Spatio-temporal heterogeneity of the wind resources over a deciduous forest in the U.S. Southeast

Abstract. The Southeastern United States is predominantly characterized by moderately tall forests (≈ 20 m) which, by absorbing a portion of flow momentum from the Atmospheric Boundary Layer, reduce wind speeds within the rotor layer of modern wind turbines. Taller wind turbines (with hub heights greater than 100 m) are likely to experience higher wind speeds, assuming that wind resources located farther away from the ground are less affected by the forest layer. However, forest canopy drag and heterogeneity effects on wind resources at high altitude above ground have not been fully investigated in the U.S. . In this work, three sites located in a deciduous forest in the Appalachian mountains of the U.S. Southeast are investigated from September 2024 through June 2025 as part of the Lidar Experiments for Assessing Flow over Forests (LEAFF) campaign. Wind statistics are resolved both within the canopy (by a meteorological tower) and above it or in clearings (via four Doppler Lidar). A reference tall wind turbine (with a hub height of 110 m and a rotor layer spanning 45 m to 175 m) is assumed for each site to estimate the available power resource. The wind statistics considered here are the mean wind speed (U), the turbulence intensity (TI) and the cube of the mean wind speed U³, assumed as a proxy for the power in region II of a turbine power curve. The two dominant physical features affecting the wind, i.e. the momentum absorption at the canopy interface (quantified by the drag coefficient, C_d) and the momentum entrainment from the free atmosphere, are quantified as well based on Doppler Lidar data. The present analysis aims to: 1) quantify the monthly variability of wind resources induced by the annual cycle of leaf coverage and changes in the synoptic wind conditions; 2) quantify the correlation of canopy drag and free-atmosphere wind speed with rotor-layer wind statistics; and 3) quantify the wind resource heterogeneity between canopy and nearby forest clearing sites. The present analysis reveals that site inhomogeneities in the wind resources are still found within the bottom half of the rotor layer (i.e., up to the hub height of 110 m) of a tall wind turbine. Additionally, the examined wind resources are more correlated with the wind speed in the free atmosphere than the C_d within the rotor layer, with the only exception of the TI which shows equal correlation with these two quantities. Finally, the largest vertical extent featuring site heterogeneity is found between November and January, which corresponds to the period of minimal leaf coverage (i.e., minimum leaf area index). Overall, the present study shows that, even for tall wind turbines, the wind resources within the rotor area are affected by spatial heterogeneity in surface drag and by the seasonal transition of the canopy leaf coverage. These results have implications for the siting and operation of wind turbines in forested regions, as well as for the siting of Lidar instruments during future observational campaigns.