Sonia Wharton

One fundamental assumption of surface layer flow theory is homogeneity over a horizontal plane, a hypothesis systematically challenged for many atmospheric flows. For example, variability in terrain elevation, presence of heterogeneous roughness sub-layers and mesoscale motions can alter the spatio-temporal flow evolution even over small distances (≈1 km). In this scenario, the experimental investigation of air-land interactions requires simultaneous data acquisitions at multiple sites, against which the hypothesis of flow homogeneity can be assessed. The Appalachian Mountains (in the Southeastern United States) represent a compelling environment to resolve complex flows over small distances due to their irregular terrain (800-1500 m elevation above sea level) and presence of moderately tall deciduous forests (~20 m) and open fields constituting an uneven roughness sub-layer. In this work, three nearby instrument sites (within 2 km of each another) are investigated as part of the Lidar Experiments for Assessing Flow over Forests (LEAFF) campaign located in and around a deciduous forest in mountainous Virginia (U.S.). Ten months of wind statistics are resolved both within the canopy by a well instrumented flux tower, and above it via four remote sensing Doppler Lidar (up to 300 m above ground, i.e. ≈15 times the forest height), thereby resolving the turbulent flow developing over a roughness sublayer with high statistical accuracy. The goal of the present analysis is twofold. First, to quantify the monthly variability of wind statistics induced by the annual cycles of leaf senescence and synoptic winds. Second, to quantify the heterogeneity of the wind statistics between different but closely spaced sites across different months. A year’s worth of data showed that the wind statistics are predominantly affected by synoptic forcing, while the leaf senescence cycle plays a marginal role in shaping mean wind and turbulence within the surface . Additionally, site-to-site heterogeneity is found to change following a monthly time scale, a result emphasizing the importance of selecting a sufficiently long observational period to correctly address site heterogeneity under different background flow conditions. The present study provides a compelling observational dataset to validate numerical weather prediction tools accounting for the presence of a forest sub-layer, as well as improving our understanding of the physical mechanisms inducing flow heterogeneities over complex terrains.

Multiscale numerical weather prediction models transition from mesoscale (Δ ≳ 1 km), where turbulence is fully parameterized, to microscale (Δ ≲ 100 m), where the majority of highly energetic scales of turbulence are resolved. This region, called the turbulence gray-zone, was intensively studied during a tracer release experiment called METEX21 in the mountainous U.S. southwest. Terrain-atmosphere interactions that influence local-scale or gray-zone (100’s m to < 5 km) plume transport and dispersion under varying atmospheric forcing conditions were of special interest. Plumes were generated using a smoke tracer released at various sites along horizontal and vertical transects. A full suite of meteorological instruments was deployed in the domain to gather wind, turbulence, thermodynamic and plume observations in the lower boundary layer. Three multiscale simulations which vary by the parameterization used for turbulence and mixing within the gray-zone were evaluated against the 9-days of field data. Here, we highlight significant plume behavior differences on synoptically-forced and locally-forced days and show evidence of how katabatic, anabatic, and mountain-valley diel wind reversals strongly influence plume behavior over the local-scale. We demonstrate that microscale predictions of transport and dispersion can be significantly influenced by the choice of turbulence and mixing parameterization in the terra incognita, particularly over regions of complex terrain and with strong local forcing. Lastly, we highlight the effectiveness of scanning lidars to measure 2-dimensional plume transport out to a 2–3 km distance; much farther than could be visibly observed. We hope that these results motivate future field campaigns involving controlled tracer releases and corresponding modeling studies of the turbulence gray-zone.

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.

The atmospheric boundary layer above forest canopies is difficult to measure in practice, and our understanding of its flow physics, including the potential wind resource, is limited in part by observational constraints. Most available datasets come from tower point measurements, which do not generally reach into heights encountered by a turbine rotor, or from remote sensing measurements, which are usually located outside of the forest in a clearing and thus do not accurately represent flow conditions above the canopy. Here, we present a field campaign that deployed four Doppler lidars in a U.S. Appalachian Forest including installment on top of a 30 m tall tower. These lidars allow for wind measurements across tall turbine rotor heights to be made directly above forested regions. Nearby wind turbines in the wooded Appalachians have hub-heights approaching 90 m and rotor diameters of 127 m, with maximum and minimum blade heights of 152 m and 25 m, respectively. We describe the experimental set-up, lidar strategies, adjoining radiosonde and UAS IOPs, and novel use of AI to drive optimal lidar scans. These data are being collected as part of the DOE “Addressing Challenges in Wind Forecasting for Tall Turbines Across Regions with Terrain and Land Surface Heterogeneity” project and will be used for analysis of forest-atmosphere interactions and numerical model validation.

Cosmogenic beryllium-10 and beryllium-7, and the ratio of the two (10Be/7Be), are powerful atmospheric tracers of stratosphere–troposphere exchange (STE) processes; however, measurements are sparse for altitudes well above the tropopause. We present a novel high-altitude balloon campaign aimed to measure these isotopes in the mid-stratosphere called Beryllium Isotopes for Resolving Dynamics in the Stratosphere (BIRDIES). BIRDIES targeted gravity waves produced by tropopause-overshooting convection to study their propagation and impact on STE dynamics, including the production of turbulence in the stratosphere. Two custom-designed payloads called FiSH and GASP were flown at altitudes approaching 30 km to measure in situ turbulence and beryllium isotopes (on aerosols), respectively. These were flown on nine high-altitude balloon flights over Kansas, USA, in summer 2022. The atmospheric samples were augmented with a ground-based rainfall collection targeting isotopic signatures of deep convection overshooting. Our GASP samples yielded mostly negligible amounts of both 10Be and 7Be collected in the mid-stratosphere but led to design improvements to increase aerosol capture in low-pressure environments. Observations from FiSH and the precipitation collection were more fruitful. FiSH showed the presence of turbulent velocity, temperature, and acoustic fluctuations in the stratosphere, including length scales in the infra-sonic range and inertial subrange that indicated times of elevated turbulence. The precipitation collection, and subsequent statistical analysis, showed that large spatial datasets of 10Be/7Be can be measured in individual rainfall events with minimum terrestrial contamination. While the spatial patterns in rainfall suggested some evidence for overshooting convection, inter-event temporal variability was clearly observed and predicted with good agreement using the 3D chemical transport model GEOS-CHEM.

METEX21 was an atmospheric tracer release experiment executed at the Department of Energy’s Nevada National Security Site (NNSS) in the southwestern U.S to study terrain-induced wind and thermodynamic conditions that influence local-scale (<5-km) plume transport under varying atmospheric forcing conditions. Meteorological observations were collected using 10-m tall meteorological towers, 2-m tall tripods with 3-d sonic anemometers, a 3-m tall eddy covariance flux tower, Doppler profiling lidars, Doppler scanning lidars, weather-balloon launched radiosondes, and a tethered balloon equipped with wind, temperature, and aerosol sensors at heights up to 800 m. A smoke tracer was released along three transects in the horizontal and vertical directions and observed with video cameras, aerosol sensors and lidars (via aerosol backscatter). The observations showed evidence of large-scale/synoptic transience as well as local-scale upslope and downslope flows, along-axis valley flows, recirculation eddies on leeward slopes, and periods of strong shear and veer aloft. The release days were classified as either synoptically-driven or locally-driven, and a single case day is presented in detail for each. Synoptically-forced days show relatively narrow smoke plumes traveling down the valley from north to south (with the predominant wind direction), with little deviation in transport direction regardless of the elevation or ground locations of the smoke releases, except near the presence of leeside recirculation eddies. Locally-forced days exhibit a wider range of plume behavior due to the combination of thermally-induced valley and slope flows, which are often flowing in different cardinal directions, and wind shear found aloft at higher altitudes and elevations. We saw evidence of smoke lofting on top of the mesas due to strong upslope flows on these days. A major finding of this experiment was the effectiveness of scanning lidars to measure 2-dimensional plume transport out to a 2–3 km distance; much farther than could be visibly observed. METEX21 was the first of three planned tracer experiments at NNSS, and future experiments will incorporate multiple tracers to improve individual plume identification so that finer resolution flow details can be attained from these measurements, as well as deploy a larger suite of meteorological instrumentation, including more temperature profiling data.

Terrain-induced flow acceleration is presented for the summertime, peak power season at Lawrence Livermore National Laboratory’s Site 300 for the Hill Flow Study (HilFlowS). HilFlowS, designed as an adjunct field campaign to the Department of Energy’s Second Wind Forecasting Improvement Project (WFIP2), provides wind profile observations at a second location in complex terrain for validating numerical atmospheric model simulations and for better understanding flow behavior over hills for wind power generation. One unique feature of HilFlowS was the inclusion of an undergraduate university student who helped plan and execute the experiment as well as analyze wind data from two remote sensing laser detection and ranging (lidar) instruments deployed along parallel ridgelines. HilFlowS examines the trend of building higher into the atmosphere for the purpose of increasing wind turbine power production and evaluates the wind resource in the Altamont Pass Region of Northern California for a set of wind turbines of differing hub-heights and rotor-disk diameters found in the area. The wind profiles show strongly channeled onshore flow above both hills, enhanced by strong subsidence aloft, which produces a wind maximum (Umax) around z = 10 m and strong negative shear throughout all of the evaluated rotor-disks for much of the summer wind season. Under these conditions, shear becomes more negative with increasing hub-height and increasing rotor-disk size. Rotor-disk equivalent wind speed (Uequiv), a measure of the average wind speed across the entire rotor-disk, is compared to hub-height, rotor length, and rated capacity factor for the set of turbines. Uequiv is most closely related to turbine hub-height and is negatively correlated given the low altitude of Umax. Based on these results, building the largest capacity, large rotor-disk wind turbine at the lowest possible hub-height appears to provide turbines in the Altamont with a fast, near-surface, onshore wind resource during the peak power season.

Predicting the response of wind farms to changing flow conditions is necessary for optimal design and operation. In this work, simulation and analysis of a frontal passage through a utility scale wind farm is achieved for the first time using a seamless multi-scale modeling approach. A generalized actuator disk (GAD) wind turbine model is used to represent turbine–flow interaction, and results are compared to novel radar observations during the frontal passage. The Weather Research and Forecasting (WRF) model is employed with a nested grid setup that allows for coupling between multi-scale atmospheric conditions and turbine response. Starting with mesoscale forcing, the atmosphere is dynamically downscaled to the region of interest, where the interaction between turbulent flows and individual wind turbines is simulated with 10 m grid spacing. Several improvements are made to the GAD model to mimic realistic turbine operation, including a yawing capability and a power output calculation. Ultimately, the model is able to capture both the dynamics of the frontal passage and the turbine response; predictions show good agreement with observed background velocity, turbine wake structure, and power output after accounting for a phase shift in the mesoscale forcing. This study demonstrates the utility of the WRF-GAD model framework for simulating wind farm performance under complex atmospheric conditions.

The Weather Research and Forecasting (WRF) model is used to investigate choice of land surface model (LSM) on the near surface wind profile, including heights reached by multi-megawatt (MW) wind turbines. Simulations of wind profiles and surface energy fluxes were made using five LSMs of varying degrees of sophistication in dealing with soil–plant–atmosphere feedbacks for the Department of Energy (DOE) Southern Great Plains (SGP) Atmospheric Radiation Measurement Program (ARM) Central Facility in Oklahoma, USA. Surface flux and wind profile measurements were available for validation. WRF was run for three, two-week periods covering varying canopy and meteorological conditions. The LSMs predicted a wide range of energy flux and wind shear magnitudes even during the cool autumn period when we expected less variability. Simulations of energy fluxes varied in accuracy by model sophistication, whereby LSMs with very simple or no soil–plant–atmosphere feedbacks were the least accurate; however, the most complex models did not consistently produce more accurate results. Errors in wind shear were also sensitive to LSM choice and were partially related to energy flux accuracy. The variability of LSM performance was relatively high suggesting that LSM representation of energy fluxes in WRF remains a large source of model uncertainty for simulating wind turbine inflow conditions.