In the wind resource industry Computational Fluid Dynamics (CFD) has gained widespread use to model the Atmospheric Boundary Layer (ABL). These models primarily focus on the neutrally stratified surface layer and ignore physical process such as buoyancy and the Coriolis force. Reductions in uncertainties of turbine suitability and energy production can be achieved if these processes are included. The present work focuses on the development and validation of an ABL CFD model using Monin-Obukhov Similarity Theory (MOST) in which atmospheric stability and the Coriolis force are included. MOST is applied to measured time series data obtained from a commercially proposed wind farm to determine the prevalence and impact of atmospheric stability. The analyses provide the inputs for the CFD model. The CFD model uses the standard k − turbulence model. To account for atmospheric stability modifications based on MOST are introduced to the standard CFD model equations. Two MOST models modifications are investigated. The modifications are successfully validated using the empty domain horizontal homogeneity test of the inlet profiles. The model is thereafter applied to the complex terrain of the proposed wind farm. The models are successfully validated by cross-prediction of the stability-dependent wind velocity profiles between two onsite meteorological masts.