and a newly developed vortex along the shear line, with its echo morphology successively developing through bow-shaped, herringbone, and bow-shaped structures. (2) Compared with the systematic rainfall stage, stratiform precipitation during the warm-sector stage has a smaller mass-weighted average diameter (D_m) and a larger generalized intercept parameter (log₁₀N_w), whereas warm-sector convective precipitation has a larger D_m and a comparable log₁₀N_w. These distinct raindrop size distribution characteristics between the two stages lead to significant differences in the fitted Z-R relationships. (3) Among the five types of heavy precipitation objectively classified by the K-means raindrop size distribution classification algorithm, the occurrence frequency of the two types with “low concentration and large diameter” during the warm-sector rainfall stage is significantly higher than that during the systemic rainfall stage. This was primarily attributed to the higher strong echo top heights and more active ice-phase microphysical processes associated with warm-sector rainfall. The results reveal the differences in raindrop size distribution characteristics during different stages of the low-vortex heavy precipitation process, which can provide a scientific reference for subsequent precipitation retrieval using radar data.