Abstract Accurate measurements of absolute wind direction are essential for maximising wind farm production through strategies such as sector management or wake steering. This study aims to evaluate how accurately a nacelle-mounted sonic anemometer and a forward-looking nacelle-mounted wind lidar can measure wind direction and wind speed, and how this accuracy is affected by intentional yaw misalignment. Ten minute measurements from nacelle sensors are analysed and compared to reference measurements on an upstream met mast, in a flat-terrain site. Calibration and mounting errors are identified, the effect of intentional yaw misalignment and atmospheric stability is assessed, and the effect of land heterogeneity is evaluated using a high-resolution Reynolds Averaged Navier-Stokes simulation. Even in a simple, highly calibrated site, the yaw misalignment bias of nacelle anemometers ranges from 1.5° fixed-offset to up to 6° due to intentional yaw misalignment and varying atmospheric conditions, which may impact the effectiveness of wind farm control strategies.

Abstract We present an investigation on instrument performance regarding mean wind speed and precipitation during a campaign over three winter months. A sodar profiler was run side-by-side with a lidar profiler at a site with three reference precipitation instruments. Constraints on sound volumes caused us to measure with different settings for the sodar, ranging from 4 to 40% of the maximum beep volume setting. Focusing on the 100 m wind speed, the sodar measured well in relation to the lidar, with proportionality close to one for all sound settings. R 2 values were above 0.99 for sound volumes over 20% and 0.96 for the 4% sound volume. With regards to data availability, both the lidar and sodar showed periods of near 100% data recovery during rough weather. However, the lidar was strongly dependent on a functioning window wiper (which broke during rough weather in this campaign), and the sodar was dependent on a relatively loud (≥ 40%) sound setting. Additionally, we tested whether a simple algorithm could be used to extract a rain intensity signal from the sodar spectra. For the two week long period of 40% sound setting, the resulting derived cumulative rain amount from the sodar lies within the envelope of the cumulative rain amounts measured by the three reference precipitation sensors.

The accurate quantification of the wind loading on trees is crucial for estimating the risk of tree damage. Here, we present an experimental quantification of the wind force on a rural, open-grown, deciduous tree. We first demonstrate that the amplitude and direction of the two-dimensional force vector can be estimated using two strain gauges mounted on the bottom of the stem. Secondly, we show that the dynamic response of the tree along the mean wind direction shows differences from that in the transverse direction, indicating the importance of studying both force components. Subsequently, the analysis is focused on the mean and maximum wind force over a wide wind speed range. During winter, both the mean and maximum force is described by a quadratic wind speed dependence, whereas during summer, an adjustment is needed to account for the reconfiguration of the leaves. This adjustment is parameterized using the same functional relationship for the mean and maximum force. Overall, in the wind speed range between 4-11 ms-1 the maximum wind load was 49%-66% and 52%-79% larger than the mean, during the summer and winter, respectively.

Airborne LiDARs can provide updated and highly accurate information of the 3D urban layer. This presentation focuses on transforming such information into boundary conditions for urban flow models. When addressing buildings, we use a method called City3D [1], which outputs a watertight geometrical model at a specified level of detail (LoD).This resulting model is then utilized in the computational fluid dynamics (CFD) solver EllipSys [2]. We demonstrate how a novel implementation of the immersed boundary method (IBM) [3] simulates the wind flow and dispersion around the building. Additionally, we explore how different LoDinfluence the simulation results. The LiDAR data can also be used to model the drag force of trees. We demonstrate this process based on recent observations of a real tree. Finally, we discuss the relative importance of trees and buildings in an urban modelling context, highlighting the significance of including more details in the 3D urban layer. References[1] Jin Huang, Jantien Stoter, Ravi Peters, and Liangliang Nan. City3d: Large-scale building reconstruction from airborne lidar point clouds. Remote Sensing, 14(9), 2022.[2] Jess A. Michelsen. Basis3D - a Platform for Development of Multiblock PDE Solvers: - release, volume AFM 92-05. Technical University of Denmark, 1992.[3] Niels Troldborg, Niels N. Sørensen, and Frederik Zahle. Immersed boundary method for the incompressible reynolds averaged navier–stokes equations. Computers Fluids, 237:105340, 2022.

Enhancing our understanding of the structural response of trees exposed to wind loading is important, since the knowledge of their aerodynamic behaviour is necessary for a realistic risk assessment of tree damage during extreme wind conditions. Here, we first present an analytical model of the aerodynamic admittance function that relates the turbulence fluctuations of the wind at a single point to their spatial average over the crown's frontal area. The latter is responsible for the wind-induced bending moments at the base of a tree's stem. We employ the aerodynamic admittance function to model the dynamic structural response of an open-grown oak tree. The analysis is performed along two axes to express both the longitudinal and transverse response with respect to the mean wind direction. The resulting predictions are compared with strain gauge observations taken at the lower part of the stem. The presented framework shows that the spatial averaging over the crown's frontal area has a stronger effect on the tree's movements in the streamwise wind direction compared to the spanwise direction. Further, the aerodynamic damping is also stronger in the streamwise direction and generally correlates positively with the inflow wind speed.

Trees have a strong effect on the local wind climate. To better understand their impact, an accurate and detailed reconstruction of botanical trees into digital twins from terrestrial LiDAR scan point clouds is important. However, capturing the complex, multi-scale nature of tree structures poses significant challenges. Issues such as gaps in the model due to occlusion in the point cloud data and inaccuracies in branch thickness estimations — especially for smaller branches — are prevalent limitations. Most advanced reconstruction methods today, such as TreeQSM (Raumonen et al., 2013), have been primarily designed for forestry applications, such as volume and biomass estimation. However, numerical flow simulations pose additional requirements including the need for a closed and continuous surface.This study introduces a different approach, building upon the work of Bærenzten et al., 2023, using tools from the field of computer graphics. The proposed method initially creates a graph from the point cloud by connecting nearby points. Subsequently, a highly detailed skeleton of the tree is generated using the so-called local separators approach (Bærenzten et al., 2021). Local separators are defined as collections of vertices that are contained within a sub-graph of the original graph. The removal of a local separator splits the sub-graph into multiple smaller sub-graphs. The branch diameters are subsequently determined using a hybrid method that blends data-driven estimates derived from the point cloud data with the Da Vinci rule for trees, which defines a relationship between the diameters of a mother branch and its daughter branches. Additionally, species-specific data obtained from direct diameter measurements is incorporated in the estimation process. The tree’s surface is then reconstructed by first generating an implicit representation from which a closed mesh is extracted as an iso-surface.Through a parameter study, the two main parameters for the generation of the skeleton, as well as the two main parameters influencing the branch thickness estimation, were studied in detail. The algorithm effectively handles occlusion in the point cloud, producing fully connected branching structures. The combined approach notably enhances the branch thickness estimation compared to using only one approach. We demonstrate the robustness of the method by applying it to three trees of very different dimensions, complexities, and point cloud characteristics and outline how the finally reconstructed tree will be used in atmospheric flow simulations. ReferencesRaumonen, P., Kaasalainen, M., Åkerblom, M., Kaasalainen, S., Kaartinen, H., Vastaranta, M., Holopainen, M., Disney, M., & Lewis, P. (2013). Fast Automatic Precision Tree Models from Terrestrial Laser Scanner Data. Remote Sensing, 5, 491-520. https://doi.org/10.3390/rs5020491Bærentzen, J. A., Villesen, I. B., & Dellwik, E. (2023). Reconstruction of a Botanical Tree from a 3D Point Cloud. In E. Christiani, M. Falcone, & S. Tozza (Eds.), Mathematical Methods for Objects Reconstruction: From 3D Vision to 3D Printing (Vol. 54, pp. 103-120). Springer. https://doi.org/10.1007/978-981-99-0776-2\_4Bærentzen, A., & Rotenberg, E. (2021). Skeletonization via Local Separators. ACM Transactions on Graphics, 40(5), Article 187. https://doi.org/10.1145/3459233

As wind turbines have grown in size, it has become ever more costly to make the necessary tower-based wind observations needed both for the pre-operation (siting) phase and for wind turbine operations. In response to this challenge, the wind energy scientific community has - over the last decades - focused on evaluating and improving ground-based remote-sensing technology. The development has often been done in close collaboration with the innovative companies dedicated to providing the new solutions for replacing the expensive meteorological towers to the market. The project EARS4WindEnergy, which started in March 2023, represents one such effort. The project is focused on a re-exploration of the sodar technology, which preceded the later focus on wind lidars. Here, we present a benchmarking of the AQ510 sodar equipped with new signal processing technology with tall-tower data focusing on the three “must-perform” criteria of accurate wind speed, accurate turbulence intensity and a reliable identification of erroneous data. The complementary aspects of data availability and robustness in relation to current wind lidars is also discussed. Most of the presented data are taken at the Østerild test site in Northern Denmark, where a 244m tall tower allows for accuracy quantification over most of the sodar’s measurement range.

Wind turbine blade erosion poses a significant challenge to the durability and performance of wind turbines. Modeling of rain erosion damage, considering atmospheric conditions, improves our understanding of the progression of leading-edge erosion on wind turbine blades. In this study, we investigate the impact of varying raindrop characteristics on rain erosion damage development. We analyse 2.5 years of data from a disdrometer, which measures the size and velocity of falling rain droplets, at Riso campus. Various post-processing methods of the disdrometer data are used for estimating representative droplet diameters and fall velocities for each rain event. We compare measured droplet fall velocities with theoretical terminal velocities, revealing a necessity for revising theoretical approaches to raindrop fall velocity for erosion damage modeling. The measured rain rates and representative fall velocities are used to calculate the liquid water content in the air. We introduce a bin-wise summation method for estimating the liquid water content, circumventing the need for representative droplet assumptions. As this method provides the most accurate input for the damage model, we benchmark the other post-processing methods against it and employ it to evaluate bias estimates of associated damage predictions. The largest bias (22%) in accumulated damage is found with an arithmetic mean droplet diameter approach and the smallest bias (-2%) with the median volume estimation method for damage model input. Furthermore, we demonstrate that, for a given rainfall volume, smaller droplets contribute to larger accumulated damage compared to larger droplets.

3D models are often acquired using optical methods such as LiDAR, structured light, or automated photogrammetry. These methods produce point clouds, and the typical downstream processing pipeline consists of registration of individually scanned point clouds followed by reconstruction of a triangle mesh from the combined point cloud. In this paper we consider a specific challenge that might prevent this pipeline from producing meshes suitable for later applications. The challenge concerns reconstruction of 3D models with thin tubular features, here exemplified by a tree with a very complex crown structure, where the radii of some branches are on the same order as the sample distance. In such cases, traditional surface reconstruction methods perform poorly. We discuss how a surface can still be reconstructed from this type of data. Our procedure begins by constructing a skeleton of the object from a graph whose vertices are the input points, a surface representation is then created from the skeleton, and, finally, a triangle mesh is generated from the surface representation. We demonstrated the efficacy of our method on a tree acquired using ground-based LiDAR.

We present a flexible solution for the representation of forest edges in windtunnel experiments that can be easily adapted to match observed wind statistics from fullscale field experiments. The solution is based on an incremental approach in which layers of coarse mesh are wrapped over a matrix of cylinders. The mesh layers increase the drag of the model canopy, while they also realistically simulate the strong damping of turbulent fluctuations inside the canopy. In addition to adding layers of mesh, the original 90 degree angle of the forest edge is tapered such that it more closely resembles the profile of the forest edge from a field experiment. The high vertical resolution of the wind-tunnel observations for the calibrated forest model shows both more detail and confirms previous findings from the field experiment. For example, in the region just above the canopy, where the slower wind flow inside the canopy mixes with the faster flow aloft, the streamwise skewness shows a strong zigzag pattern as a function of height and an increase in the streamwise velocity standard deviation.

Solitary trees are natural land surface elements found in almost all climates, yet their influence on the surrounding airflow is poorly known. Here we use state-of-the-art, laser-based, remote sensing instruments to study the turbulent wind field in the near-wake region of a mature, open-grown oak tree. Our measurements provide for the first time a full picture of the mixing layer of high turbulence that surrounds the mean wind speed deficit. In this layer, we investigate the validity of a two-dimensional vectorial relation derived from the eddy-viscosity hypothesis, a hypothesis commonly used in modelling the turbulence transport of momentum and scalars in the atmosphere. We find that the momentum fluxes of the streamwise wind component can be adequately predicted by the transverse gradient of the mean flow. Using the mixing-length hypothesis we find that for this tree the corresponding turbulence length scale in the mixing layer can be approximated by one height-independent value. Further, the laser-based scanning technology used here was able to accurately reveal three-dimensional turbulent and spatially varying atmospheric flows over a large plane without seeding or intruding the atmospheric flow. This capability points to a new and more exact way of exploring the complex earth–atmosphere interactions.

Leading edge erosion (LEE) of wind turbine blades causes decreased aerodynamic performance leading to lower power production and revenue and increased operations and maintenance costs. LEE is caused primarily by materials stresses when hydrometeors (rain and hail) impact on rotating blades. The kinetic energy transferred by these impacts is a function of the precipitation intensity, droplet size distributions (DSD), hydrometeor phase and the wind turbine rotational speed which in turn depends on the wind speed at hub-height. Hence, there is a need to better understand the hydrometeor properties and the joint probability distributions of precipitation and wind speeds at prospective and operating wind farms in order to quantify the potential for LEE and the financial efficacy of LEE mitigation measures. However, there are relatively few observational datasets of hydrometeor DSD available for such locations. Here, we analyze six observational datasets from spatially dispersed locations and compare them with existing literature and assumed DSD used in laboratory experiments of material fatigue. We show that the so-called Best DSD being recommended for use in whirling arm experiments does not represent the observational data. Neither does the Marshall Palmer approximation. We also use these data to derive and compare joint probability distributions of drivers of LEE; precipitation intensity (and phase) and wind speed. We further review and summarize observational metrologies for hydrometeor DSD, provide information regarding measurement uncertainty in the parameters of critical importance to kinetic energy transfer and closure of data sets from different instruments. A series of recommendations are made about research needed to evolve towards the required fidelity for a priori estimates of LEE potential.

Trees are important natural wind engineering elements in both the urban and the agricultural contexts, but their aerodynamic description has been limited by its focus on young, flexible trees. Here, we provide a reformulation of the classical drag equation, which is also suitable for mature and wind-adapted trees. The new formulation is based on results from a full-scale experiment with focus on a solitary oak tree, for which we determined all terms in the drag equation experimentally. We also present a new photographical method for the accurate quantification of the tree’s frontal area under highly variable outdoor lighting conditions. We used a database of images from a surveillance camera, from which a high-quality subset was automatically selected with machine learning algorithms. Compared to previous work on younger and smaller trees, the mature tree has a lower absolute value of the Vogel exponent, which indicates a relatively low degree of reconfiguration. The presented results underline the high efficiency of mature trees in reducing the momentum of the wind. The results can be used to quantify the effect of similar trees in wind simulations, and the new method for determining the frontal area can be applied in other tree measurement campaigns.

Sonic anemometers provide point observations of the three-dimensional velocity field at high sampling rates and are crucial instruments for understanding and quantifying the fluxes of momentum, energy and scalars between the atmosphere and Earth’s surface. Since the beginning of sonic anemometry 50 years ago, the characterization of flow distortion, i.e. how the instrument structure alters the flow, has been an ongoing research topic. Multi-path sonic anemometry provides a new opportunity to research and understand flow distortion on the vertical velocity component, since several positions in the small measurement volume can be measured simultaneously. In this work, we use data from a flat terrain measurement campaign in 2020, in which several sonic anemometers were mounted on 4m towers placed 4m apart. The analysis is focused on the Multipath Class-A sonic anemometer (Metek GmbH, Germany), which provides vertical velocity observations from three vertical paths 120 degrees and 0.1m apart. Vertical velocities are also calculated from several combinations of the tilted paths. We investigate how the vertical velocity component is altered depending on wind direction relative to different parts of the instrument structure. We demonstrate that by an optimal combination of the different paths, the vertical velocity variance and fluxes can be significantly enhanced. We also show spectra, and especially look at the high frequency end of the spectrum, where the relative behaviour of the velocity components is known from fundamental turbulence theory. Further, the relative importance of transducer shadowing and pressure-induced blockage effects is discussed.

Interactions between wind and trees control energy exchanges between the atmosphere and forest canopies. This energy exchange can lead to the widespread damage of trees, and wind is a key disturbance agent in many of the world's forests. However, most research on this topic has focused on conifer plantations, where risk management is economically important, rather than broadleaf forests, which dominate the forest carbon cycle. This study brings together tree motion time-series data to systematically evaluate the factors influencing tree responses to wind loading, including data from both broadleaf and coniferous trees in forests and open environments. We found that the two most descriptive features of tree motion were (a) the fundamental frequency, which is a measure of the speed at which a tree sways and is strongly related to tree height, and (b) the slope of the power spectrum, which is related to the efficiency of energy transfer from wind to trees. Intriguingly, the slope of the power spectrum was found to remain constant from medium to high wind speeds for all trees in this study. This suggests that, contrary to some predictions, damping or amplification mechanisms do not change dramatically at high wind speeds, and therefore wind damage risk is related, relatively simply, to wind speed. Conifers from forests were distinct from broadleaves in terms of their response to wind loading. Specifically, the fundamental frequency of forest conifers was related to their size according to the cantilever beam model (i.e. vertically distributed mass), whereas broadleaves were better approximated by the simple pendulum model (i.e. dominated by the crown). Forest conifers also had a steeper slope of the power spectrum. We interpret these finding as being strongly related to tree architecture; i.e. conifers generally have a simple shape due to their apical dominance, whereas broadleaves exhibit a much wider range of architectures with more dominant crowns.

We present numerical predictions and experimental observations of the drag force on the major branches of a model tree as well as the wind field in its wake. The tree model was mounted on a force sensor in a wind tunnel. The numerical simulations solved both the Reynolds Averaged Navier Stokes and detached eddy simulations, in combination with an immersed boundary model representation of the tree, while the measurements were obtained in the WindEEE Dome. Contrary to previous studies on trees or fractal structures, we find that the simulated forces on the tree skeleton were strongly dependent on the roughness of its surface. Upon setting a proper surface roughness, the simulations were capable of predicting both forces and wake fields, which were in good agreement with the observations both in terms of mean wind speed, mean turbulence and spectra. Furthermore, both simulations and observations showed that turbulence and mean wind speed were reduced for up to a distance of two tree heights downwind of the tree skeleton, underlining the efficiency of trees to remove momentum from a flow.

Trees are known to reduce the wind momentum efficiently. Yet, firm quantitative estimates of their contribution to the land surface drag have remained elusive, partly because trees have complex shapes that consist of elastic multi-scale elements. This structural complexity makes trees inherently difficult to scale for wind tunnel studies. Here, we test a new method for quantifying the drag force on a solitary mature tree in its natural environment. The method is based on the application of mass and momentum conservation over a control volume that encloses the tree. For this control volume, the drag force is estimated through the momentum deficit in the wake. For the characterisation of the heterogeneous and high-gradient wind field in the wake, spatially distributed measurements of the wind vector were acquired using three synchronously scanning wind lidar instruments in a vertical plane encompassing the wake. The resulting drag force estimate is compared to a reference measurement from a tree-mounted sensor at the base of the stem. We find that the drag force in both methods shows a dependence on the wind speed raised to an exponent of 1.8 and that the drag force, based on the momentum deficit method, is consistently underestimated by 1 %-10 %. Potential reasons for this bias are discussed in light of the accuracy of both methods. The relatively close agreement between the two methods indicates that scanning Doppler lidar measurements can be used to determine the drag force on complex objects in their natural environment, such as trees.

Toby D. Jackson, Sarab Sethi, Ebba Dellwik, Nikolas Angleou, Amanda Bunce, Tim van Emmerik, Marine Duperat, Jean-Claude Ruel, Axel Wellpott, Skip Van Bloem, Alexis Achim, Brian Kane, Dominick M. Ciruzzi, Steven P. Loheide II, Ken James, Daniel Burcham, John 5 Moore, Dirk Schindler, Sven Kolbe, Kilian Wiegmann, Mark Rudnicki, Victor J. Lieffers, John Selker, Andrew V. Gougherty, Tim Newson, Andrew Koeser , Jason Miesbauer, Roger Samelson, Jim Wagner, Anthony Ambrose, Andreas Detter, Steffen Rust, David Coomes, Barry Gardiner