Atmosphere-Surface Coupling and Turbulence Scale Separation
Monin–Obukhov similarity theory (MOST) is the back-bone for coupling the atmospheric model component of numerical models to the underneath surface. MOST applies for homogeneous and stationary conditions, but it is used in ever more complex and heterogeneous configurations. In previous work, a set-up was developed to estimate the validity of MOST as a function of filter scale. This set-up critically relies on direct numerical simulation of turbulent Ekman flow above a smooth surface to explicitly resolve the near-wall dynamics. While these simulations give an explicit representation of near-wall turbulence, existing studies are limited to rather small Reynolds numbers. Here, we will use more recent simulation data at higher Reynolds number to investigate the dependence of the behavior on scale separation in atmospheric flow and thus eventually allow for an extrapolation of the DNS results to the atmospheric problem at scale.
Supplementary information: The candidate will have to work on large amounts of data from a turbulence-resolving model. He should have a solid background in scripting and programming in at least one of Python or FORTRAN.