Microscale flow models used in the wind energy industry commonly assume statically neutral conditions. These models can provide reasonable wind speed predictions for statically unstable and neutral flows; however, they do not provide reliable predictions for stably stratified flows, which can represent a substantial fraction of the available energy at a given site. With the objective of improving wind speed predictions and in turn reducing uncertainty in energy production estimates, we developed a Reynolds-Averaged Navier-Stokes (RANS)-based model of the stable boundary layer. We then applied this model to eight prospective wind farms and compared the results with on-site wind speed measurements classified using proxies for stability; the comparison also included results from linear and RANS wind flow models that assume neutral stratification. This validation demonstrates that a RANS-based model of the stable boundary layer can significantly and consistently improve wind speed predictions.In order to better predict statically stable flows, we developed a RANS model of the stable boundary layer; we refer to this model as the stable RANS model. The stable RANS model is implemented in STAR-CCM+ (CD-adapco Melville, NY USA), a commercial computational fluid dynamics (CFD) package from CD-adapco. 16 We used STAR-CCM+ as a 2 nd -order, implicit, incompressible RANS solver with k-ε turbulence closure to produce the results presented herein. The following describes the stable RANS model equations with a focus on how they differ from the equations solved in a typical neutral RANS wind flow analysis. The boundary conditions for the stable RANS calculations are also discussed in detail. * The term 'speedup' is used throughout this paper. A speedup refers to the average ratio of wind speed at a target meteorological mast to wind speed at a reference meteorological mast.† This finding is based on an analysis of 82 meteorological masts at 14 sites located in the US Great Plains. The mast heights ranged from 50 to 100 m; each mast had temperature sensors and anemometers at multiple heights.Modeling stable thermal stratification J. Bleeg et al.

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