Organized Moist Convection in the Tropics: SP-CAM v.s. CAM

The mesoscale convective system (MCS) contributes about half of the total rainfall in both the observed tropics and in regions where climate models have difficulty with rainfall frequency and distribution. MCS consists of cumulonimbus (strong rainfall) embedded in stratiform (weak rainfall) regions and gains energy from small and large scale perturbations through convective organization. It is therefore not surprising that the large-scale model with parameterized convection struggles to represent the mesoscale organization. Studies show that the mesoscale organization can be resolved in and interact with the large-scale model by embedding a 2-D cloud-resolving model, e.g, super-parameterized Cummunity Atmosphere Model (SP-CAM). It has also been shown that SP-CAM can resolve one of the most significant multi-scale organizations, MJO, which is ill-represented in climate models. With a timestep-wise comparison of CAM with SP-CAM, we found SP-CAM realistically represents the dominant large-scale convective heating mode in the tropics. We also found the weaker heating mode of CAM may be attributed to a weak vertical mass flux mode. This may be rooted in the failure of the deep convection entrainment parameterization to produce the multi-scale organization. We studied the cloud-scale phenomena of SP-CAM to see how multi-scale organization is represented and how it produces the better heating mode. This could benefit future convection parameterizations (e.g., stochastic paramterization) as research shows asemblance of organization as a result of interactions between parameterization and resolved dynamics in large-scale models.