Benchmarking HRRR modeled wind field using multi-source measurements in the complex terrain of the southeastern United States

Wind energy development in the southeastern United States (SEUS) has faced limitations due to lower mean wind speeds and unique regional features, such as complex terrain and variable land use and vegetation. However, with the advancement of taller turbine towers and extended blades, many areas of the SEUS are becoming economically viable prospects for wind energy development. As the southeastern states set ambitious goals for renewable energy and explore the untapped potential of both inland areas and coastlines, wind energy is gaining traction as an effective and sustainable energy source. Despite the renewable and generally cost-effective nature of wind energy, its availability fluctuates based on the prevailing wind speed and direction. Numerical weather prediction (NWP) models are essential tools for operation and decision-making in the wind energy sector. The High-Resolution Rapid Refresh (HRRR), operational at NOAA/NCEP since 2014, is a convection-allowing implementation of the Advanced Research version of the Weather Research and Forecasting (WRF-ARW) Model with hourly data assimilation. During the Second Wind Forecast Improvement Project (WFIP2), model improvements particularly focusing the complex terrain were integrated, leading to notable reduction of the mean absolute error for 80-m wind speed across the Pacific Northwest. However, the effectiveness of this integration in other regions, including the SEUS, is yet to be assessed. The limited validation over the SEUS is compounded by the scarcity of observations, particularly at the turbine hub-height (approximately 100 m above ground level). In this study, we evaluate the turbine hub-height and near-surface wind speed from the HRRR analysis against measurements from diverse sources. The errors then are attributed to the model’s representation of terrain complexity and forest canopy characteristics. The insights gained from this study will play a pivotal role in defining the further model development with a focus on wind profiles within a few hundred meters of the surface, which can enrich wind resource assessment, planning, and management endeavors.