Towards Adaptive Grids for the Modeling of the Atmospheric Boundary Layer

From a modeling perspective, the most challenging atmospheric scenarios are characterized by processes which are localized in the spatial and temporal domain. Examples include the radiative cooling of nocturnal cumulus cloud interfaces and the diurnal cycle. Therefore, adaptive grids hold an important advantage over the usage of fixed grids. By adaptively varying a model's resolution is space and time, the required effort to run a model becomes a function of the complexity of the resolved physics. The associated scaling of the simulation costs with an increasing resolution is then favorable compared to that of regular fixed grid approaches. We present results obtained for a variety of modeling fidelities, using adaptive grids. Ranging from turbulence resolving direct numerical simulation and large-eddy simulation, to Reynolds-averaged techniques. The overall analysis shows that the used and novel methods form a powerful tool for studies on challenging, dynamical atmospheric cases.