Abstract:Based on hourly precipitation data from high-density national and regional stations in Guizhou Province from April to September in 2010–2023, as well as SRTM elevation data and ERA5 reanalysis data, this study systematically investigates the fine-scale spatio-temporal characteristics of rainstorms and their relationships with terrain in Guizhou by using multivariate terrain combination analysis and a geographically weighted regression (GWR) model. The results show that rainstorms in Guizhou are distributed unevenly with three rainstorm centers. The maximum frequency and intensity of rainstorms are concentrated in the southeastern edge area and extremely heavy rainstorms are scattered. The rainstorm proportion is higher in the northeastern and central-southern parts of Guizhou. Rainstorm days show an increasing interannual variability, peaking in 2020–2021. Rainstorms occur mainly in June and July, often accompanied by short-duration heavy precipitation and lasting for a long time, which poses high disaster risks. Diurnal variation of precipitation is unimodal and dominated by nocturnal rain (22:00–08:00 BT), and the rainfall intensity often reaches its peaks around 03:00 BT. Short-duration heavy precipitation exhibits a pronounced nocturnal peak, and the nighttime precipitation amount is roughly twice the daytime precipitation, mainly concentrated in the west and south of Guizhou and featured with eastward propagation. The Guizhou rainstorm-prone areas correspond to the topographic uplift zones of the Beipan River, Leigong Mountain, and Fanjing Mountain, reflecting terrain–wind coupling. Single terrain factors are weak to be directly correlated to precipitation. However, through the analysis of multiple terrain combinations, the explanatory power of precipitation distribution has been enhanced. Slope, aspect, elevation, and relief exert nonlinear effects. Rainstorm stations are the most in south aspects. Rainstorm frequency increases when slope is <20°, elevation ranges in 800–1,000?m, and relief is <200 m, but decreases beyond these thresholds. The combined analysis indicates that the steep/moderate slope, south aspect, medium elevation, large/medium relief, and windward slope has the strongest triggering effect. The GWR model diagnosis suggests that there is obvious spatial heterogeneity in the influence of topographic factors.. Elevation is the dominant factor in most areas of Guizhou, and the local influence of relief, slope and aspect is strong, mostly concentrated in the vicinity of large relief or near rivers and mountains.