Atmospheric convection is a dominant process for the meteorological conditions in the troposphere, causing a vertical redistribution of air masses, including the associated energy and moisture budgets, leading to a stabilised stratification. The representation of convective processes in large-scale models is difficult, since the horizontal size of typical convective cells is on the order of a few kilometres, but the grid size of climate models on the order of hundred kilometres. Consequently, the individual clouds cannot be explicitly resolved, but their effects must be parameterised. Instead of a traditional convection parameterisations which are subject to large uncertainties, a so-called ”superparameterisationâ is going to be implemented in the chemistry climate model EMAC within this project. Such a superparameterisation describes the effects of the small scale convective processes by applying an ensemble of clouds which are simulated with the help of a cloud resolving in each gridcell. Instead of filling each of the global grid boxes with grid cells from the cloud resolving model only a reduced ensemble of cells is used which allows resolved cloud processes, including dynamics and interactions on the cloud scale, but is less computationally demanding compared to a global cloud resolving model. From this ensemble the mean effects of the small scale clouds within the climate model grid cell are determined allowing for feedbacks with the larger scale phenomena. Results from the simulations using the superparameterisation are going to be evaluated against global satellite data sets for clouds and radiation.