Simulated Low-Level Jets in the North and Baltic Seas: Sensitivity Analysis and Climatology

Accurately accounting for Low-level jets (LLJs) in wind resource assessment is increasingly important as the height of wind turbines continues to grow. During LLJ events, wind speeds increase, leading to a general increase in power output. However, the vertical wind shear and veer associated with LLJs also impact the performance and reliability of wind turbines. Atmospheric conditions, conductive of the LLJs may also modify the wake dissipation properties in large offshore wind farms, depending on the LLJ height relative to the height of the wind farm's rotors. This study aims to optimize the configuration of the Weather Research and Forecasting (WRF) model to represent LLJs around the North and Baltic Seas at heights relevant to wind energy production. Using the optimal WRF model configuration, we derive a detailed long-term LLJ climatology focusing on wind energy implications.

We utilize wind measurements from LiDARs and a mast for five sites to assess the quality of the WRF model simulations for LLJ characterization. We also investigate the benefits of WRF simulations compared to the widely used ERA5 re-analysis. In the WRF model simulations, we vary the grid spacing, vertical resolution, and the planetary boundary layer scheme and land surface models, parameters we deemed most likely to have a substantial impact. The model’s performance was evaluated based on its ability to replicate observed distributions of LLJs and relevant associated characteristics, such as the shear and veer across the rotor-plane of typical large offshore wind turbines (30-300 meters). 

Our results show a strong dependency of the LLJ representation and the associated wind profiles on WRF model configuration and that relying on ERA5 for LLJ characterization is insufficient. For example, the LLJ rate-of-occurrence varied by up to a factor of 3 and more between some WRF model runs. The optimized model more accurately reflects the frequency, intensity, and vertical extension of LLJs, as confirmed by LiDAR data. Subsequent application of this configuration to a multi-year climatology provides new insights into the region's temporal patterns and potential wind energy impacts of LLJs.