Evolution and Characteristics of Mesoscale Convective Systems over the Congo Basin

Abstract Mesoscale convective systems (MCSs) are the dominant rainfall-producing systems over the Congo basin, yet their life cycle, structure, and environmental drivers remain poorly understood. This study constructs a 20-yr climatology (2001–20) of MCS characteristics and rainfall using Python Flexible Object Tracker (PyFLEXTRKR)—a flexible tracking algorithm that integrates brightness temperature and precipitation data to capture system evolution. We analyze diurnal, seasonal, and spatial variability of MCSs, highlighting the role of regional circulation features in shaping their development and rainfall production. Seasonal comparisons reveal that, despite being less intense and large, September–November (SON) MCSs produce comparable or greater rainfall than March–May (MAM) systems, supported by larger precipitating areas, higher precipitation feature (PF) rain rates, and longer system lifespans, under more humid and thermodynamically favorable conditions in this season. Trend analysis from 2001 to 2020 reveals increasing MCS intensity, declining PF rain rates, and longer upscale growth times. These trends suggest evolving convective structures and growing thermodynamic constraints on rainfall production, despite intensifying convection. The contribution of MCSs to local extreme daily rainfall has also increased, particularly in SON. These findings provide new insight into MCS behavior over the Congo basin, establish a climatological benchmark for the region, and offer guidance for improving rainfall prediction and the representation of convection in climate models. Significance Statement This study examines mesoscale convective systems (MCSs) in the Congo basin, a region central to tropical convection and global water cycles. MCSs drive over 70% of local rainfall, yet their dynamics remain poorly understood. By analyzing 20 years of satellite data, findings reveal distinct diurnal and seasonal characteristics, with implications for understanding climate variability and model evaluation. These findings establish a foundation for future research on MCSs in the Congo basin and provide a benchmark to enhance rainfall predictions and improve the representation of convection in climate models for this understudied yet climatologically significant region.