| Abstract: | Micro‐scale Reynolds‐averaged Navier‐Stokes (RANS) simulations of the neutral atmospheric boundary layer (ABL) over complex terrain and a comparison of the results with conditionally averaged met‐tower data are presented. A robust conditional sampling procedure for the meteorological tower (met‐tower) data to identify near‐neutral conditions based on a criterion for the turbulence intensity is developed. The conditionally averaged wind data on 14 met‐towers are used for the model validation. The ABL flow simulations are conducted over complex terrain which includes a prominent hill using the OpenFOAM‐based simulator for on/offshore wind farm applications (SOWFA) with the k?? and the SST k?ω turbulence models. The discretization of the production term in the transport equation for the turbulent kinetic energy (TKE) is modified to greatly reduce the commonly observed nonphysical near surface TKE peak. The driving inflow is generated through an iterative approach using a precursor method to reproduce the measured wind statistics at the reference tower. Both of the RANS models are able to capture the flow behavior windward of the hill. The SST k?ω model predicts more intense flow separation than the k?? model downstream of the steepest sections of the hill. The wind statistics predicted at the location of the met‐towers by both of the RANS models are fairly consistent. Overall, the comparisons of the direction, mean, and standard deviation of the wind between the simulations and the tower data show reasonable agreement except for the differences of the mean wind speeds at four met‐towers located closer to the main ridge of the hill in a region of strong terrain variations. |
