Abstract: Using the China Meteorological Administration (CMA) Multisource Precipitation Analysis System and European Center’s Fifth Generation Reanalysis data for warm seasons (May–September) from 2017 to 2022, precipitation characteristics and diurnal variation patterns are classified using the K-means clustering algorithm under the background of cold vortex in the Northeast China. The following conclusions are drawn from the study. 1) The spatial distribution of the multiyear average precipitation amount shows an increasing trend from the northwest toward the southeast. A similar pattern is observed in the spatial distribution of precipitation frequency, and high-intensity precipitation areas are concentrated near the Liaodong Peninsula. 2) Under the influence of cold vortex, average diurnal variations in precipitation amount, frequency, and intensity exhibit a bimodal pattern. The main diurnal peak in the precipitation amount is primarily attributed to precipitation frequency, while the secondary peak exhibits a remarkable correlation with precipitation frequency and intensity. 3) Third, diurnal variations in the precipitation amount and frequency exhibit either unimodal or bimodal characteristics, while precipitation intensity shows a unimodal distribution. Based on the peak time and patterns, the precipitation amount, frequency, and intensity can be classified into four distinct types of diurnal variation. 4) The spatial distribution statistical results show that grid points exhibiting afternoon peaks form the largest proportion of daily variations in precipitation amount, frequency, and intensity. This is followed by nocturnal peaks. Meanwhile, two variation types display evident regional features closely tied to topography and a relatively orderly distribution. Concerning diurnal variations in cold vortex precipitation intensity, grid points with a single afternoon peak dominate, with their spatial distribution becoming more dispersed after applying the clustering algorithm.