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Detailed Observations of Complex Flow due to Wind Turbine Wakes We utilize profiling lidar (Aitken et al. J Tech 2012, Rhodes and Lundquist BLM 2013, Lundquist et al. AMT 2015), scanning lidar (Smalikho et al. J Tech 2013, Mirocha et al. JRSE 2014, Aitken et al. J Tech 2014, Aitken and Lundquist J Tech 2014), radiometers (Friedrich et al. GRL 2012), meteorological towers (Vanderwende and Lundquist ERL 2012, Clifton et al. JSEE 2013) and tethered lifting systems (Lundquist and Bariteau BLM 2015) to study the development and propagation of wind turbine wakes in different atmospheric conditions, with special interest in wind farms co-located with agriculture (Rajewski et al. BAMS 2013, Rajewski et al. AFM 2014).

Atmospheric Impacts on Wind Energy Production Atmospheric stability impacts wind turbine power production (Wharton and Lundquist WE 2012) sometimes in contradictory ways (Wharton & Lundquist ERL 2012 vs Vanderwende & Lundquist ERL 2012) depending on local meteorology. Neural networks can extend limited measurements at a site towards improved resource assessment (Clifton et al. ERL 2013). Detailed lidar observations and WRF simulations of nocturnal low-level-jets (LLJ) (Vanderwende et al. MWR 2015, to appear) suggest that LLJ-induced wind shear and veer extend into the turbine rotor-layer during intense jets. Ramp events, in which winds rapidly increase or decrease in the rotor-layer, were also commonly observed during jet formation periods. At large spatial scales, we evaluate the statistical independence of wind generators, and find that higher-rate fluctuations in wind power generation can be effectively smoothed by aggregating wind plants over areas smaller than otherwise estimated (St. Martin et al. 2015, in review).

Mesoscale Modeling of Wind Farms To assess the local and regional impacts of wind energy development, we have implemented a wind farm parameterization into the Weather Research and Forecasting model. The Fitch et a. parameterization (MWR, 2012a, 2012b) is available with every WRF download since version 3.3. In simulations of the CASES-99 GABLS case, the wind farm wake varies throughout the diurnal cycle, with the maximum downwind surface temperature increases ~ 0.5K at night (MWR, 2013) consistent with observations. Comparisons between this elevated drag model and climate simulations representing wind farms simply with enhanced surface roughness show nearly the opposite local impacts on surface temperature (Fitch et al. J Climate 2013).

Large Eddy Simulations of the Atmospheric Boundary Layer Improved turbulence models (MWR 2010b) and/or immersed boundary methods (MWR 2010a, MWR 2012) may be required to simulate complex flow in stable atmospheric boundary layers or in regions of complex terrain. To elucidate interactions of atmospheric stability with wind turbine wakes, large-eddy simulations with a generalized actuator disk model (Mirocha et al. JRSE 2014, Aitken et al. JRSE 2014) demonstrate how ambient turbulence accelerates the erosion of wind turbine wakes.

Urban Meteorology Cities can create their own microclimates with interesting implications for detailed simulations of flow in urban areas (Lundquist and Chan JAMC 2006; Lundquist and Mirocha JAMC 2008) and air pollution events (Hu et al. JAMC 2013), especially when urban meteorology interacts with nocturnal low-level jets (LLJ). Immersed boundary methods may be required for simulations in urban areas (Lundquist, Chow, and Lundquist MWR 2010, 2012).