The WRF Model Forecast-Derived Low-Level Wind Shear Climatology over the United States Great Plains

For wind resource assessment projects, it is common practice to use a power-law relationship (U(<em>z</em>) ~ <em>z</em>^α) and a fixed shear exponent (α = 1=7) to extrapolate the observed wind speed from a low measurement level to high turbine hub-heights. However, recent studies using tall-tower observations have found that the annual average shear exponents at several locations over the United States Great Plains (USGP) are significantly higher than 1=7. These findings highlight the critical need for detailed spatio-temporal characterizations of wind shear climatology over the USGP, where numerous large wind farms will be constructed in the foreseeable future. In this paper, a new generation numerical weather prediction model—the Weather Research and Forecasting (WRF) model, a fast and relatively inexpensive alternative to time-consuming and costly tall-tower projects, is utilized to determine whether it can reliably estimate the shear exponent and the magnitude of the directional shear at any arbitrary location over the USGP. Our results indicate that the WRF model qualitatively captures several low-level wind shear characteristics. However, there is definitely room for physics parameterization improvements for the WRF model to reliably represent the lower part of the atmospheric boundary layer.