Changes in boundary layer clouds in response to global warming as well as their interactions with aerosols are two key sources of uncertainty in future climate projections and climate sensitivity estimation. In this observational study, we examine how the organization of boundary layer clouds into mesoscale morphology patterns (O~100 km) may modulate both cloud feedback and aerosol forcing. We utilize identifications from a supervised neural network algorithm that categorized near-global satellite retrievals into three mesoscale cellular convective (MCC) cloud morphology patterns. At constant cloud fraction, brightness differences between morphology patterns depend in part on the prevalence of optically thin cloud features. Environmentally driven transitions from closed MCC to other morphology patterns, which are typically accompanied by more optically thin cloud features associated with increased precipitation depletion, are used as a framework to quantify the morphology contribution to the optical depth component of the shortwave cloud feedback. Including a measure of anthropogenic aerosol in addition to environmental controls in this regime framework provides insights into the sensitivity of aerosol forcing to cloud morphology shifts under current and future climates.