Cumulus parameterization (CP) in state-of-the-art global climate models (GCM) is based on the quasi-equilibrium assumption (QEA), which views convection as the action of an ensemble of cumulus clouds, in a state of equilibrium with respect to a slowly varying atmospheric large-scale state. This view is not compatible with the organization and dynamical interactions across multiple scales of cloud systems in the tropics and progress in this research area was slow over decades despite the widely recognized major shortcomings. Novel ideas on how to represent key physical processes of moist convection-large-scale interaction to overcome the QEA have surged recently. The stochastic multicloud model (SMCM) CP in particular mimics the dynamical interactions of multiple cloud types that characterize organized tropical convection. Here, the SMCM is used to modify the Zhang-McFarlane (ZM) CP by changing the way in which the bulk mass flux is calculated. This is done by introducing a stochastic ensemble of plumes characterized by randomly varying detrainment level distributions based on the cloud area fraction (CAF) of the SMCM. The SMCM is here extended to include shallow cumulus clouds resulting in a unified shallow-deep CP. The new stochastic multicloud plume CP is validated against the control ZM scheme in the context of the single column Community Climate Model of the National Center for Atmospheric Research using six test-cases including both tropical ocean and midladitude land convection. Some key features of the SMCM SP such as it capability to represent the tri-modal nature of organized convection are emphasized.