We demonstrate that an extended eddy-diffusivity mass-flux (EDMF) scheme can be used as a unified parameterization of subgrid-scale turbulence and convection across a range of dynamical regimes, from dry convective boundary layers, through shallow convection, to deep convection. Central to achieving this unified representation of subgrid-scale motions are entrainment and detrainment closures. We model entrainment and detrainment rates as a combination of turbulent and dynamical processes. Turbulent entrainment/detrainment is represented as downgradient diffusion between plumes and their environment. Dynamical entrainment/detrainment is proportional to a ratio of a relative buoyancy of a plume and a vertical velocity scale, that is modulated by heuristic nondimensional functions which represent their relative magnitudes and the enhanced detrainment due to evaporation from clouds in drier environment. We first evaluate the closures offline against entrainment and detrainment rates diagnosed from large-eddy simulations (LES) in which tracers are used to identify plumes, their turbulent environment, and mass and tracer exchanges between them. The LES are of canonical test cases of a dry convective boundary layer, shallow convection, and deep convection, thus spanning a broad range of regimes. We then compare the LES with the full EDMF scheme, including the new closures, in a single column model (SCM). The results show good agreement between the SCM and LES in quantities that are key for climate models, including thermodynamic profiles, cloud liquid water profiles, and profiles of higher moments of turbulent statistics. The SCM also captures well the diurnal cycle of convection and the onset of precipitation.Plain Language Summary The dynamics of clouds and turbulence are too small in scale to be resolved in global models of the atmosphere, yet they play a crucial role in controlling weather and climate. These models rely on parameterizations for representing clouds and turbulence. Inadequacies in these parameterizations have hampered especially climate models for decades; they are the largest source of physical uncertainties in climate predictions. It has proven challenging to represent the wide range of cloud and turbulence regimes encountered in nature in a single parameterization. Here we present such a parameterization that does capture a wide range of cloud and turbulence regimes within a single, unified physical framework, with relatively few parameters that can be adjusted to fit data. The framework relies on a decomposition of turbulent flows into coherent updraft and downdraft (i.e., plumes) and random turbulence in their environment. A key contribution of this paper is to show how the exchange of mass and properties between the plumes and their turbulent environment-the so-called entrainment and detrainment of air into and out of plumes-can be modeled. We show that the resulting parameterization represents well the most important features of dry convective boundary layers, shallow cumulus convection, and de...