Abstract: The daily grid precipitation data from 1961 to 2018 were obtained by interpolating data from more than 2400 national meteorological stations in China. Based on this data set, regression analysis, Morlet wavelet transform, and other methods are employed to analyze the spatial and temporal characteristics of the rainstorm and regional rainstorm in South China; moreover, the variation laws of heavy precipitation are revealed. Results show that from 1961 to 2018, the maximum number of annual rainstorm days and amount of rainstorm rainfall in South China are distributed in the coastal areas of Guangdong, Guangxi, and Fujian, as well as Hainan Province and the northern part of Guangxi. The number of rainstorm days and amount of rainfall are the largest in summer, followed by spring. From the northern part of Guangxi to the junction of Guangxi, Hunan, and Guangdong provinces, the southern part of Guangdong, Fujian, and Hainan provinces, the increasing trend of rainstorm days, rainfall, and intensity are the most significant. The regional mean increasing trend is the highest in summer, followed by autumn. Additionally, the number of regional rainstorm days and processes in South China presents the occurrence of a single peak distribution, which could occur throughout the year. Moreover, the maximum value appears in June. The annual average number of regional rainstorm days and processes are 28 d a⁻¹ and 16.5 a⁻¹, and the increasing rates are 0.15 d a⁻¹ and 0.097 a⁻¹. In four seasons, the increasing rate is the fastest during summer and the slowest in autumn. The average and maximum of a single course duration increase significantly at the rate of 0.015 d a⁻¹ in winter but show a decreasing trend in spring. For the periodic change, the South China rainstorm and regional rainstorm show quasi-three-year, quasi-14-year, and quasi-18-year cycle changes to different degrees in annual and seasonal fluctuations. After 2000, the quasi-18-year long period and quasi-three-year short-period oscillations of annual rainstorms and regional rainstorms are extremely significant.