Analysis of Potential Wind Farm Impacts on Turbulent Mixing and the Nocturnal Low-Level Jet during the American WAKE ExperimeNt (AWAKEN)

Wind farms are steadily increasing around the world, and they will continue to grow in size and number as efforts shift toward a carbon-neutral future harnessing more renewable energy. Understanding their impacts can provide insight on how they may alter the atmosphere.

Doppler lidars can be used to collect time series of vertical velocity w at high temporal resolution; this can then compute vertical velocity variance (the square root of which is w) to help understand how wind plants may impact turbulent mixing properties at turbine height. Doppler lidars are also a rich data resource for analyzing wind speeds, including important boundary layer features such as the nocturnal low-level jet (NLLJ). However, the depth of the observed profiles depends on how much aerosol content the lidar laser can scatter off, which typically declines with height. The limited height coverage may inhibit accurate NLLJ classifications. An algorithm to retrieve wind profiles via optimal estimation (WINDoe) has been recently developed; one of its many advantages is resolving deeper boundary layer profiles than what traditionally-filtered observations can provide while also including uncertainty information of the estimated wind speeds. This aids in meeting the scientific objectives of this study: determining if wind farms induce turbulent mixing, and how these findings might change with NLLJs of different strengths.

To accomplish this goal, we analyzed lidar observations in northern Oklahoma, where the American WAKE ExperimeNt (AWAKEN) took place. Multiple AWAKEN sites were analyzed, with a primary focus on two locations where Collaborative Lower Atmospheric Mobile Profiling Systems (CLAMPS) platforms were deployed. The CLAMPS1 trailer collected near-farm observations, while CLAMPS2 collected far-field observations, allowing for comparisons between datasets of different atmospheric characteristics inside and outside the path of wind farms’ likely area of influence. Each CLAMPS contained a Halo scanning lidar, among other instruments, which continuously measured vertical velocity from roughly 60-4000 m at a 1-second temporal resolution. From this, 10-minute w was computed at averaged heights closest to those of the turbine rotor disk. Wind speed ws also measured at a 10-minute temporal resolution, where wind speed retrievals were computed using WINDoe. Results show the overall trend in w is higher at the near-farm site than the far-field site, and increases with NLLJ strength. When the direction of the winds was assessed, southerly flow consistently depicted the same results, suggesting an impact due to wind farms. Future investigation involves including winter cases also available from AWAKEN and analyzing only cases of pristine conditions to best understand potential turbine-driven effects.