The MJO in a Coarse-Resolution GCM with a Stochastic Multicloud Parameterization

The the Madden-Julian oscillation (MJO) is the dominant mode of variability of the tropical troposphere at the intra-seasonal scale. It originates over the Indian Ocean warm pool and propagates slowly eastward as a complex envelope of convection involving coherent patterns of winds, temperature, and humidity. The MJO is at the intersection of weather and climate variability and controls most of weather phenomena in the tropical region over the Indian Ocean/Western Pacific and beyond and has a tremendous influence on the global weather patterns and climate variability. However, its representation is still a challenge for numerical weather prediction and general circulation models (GCMs) due to the inadequate treatment of convection by the underlying cumulus parameterizations. These deterministic parameterizations fail to represent properly the interactions across scale of multiscale organized convective systems that are embedded within the MJO envelope.

One new promising direction is the use of stochastic multicloud models (SMCM) that have been designed specifically to capture the missing variability due to unresolved processes of convection and their impact on the large scale flow. The SMCM specifically models the area fractions of the three cloud types (congestus, deep and stratiform) that characterize organized convective systems of all scales. The SMCM captures the stochastic behavior of these three cloud types via a judiciously constructed Markov birth death process using a particle interacting lattice gas model. The SMCM has been successfully applied for convectively coupled waves in a simplified primitive equation model and validated against radar data of tropical precipitation.

In this work we use for the first time the SMCM in a GCM. We build on previous work of Khouider et al. (JAS, 2011) where they coupled the High-Order Methods Modeling Environment (HOMME) NCAR-GCM to a simple deterministic multicloud model. We tested the new SMCM-HOMME model in the parameter regimes considered in Khouider et al. (JAS 2011) and found that the stochastic model improves drastically the results of the deterministic multicloud-HOMME model. Clear MJO-like structures are reproduced by SMCM-HOMME in all the physically relevant parameter regimes and more importantly, one of the caveats of the deterministic simulation of requiring a doubling of the moisture background is not required anymore.