Atmospheric phenomena across a wide range of scales impact wind power plant aerodynamics. For this reason, problems in wind engineering are best solved using an integration of measurements and models. This approach is used herein to answer a series of distinct research questions. The overarching objective of this work is to improve the quantification of flow parameters of relevance to the wind energy industry in heterogeneous landscapes. These landscapes include complex terrain and land-sea boundaries, turbulent flow within wind farms, and the numerical space referred to as gray zone in atmospheric modeling.

Focusing on the Great Lakes region, a new methodology for offshore wind resource assessment is presented, which is primarily based on in situ and remote sensing observations. It is demonstrated that a combination of distinct data sets yields a robust wind atlas and reduces the error in the final resource.

Seeking to better characterize wind farm aerodynamics, a new approach is proposed to increase the level of detail in low-fidelity wind turbine wake modeling. It consists of a stochastic model which moves away from the commonly used steady, axisymmetric wake modeling framework. When combined with a description for the velocity deficit distribution and used as input to a structural dynamics model, the proposed wake shape model is found to improve predictions of fluctuating loads and power.

Still aiming to characterize wakes, a different study is performed to quantify the level of uncertainty in wind speed retrievals when sampling a large atmospheric volume with a scanning lidar in a wind turbine wake. A high-fidelity simulation is conducted and resampled to match the field measurements, enabling for a comparison between spatially and temporally disjunct points, and what would be seen by the lidar if it could either obtain a snapshot or a true temporal mean of the same volume of air.

Finally, when running full physics atmospheric simulations that are nested down from the meso to the micro scale it is important to consider the treatment of the gray zone in which half the turbulence is naturally resolved by the model while the other half needs to be parameterized. Cutting edge simulation techniques are employed to investigate three different ways of approaching this problem. In one such simulation we further determine how much of the discrepancy between measured and modeled flow parameters can be attributed to wake effects.