Extended Eddy-Diffusivity Mass-Flux Schemes

15 We demonstrate that an extended eddy-diffusivity mass-flux (EDMF) scheme can be used 16 as a unified parameterization of subgrid-scale turbulence and convection across a range 17 of dynamical regimes, from dry convective boundary layers, over shallow convection, to 18 deep convection. Central to achieving this unified representation of subgrid-scale mo19 tions are entrainment and detrainment closures. We model entrainment and detrainment 20 rates as a combination of turbulent and dynamical processes. Turbulent entrainment/detrainment 21 is represented as downgradient diffusion between plumes and their environment. Dynam22 ical entrainment/detrainment are proportional to a ratio of buoyancy difference and ver23 tical velocity scale, partitioned based on buoyancy sorting approaches and modulated 24 by a function of relative humidity difference in cloud layer to represent buoyancy loss 25 owing to evaporation in mixing. We first evaluate the closures offline against entrain26 ment and detrainment rates diagnosed from large-eddy simulations (LES) in which trac27 ers are used to identify plumes, their turbulent environment, and mass and tracer ex28 changes between them. The LES are of canonical test cases of a dry convective bound29 ary layer, shallow convection, and deep convection, thus spanning a broad range of regimes. 30 We then compare the LES with the full EDMF scheme, including the new closures, in 31 a single column model (SCM). The results show good agreement between the SCM and 32 LES in quantities that are key for climate models, including thermodynamic profiles, cloud 33 liquid water profiles, and profiles of higher moments of turbulent statistics. The SCM 34 also captures well the diurnal cycle of convection and the onset of precipitation. 35 Plain Language Summary 36 The dynamics of clouds and their underlying turbulence are too small in scale to 37 be resolved in global models of the atmosphere, yet they play a crucial role controlling 38 weather and climate. Climate and weather forecasting models rely on parameterizations 39 to represent the dynamics of clouds and turbulence. Inadequacies in these parameter40 izations have hampered especially climate models for decades; they are the largest source 41 of physical uncertainties in climate predictions. It has proven challenging to represent 42 the wide range of cloud and turbulence regimes encountered in nature in a parameter43 ization that can capture them in a unified physical framework. Here we present a pa44 rameterization that does capture a wide range of cloud and turbulence regimes within 45 a single, unified physical framework, with relatively few parameters that can be adjusted 46 to fit data. The framework relies on a decomposition of turbulent flows into coherent up47 and downdrafts (i.e. plumes) and random turbulence in their environment. A key con48 tribution of this paper is to show how the interaction between the plumes and their tur49 bulent environment—the so-called entrainment and detrainment of air into and out of 50 plumes—can be modeled. We show that the resulting parameterization represents well 51 the most important features of dry convective boundary layers, shallow cumulus convec52 tion, and deep cumulonimbus convection. 53