Accurate Representation of Organized Convection in CFSv2 Via a Stochastic Lattice Model

General circulation models (GCM) show limitations of various sorts in their representation of synoptic and intra-seasonal variability associated with tropical convective systems apart from the success of superparameterization and cloud system permitting global models. This systematic deficiency is believed to be due to the inadequate treatment of organized convection by the underlying cumulus parameterizations, which have the quasi-equilibrium assumption as a common denominator. By its nature, this assumption neglects the continuous interactions across scales between convection and the large scale dynamics.  By design, the stochastic multicloud model (SMCM) mimics the interactions between the three cloud types, congestus, deep, and stratiform, that are observed to play a central role across multiple scales in the dynamics and physical structure of tropical convective systems.  It is based on a stochastic lattice model, overlaid over each GCM grid box, where an order parameter taking the values 0,1,2,3 at each lattice site according to whether the site is clear sky or occupied by a congestus, deep, or stratiform cloud, respectively.  As such the SMCM mimics the unresolved variability due to cumulus convection and the interactions across multiple scales of organized convective systems, following the philosophy of superparameterization.

Here, we discuss the implementation of the SMCM in NCEP Climate Forecast System model (CFS), version-2, through the use of a simple parametrization of adiabatic heating and moisture sink due to cumulus clouds based on their observed vertical profiles (a.k.a Q1 and Q2). Much like the success of superparameterization but without the burden of high computational cost, a 20 year run showed tremendous improvements in the ability of the CFS-SMCM model to represent synoptic and intraseasonal variability associated with organized convection as well as a few minor improvements in the simulated climatology when compared to the control CFSv2 model which is based on the widely used simplified Arakawa-Shubert parameterization. This extra-ordinary improvement comes in despite the fact that CFSv2 is one of the best GCMs in terms of its representation of intra-seasonal oscillations in the tropical atmosphere.