CWEX demonstrates the importance of collecting field measurements within a wind farm to facilitate basic understanding of the three-way interactions among wind energy, meteorology, and crop agriculture.

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Wind turbine impacts on the atmospheric flow are investigated using data from the Crop Wind Energy Experiment (CWEX-11) and large-eddy simulations (LESs) utilizing a generalized actuator disk (GAD) wind turbine model. CWEX-11 employed velocity-azimuth display (VAD) data from two Doppler lidar systems to sample vertical profiles of flow parameters across the rotor depth both upstream and in the wake of an operating 1.5 MW wind turbine. Lidar and surface observations obtained during four days of July 2011 are analyzed to characterize the turbine impacts on wind speed and flow variability, and to examine the sensitivity of these changes to atmospheric stability. Significant velocity deficits (VD) are observed at the downstream location during both convective and stable portions of four diurnal cycles, with large, sustained deficits occurring during stable conditions. Variances of the streamwise velocity component, σu, likewise show large increases downstream during both stable and unstable conditions, with stable conditions supporting sustained small increases of σu, while convective conditions featured both larger magnitudes and increased variability, due to the large coherent structures in the background flow. Two representative case studies, one stable and one convective, are simulated using LES with a GAD model at 6 m resolution to evaluate the compatibility of the simulation framework with validation using vertically profiling lidar data in the near wake region. Virtual lidars were employed to sample the simulated flow field in a manner consistent with the VAD technique. Simulations reasonably reproduced aggregated wake VD characteristics, albeit with smaller magnitudes than observed, while σu values in the wake are more significantly underestimated. The results illuminate the limitations of using a GAD in combination with coarse model resolution in the simulation of near wake physics, and validation thereof using VAD data.

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Recent wind farm studies have revealed elevated nighttime surface temperatures but have not validated physical mechanisms that create the observed effects. We report measurements of concurrent differences in surface wind speed, temperature, fluxes, and turbulence upwind and downwind of two turbine lines at the windward edge of a utility‐scale wind farm. On the basis of these measurements, we offer a conceptual model based on physical mechanisms of how wind farms affect their own microclimate. Periods of documented curtailment and zero‐power production of the wind farm offer useful opportunities to rigorously evaluate the microclimate impact of both stationary and operating turbines. During an 80 min nighttime wind farm curtailment, we measured abrupt and large changes in turbulent fluxes of momentum and heat leeward of the turbines. At night, wind speed decreases in the near wake when turbines are off but abruptly increases when turbine operation is resumed. Our measurements are compared with Moderate Resolution Imaging Spectroradiometer Terra and Aqua satellite measurements reporting wind farms to have higher nighttime surface temperatures. We demonstrate that turbine wakes modify surface fluxes continuously through the night, with similar magnitudes during the Terra and Aqua transit periods. Cooling occurs in the near wake and warming in the far wake when turbines are on, but cooling is negligible when turbines are off. Wind speed and surface stratification have a regulating effect of enhancing or decreasing the impact on surface microclimate due to turbine wake effects.