A major challenge in contemporary parameterizations of cumulus convection is  associated with their inability to capture the interactions across multiple temporal and spatial scales  of cloud systems in the tropics. This is mainly due to the lack of an adequate representation of the subgrid variability associated with organized convection, inherited from the underlying quasi-equilibrium assumption (QEA).

We propose a new modelling paradigm based on a stochastic multicloud model (SMCM) which allows an efficient emulation of cloud-cloud interactions and their effect on the organization of convection on multiple scales and a seamless treatment of shallow and deep convection parametrization within the mass-flux parameterization framework.

The SMCM is based of the representation of the multiple cloud types that characterize deep convection, namely, shallow, congestus, deep, and stratiform, by an order parameter that takes discrete values on a square lattice overlaid on top of each model grid box and evolves dynamically as a Markovian process with transition probabilities depending on the large-scale (model resolved) dynamics and thermodynamics.

This for instance allows build up of CAPE and progressive moistening of the environment prior to deep convection which is then followed by stratiform anvils as it pertains to the convection life cycle in tropical convective systems.

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