INSPIRE: Understanding Spatiotemporal Extent and Structure of Large Wind Farm Footprint on Weather and Climate by Combining Observational Analysis with Numerical Modeling

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This INSPIRE award is partially funded by Physical and Dynamic Meteorology program in the Division of Atmospheric and Geospace Sciences in the Directorate for Geosciences, Climate and Large-scale Dynamics program in the Division of Atmospheric and Geospace Sciences in the Directorate for Geosciences, and Environmental Sustainability program in the Division of Chemical, Bioengineering, Environmental, and Transport Systems in the Directorate for Engineering.The global wind industry has experienced a remarkably rapid expansion of capacity in recent years and this fast growth is expected to continue in the future. While converting wind's kinetic energy into electricity, wind turbines modify surface-atmosphere exchanges of energy, momentum, mass and moisture. Given the current installed capacity and the projected installation worldwide, wind farms (WFs) are likely becoming a major driver of manmade land use change on Earth. Hence, understanding WF-atmosphere-environment interactions and assessing potential environmental impacts are of significant societal importance. However, recent studies of WF impacts on meteorology have been primarily in the modeling domain using simplified wind turbine parameterizations (WTPs) due to the lack of observations. Given the availability of high resolution radar and remote sensing data, we believe it is time to begin systematically assessing WF impacts in the U.S.The project will conduct a process-based observational and modeling study to investigate possible impacts on weather, climate and environments due to the rapid development of wind farms (WF) in the Great Plains and Midwest. Specifically, the study will involve analyzing a variety of observational data (near-surface meteorological variables, radar and remote sensed), detecting, quantifying and attributing such impacts over the 17 biggest U.S. WFs, and then performing a series of high resolution mesoscale simulations to evaluate wind turbine parameterizations (WTPs). The investigations will unveil how operational WFs influence the diurnal, seasonal and interannual variations of atmospheric boundary layer (ABL) structures and phenomena, near-surface hydrometeorology, and crop/vegetation growth, and how these changes vary under various meteorological and surface conditions and WF configurations (e.g., elevation, land cover, wind patterns, local climate).Intellectual merit:This research can potentially bridge scientific knowledge gap of (a) atmospheric boundary layer dynamics and thermodynamics within and downwind of operational wind farms and (b) physical processes and mechanisms of wind farm impacts on environment. It will also generate knowledge about the performance of the wind turbine parameterizations and identify model refinements required to simulate wind farms in mesoscale models. It is potentially transformative by providing a comprehensive picture of wind farm footprint on weather and climate, a fundamental step toward projecting the future impacts at large scales, and by challenging conventional wisdom with far more complicated wind farm-atmosphere-environment interactions. Broader Impacts:Wind power supports environmental sustainability and is likely to be part of the solution to the climate change, air pollution and energy security problem. Assessing potential WF impacts is critical for developing efficient adaptation and management strategies to ensure long-term sustainability of wind power. The study will lead to improvements in numerical weather prediction and projection of WF impacts on weather, climate, environments, water cycle and agricultural practices. The obtained knowledge and approaches can be generalized to other studies. In addition, this project has important education and outreach components and will provide learning and training experience for undergraduate and graduate students.