Severe convective weather systems are often accompanied by abundant lightning, and the key discharge characteristics of lightning are closely related to charge regions. However, existing detection methods cannot achieve comprehensive observation of these charge regions, which limits the in-depth understanding of lightning discharge processes.To address this issue, an identification algorithm for charge regions in convective systems was developed based on a multi-channel threshold method combined with a clustering algorithm. The probability of detection (POD), false alarm rate (FAR), and critical success index (CSI) were used as quantitative metrics to evaluate the algorithm’s performance. The results show that the algorithm achieves high identification accuracy, with a POD of 71.67%, a FAR of 3.83%, and a CSI of 69.67%.A comparative analysis was carried out between the proposed algorithm and an existing single-channel threshold algorithm for convective cloud cluster identification, based on the same dataset. Distinct differences were found in their results: charge regions tend to be sporadically distributed, while convective cloud clusters appear as large contiguous patches; the spatial scope of charge regions does not fully overlap with that of convective cloud clusters, and charge regions are likely to be located at the peripheries of cloud clusters; additionally, not all convective cloud clusters contain charge regions. It is concluded that there is a certain spatial displacement between charge centers and convective centers. The research findings provide valuable references for optimizing charge region detection techniques and deepening the study of lightning discharge mechanisms.