| Description |
This work presents the general characteristics of cumulus convection and the large-scale environment in a simulation of tropical precipitating convection known as the Giga-LES. A moist static energy (MSE)-based analysis is used because MSE mixes linearly and is conserved for moist adiabatic motions. The MSE-based analysis is rst used to examine the properties of convection over height and amount of dilution through mixing, and a minimum dilution greater than zero is quantied. Additionally, an interesting pattern of average buoyancy over MSE and height in the simulation is revealed, possibly linked to cloudy downdrafts and mixing at the edge of clouds. Investigating further, an MSE-based analysis is performed on selected subregions of the simulation domain, particularly the near cloud environment (NCE) of cloudy updrafts in the simulation. It is found that the NCE around all sizes of updrafts, from shallow to deep convection, contains points with properties of a subsiding shell. The dynamical importance of the evaporative-cooling driven subsiding shell has already been demonstrated in previous work studying shallow cumulus clouds. This work presents the rst evidence of subsiding shells in the NCE of deep convection, and quanties the mass ux associated with subsiding shells for dierent sized clouds. With a new understanding of the NCE of active cloudy updrafts, the updrafts themselves are studied further. The work of Lin and Arakawa is discussed which claries how the entraining plumes of the Arakawa and Schubert parameterization should be interpreted. The physical interpretation is that they are composed of subcloud elements with similar detrainment levels that come from dierent cloudy updrafts. How are the subcloud elements that make up these ideal plumes distributed throughout the cloud eld? The answer to this question has implications for the viability of dierent techniques of cumulus parameterization. I present a new method for characterizing the dilution of a cloud with a constant fractional entrainment rate that is sensitive to the cloud's population of least diluted subcloud elements. This allows for variability in both CTH and composition of least diluted subcloud elements to be simultaneously examined over thousands of active cloudy updrafts in the simulation. |
