Grid resolution effects on wind farm representation in HARMONIE-AROME

Rapid growth of the wind energy industry has led to increasingly congested wind harvesting areas, necessitating that numerical weather prediction (NWP) models better resolve wind farm effects. HARMONIE-AROME is a widely used, operational, mesoscale NWP which has been shown to effectively capture wind farm physics using the established Fitch wind farm parameterization (WFP). The Royal Netherlands Meteorology Institute (KNMI) operates HARMONIE with the standard grid-size of 2 km; however, this scale is relatively coarse compared to wind farms. Within this framework, wind turbines are implemented as a momentum sink, and multiple turbines can occupy one grid point. Various studies have shown that including this WFP is necessary for accurate weather predictions near wind farms. However, a smaller grid-size can potentially improve model performance by better resolving the wind farm–atmosphere interactions.

To this end, we investigate the effect of reducing the grid-size to 1 km for one week when various relevant observations are available to support validation. In the interest of offshore wind farms, we evaluate the model performance by comparing the predicted wind speed to offshore measurements with varying proximity to wind turbine arrays (FINO 1 and 3 masts, Europlatform Lidar, and X-wakes flight). Additionally, we compare to onshore measurements in relatively turbine-free conditions (Cabauw mast) to confirm that the WFP does not degrade the performance for this configuration.  Overall, we observed that near wind farms, the WFP improves model performance compared to simulations without WFP, as expected. We also observed that at locations farther from the wind farm, the contribution and effectiveness of the WFP can be dependent on the wind direction. Most notably, we observed that reducing the grid resolution to 1 km did not exhibit a consistent advantage in predicting wind speed at a point location over time. However, we found that increasing the resolution can improve predictions over a spatial trajectory. Therefore, a higher resolution is recommended to effectively study wind farm physics, such as wind speed distribution throughout the farm, wake development, and farm-to-farm interactions.