Geophysical flow is generally characterized by huge Reynolds numbers—which limits our ability to directly represent these systems on a computer. Most practical applications such as weather forecasting or climate projection rely on the representation of small-scale processes, one of which is turbulent mixing, by parameterizations. Sometimes, however, an explicit representation is inevitable to further process-level understanding, for instance for informed representation of mixing processes in parameterizations. While an explicit representation of turbulence is not possible across the entire geophysical range of scales, hydrodynamic/Reynolds-number similarity can be exploited to quantitatively extrapolate the behavior at reduced scale to the geophysically relevant limit of large scale separation. In previous work, we established a research framework based on direct numerical simulation of turbulent Ekman flow to proceed this path. Here, we outline results from the explicit representation of roughness in turbulent Ekman flow. Preliminary results indicate that roughness acts as a geometric reduction of the scale separation in the flow. This potentially allows us to narrow the gap in turbulence scale separation between the numerical simulations possible on modern HPC systems on the one side and the real atmospheric system on the other.