Investigating the optimal WRF model setup for modelling diurnal cycles of wind speed at turbine heights in Sweden

Mesoscale atmospheric models are widely used to provide long term time series of winds at turbine heights. Mesoscale models are known to poorly estimate diurnal cycles in wind speed. For example, the NEWA model dataset on average overestimates the magnitude of the diurnal cycle of the wind speed by 1.4 m/s. Diurnal errors in modelling wind speed can significantly affect estimates of annual energy production, even if the overall mean wind speed is correctly modelled.

Previous WRF model wind speed sensitivity studies have usually focused on overall performance metrics such as mean bias and correlation, while rarely targeting diurnal cycles of the wind speed explicitly. This work compares the performance of different WRF model setups in predicting the diurnal cycle of wind speed. Our goal is to identify the WRF setup that minimises the diurnal error in modelled wind speeds. We test three surface-layer schemes, three radiation schemes, and 15 planetary boundary layer (PBL) schemes.

For each of the WRF setups, we perform a 1-year-long run over Sweden. We compare modelled diurnal and seasonal cycles of the wind speed against observed ones from EMD’s internal mast database containing data from 62 observation campaigns at wind turbine heights. In addition, different model outputs are compared to each other, to better investigate the effects of different parametrisations on the modelled wind speeds.

Our results show that the choice of the PBL and surface layer schemes has a significant impact on modelled wind speeds during the night, while having little effect on modelled winds during the day. On the other hand, the choice of the radiation scheme mostly affects modelled wind speeds during the day. Results show that the better-performing setup for modelling diurnal wind cycles at 100 m is a combination of the MYJ PBL scheme, the Eta similarity surface layer scheme, and the RRTMG radiation scheme. Nevertheless, the best setup still overestimates the magnitude of the diurnal cycle of wind speed by 0.4 m/s.

Our results show that the choice of WRF parametrisation can significantly reduce the diurnal bias in mesoscale models. However, further research is needed to resolve the diurnal bias completely.