In order to strengthen the understanding of the climatic patterns and enhance the predictive ability of precipitation in Guizhou during the warm season (PGWS). Based the precipitation observation data, reanalysis data from NCEP/NCAR, and sea surface temperature data from HadISST, the spatial and temporal distribution characteristics of PGWS and its relationship with abnormal circulation using various climate statistical methods is analysed. The results shows that the distribution of PGWS and its percentage of the annual precipitation generally showed the pattern of more in the south and less in the north, more in the west and less in the east. The difference between the dry and wet seasons was more significant and precipitation had a stronger concentration in the western region; There is a significant interannual (decadal) variations and quasi-20 years and quasi-7 years oscillation periods of PGWS; The distribution of PGWS is significantly correlated with the sea surface temperature in the Indian Ocean and Atlantic Ocean in the previous period, as well as the position index of the subtropical high ridge line and the East Asian trough during the same period; When there is an excess of PGWS, there is a trough extending from the polar vortex in the northern hemisphere towards the Ural Mountains and Northern Canada, the circulation pattern in Northeast Asia characterized by a high west and low east is conducive to the increase in meridional circulation and the guidance of cold air southward to affect southern China. This is accompanied by the abnormal positive circulation ascending branch over the northern side of Guizhou, which jointly affects the convergence and uplift of water vapor from Bay of Bengal and the South China Sea within Guizhou, which provided favorable conditions for the formation of precipitation; The distribution of PGWS is also closely related to the SSTA in the North Pacific, the west coast of North America, the western Pacific, the North Atlantic, and the equatorial Atlantic during the previous autumn and winter.