More Like this

1. “Wind Theft” from Onshore Wind Turbine Arrays: Sensitivity to Wind Farm Parameterization and Resolution

   https://doi.org/10.1175/JAMC-D-19-0235.1  

   Pryor, Sara C. ; Shepherd, Tristan J. ; Volker, Patrick J. H. ; Hahmann, Andrea N. ; Barthelmie, Rebecca J. ( January 2020 , Journal of Applied Meteorology and Climatology)

   High-resolution simulations are conducted with the Weather Research and Forecasting Model to evaluate the sensitivity of wake effects and power production from two wind farm parameterizations [the commonly used Fitch scheme and the more recently developed Explicit Wake Parameterization (EWP)] to the resolution at which the model is applied. The simulations are conducted for a 9-month period for a domain encompassing much of the U.S. Midwest. The two horizontal resolutions considered are 4 km × 4 km and 2 km × 2 km grid cells, and the two vertical discretizations employ either 41 or 57 vertical layers (with the latter having double the number in the lowest 1 km). Higher wind speeds are observed close to the wind turbine hub height when a larger number of vertical layers are employed (12 in the lowest 200 m vs 6), which contributes to higher power production from both wind farm schemes. Differences in gross capacity factors for wind turbine power production from the two wind farm parameterizations and with resolution are most strongly manifest under stable conditions (i.e., at night). The spatial extent of wind farm wakes when defined as the area affected by velocity deficits near to wind turbine hub heights in excess of 2% of the simulation without wind turbines is considerably larger in simulations with the Fitch scheme. This spatial extent is generally reduced by increasing the horizontal resolution and/or increasing the number of vertical levels. These results have important applications to projections of expected annual energy production from new wind turbine arrays constructed in the wind shadow from existing wind farms.

    

   more » « less
2. A wind-albedo-wind feedback driven by landscape evolution

   https://doi.org/10.1038/s41467-019-13661-w  

   Abell, Jordan T. ; Pullen, Alex ; Lebo, Zachary J. ; Kapp, Paul ; Gloege, Lucas ; Metcalf, Andrew R. ; Nie, Junsheng ; Winckler, Gisela ( January 2020 , Nature Communications)

   The accurate characterization of near-surface winds is critical to our understanding of past and modern climate. Dust lofted by these winds has the potential to modify surface and atmospheric conditions as well as ocean biogeochemistry. Stony deserts, low dust emitting regions today, represent expansive areas where variations in surficial geology through time may drastically impact near-surface conditions. Here we use the Weather Research and Forecasting (WRF) model over the western Gobi Desert to demonstrate a previously undocumented process between wind-driven landscape evolution and boundary layer conditions. Our results show that altered surficial thermal properties through winnowing of fine-grained sediments and formation of low-albedo gravel-mantled surfaces leads to an increase in near-surface winds by up to 25%; paradoxically, wind erosion results in faster winds regionally. This wind-albedo-wind feedback also leads to an increase in the frequency of hours spent at higher wind speeds, which has implications for dust emission potential.

    

   more » « less
3. Katabatic Wind-Driven Exchange in Fjords: WIND-DRIVEN EXCHANGE

   https://doi.org/10.1002/2017JC013026  

   Spall, Michael A. ; Jackson, Rebecca H. ; Straneo, Fiammetta ( October 2017 , Journal of Geophysical Research: Oceans)
4. Effect of wind veer on wind turbine power generation

   https://doi.org/10.1063/5.0033826  

   Gao, Linyue ; Li, Bochen ; Hong, Jiarong ( January 2021 , Physics of Fluids)
5. Probabilistic Characterization of Wind Diurnal Variability for Wind Resource Assessment

   https://doi.org/10.1109/TSTE.2020.2965444  

   Jang, Youngchan ; Byon, Eunshin ( October 2020 , IEEE Transactions on Sustainable Energy)