Human-driven climate change unleashes severe weather events that affect millions of people worldwide every year, notably by reshaping the patterns of intense precipitation. More extreme rainfall events can generate more flooding, landslides, and pose threats to natural and human systems, calling for a deeper understanding of the causes behind the long-term evolution of extreme rainfall. This study investigates the underlying causes of recent observed changes in extreme rainfall events by analyzing patterns from CMIP6 climate models simulations. Previously, we discovered that the increase in greenhouse gas (GHG) emissions and the uneven spatial distribution of anthropogenic aerosols (AA) emissions have influenced the observed changes in mean precipitation. Here, we show that GHG and AA emissions together have also driven global changes in annual extreme rainfall. The first mechanism captures an intensification of extreme rainfall, mainly due to GHG increases, partially masked by an AA-induced drying signal. The second captures the decadal changes in extreme rainfall driven by aerosol-induced shifts in the tropical rain belt. We use different sets of simulations and observations, ECS information, and bias-corrected datasets to evaluate climate models' ability to reproduce observed forced component, focusing on the roles of aerosols, climate sensitivity, and horizontal grid resolution.