The system is being applied for wind farms in several regions of the central US. ARPS simulations with a 1-hour or 2-hour update frequency and horizontal resolutions of 6 to 10 km are used to produce deterministic high frequency forecasts of the flow within the layer from 50 m to 100 m above ground level. The system employs the ARPS three-dimensional variational (3DVAR) scheme to assimilate data from a variety of sources including surface mesonet data, wind profilers, Doppler radars and meteorological observations from the wind farms themselves. As part of the development and evaluation process for this forecast system, an investigation of the impact of grid resolution, type of assimilated data and the formulation of the model boundary layer parameterization on performance of the ARPS low-level wind forecasts (before and after the application of MOS) was examined by executing parallel runs with different configurations. An overview and analysis of forecast performance comparisons from the parallel runs will be presented. The analysis of the results provide considerable information into the relative importance of these factors for short-term 50-m to 100-m wind forecast performance as well as insight into the situations in which forecast uncertainty is the largest. The initial results indicate that vertical processes and convection are associated with the largest short-term forecast uncertainty.