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To investigate the spatiotemporal distribution characteristics of Convective Initiation (CI) during the warm season (May-September) over the North China region, this study utilises composite reflectivity mosaic data from regional radar networks across North China for the warm seasons spanning 2022 to 2024. An objective identification algorithm specifically designed to detect “isolated” CI events is developed. Leveraging this algorithm, a comprehensive CI database for North China is subsequently constructed. Detailed statistical analyses are then performed on this database to elucidate both the temporal and spatial patterns of CI occurrence within the region. The principal findings derived from this research are summarised as follows: (1) Sensitivity experiments focus on two key parameters within the objective CI identification algorithm: the lower threshold for convective cell area (A) and the screening radius (R). The results demonstrate a significant sensitivity in the number of identified CI events to variations in these parameters. Specifically, setting a larger threshold value for the minimum convective cell area (A) effectively filters out nascent convective cells that fail to develop further. Conversely, employing a larger screening radius (R) aids in filtering out newly initiated convective cells occurring in close proximity to pre-existing, already identified convective cells, thereby refining the detection to focus on truly isolated initiation events. (2) The temporal distribution of CI events during the warm season in North China exhibits distinct patterns. Monthly analysis reveals that the highest frequency of CI occurrences is concentrated in July and August, while May registers the lowest number. Diurnally, CI events display a pronounced unimodal structure, with a clear peak in activity observed between 13:00 and 17:00. (3) Spatially, CI events during the warm season in North China show a highly heterogeneous distribution. High-frequency CI zones are predominantly concentrated along major mountain ranges and their foothills. These include the Yinshan Mountains in Inner Mongolia, the northern Yanshan Mountains near Beijing, the Lvliang Mountains on the western flank of Shanxi Province; the Taihang Mountains along the eastern border of Shanxi Province, the Zhongtiao Mountains in southern Shanxi, the eastern extensions of the Qinling Mountains in Henan Province, and the western and northern flanks of the Taiyi Mountains in Shandong Province. Notably, exceptionally high CI frequency zones are identified within the southern segment of the Taihang Mountains (eastern Shanxi) and the eastern Qinling Mountain extensions in Henan. Conversely, regions exhibiting significantly lower CI frequency encompass the Inner Mongolia Plateau, the Hetao Plateau, the basins situated between the mountain ranges flanking Shanxi Province, and the expansive North China Plain. This clear spatial dichotomy underscores that CI hotspots are overwhelmingly associated with mountainous terrain, while CI-sparse areas predominantly coincide with relatively flat plateaus, basins, and plains. These research findings, detailing the objective identification methodology and the resulting spatiotemporal climatology of CI over North China, provide valuable insights and offer a substantive reference for enhancing CI potential forecasting and nowcasting capabilities in the region.