Characterization of HRRR simulated Rotor Layer Wind Speeds and Clouds along Coast of California

Abstract. Stratocumulus clouds, with their low cloud base and top, affects the atmospheric boundary layer wind and turbulence profile, modulating wind energy resources. GOES satellite data reveals an abundance of stratocumulus clouds in late spring and summer months off the coast of Northern and Central California where there are active plans to deploy floating offshore wind farms at two lease areas (near Morro Bay and Humboldt). From fall 2020, two buoys with multiple instrumentations including lidar were deployed for about 1 year in these wind farm lease areas to assess the wind energy resources in these locations. In this study, we characterize the stratocumulus cloud properties and wind speed at turbine-relevant rotor layer (from surface to 300 m above sea level) in both buoy observations and the High Resolution Rapid Refresh (HRRR) model. First, we find that HRRR numerical model reproduces the seasonal cycle of cloud top height quite well in these locations. However, during the warm season, especially at Morro Bay, we find the stratocumulus clouds simulated by HRRR tend to have lower cloud tops by about 150 m and weaker diurnal cycles compared to the satellite reported cloud observations. Next, our findings show that the wind speed and vertical shear are stronger in Humboldt location than in Morro Bay. Also, those fields are stronger under clear sky conditions in both locations. Finally, our findings suggest that the model bias in rotor layer wind speed is small under cloudy conditions, while the bias is large and increases with observed wind speed under clear sky condition. At Morro Bay, the model under clear-sky condition is underestimating the observed wind speed, while at Humboldt, there is overestimation in the model simulated wind speed. The findings from this study will potentially inform how to improve the modeling of wind resources off the coast of Northern California.