Unified Convection Parameterizations: A Stochastic Eddy-Diffusivity/Mass-Flux (EDMF) Approach

The parameterization of turbulent and convective mixing in weather, seasonal and climate prediction models has been a major challenge in meteorological research for a long time. In particular, different parameterizations are used, and patched together often artificially, for different types of convection: dry or moist, in the boundary layer or in the full troposphere. The Eddy-Diffusivity (ED) approach has been relatively successful in representing some characteristics of neutral boundary layers and surface layers in general. The Mass-Flux (MF) approach, on the other hand, has been used for the parameterization of shallow and deep moist convection. In this presentation, a new approach that relies on an optimal combination of the ED and MF parameterizations (EDMF) is discussed in detail as a possible solution for the unification of the parameterizations of convective mixing in global atmospheric models. In particular we will present results from a new stochastic EDMF approach coupled with cloud microphysics that fully unifies the representation of convection in weather and climate prediction models: One parameterization that represents the effects of dry, shallow and deep moist convection in the atmosphere.