Evaluation of a High-Resolution Regional Climate Simulation for Surface and Hub-height Wind Climatology over North America

Abstract. Assessing the availability of key wind resources requires augmenting observations to support the implementation of wind energy infrastructure. However, observations are limited, necessitating the development of high resolution, long-term gridded datasets. This study presents a robust, dynamically downscaled climatological dataset, offering 20 years of hourly wind data at a 4-km spatial resolution across North America, and evaluates its performance against observations, including meteorological towers and Automated Surface Observing Stations (ASOS), as well as a coarse-resolution reanalysis data 一 European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis version 5 (ERA5). Results demonstrate that the downscaled high resolution wind data outperforms ERA5 in regions of complex terrain and coastal areas, with improved overlap ratios for wind data distributions and reduced root mean square errors (RMSE) for hub-height and near-surface diurnal wind patterns. The downscaled simulation also reasonably captures the synoptic drivers of seasonal wind direction patterns, indicated by high wind rose overlap ratios. This study also provides an analysis of interannual variability, utilizing the dataset’s full 20-year period, and model uncertainty, generated by varying model initial conditions and physics parameterizations across 1-year ensemble members, which are key considerations for wind resource assessment in wind farm development.