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To characterize the effects of subgrid surface heterogeneity, the blending-height concept has been developed as a coupling strategy for surface parameterization schemes used in numerical weather prediction models. Previous modeling studies have tested this concept using stationary conditions with one-dimensional strips of surface roughness. Here, large-eddy simulations are used to examine the response of the blending height and effective surface roughness to tiled land-cover heterogeneity, or a two-dimensional chessboard pattern of alternating high and low vegetation given a diurnal cycle of solar irradiance in subarctic conditions. In each experiment, the length scale of the roughness elements is increased while the total domain fraction of each vegetation type is kept constant. The effective surface roughness was found to decrease with increasing length scale of surface cover heterogeneity, which is shown to have a significant impact on estimated wind turbine power calculated from logarithmic wind profiles. In stable conditions, the blending height in cases with large heterogeneity length scales was found to exist well above the surface layer. Because the behavior of the blending height has implications for coupled models, a simple model for the blending height as a function of heterogeneity length scale is introduced.

We present a new algorithm for the estimation of plant area density (PAD) profiles and plant area index (PAI) for forested areas based on data from airborne lidar. The new element in the algorithm is to scale and average returned lidar intensities for each lidar pulse, whereas other methods either do not use the intensity information at all, only use average intensity values or do not scale the intensity information, which can cause problems for heterogeneous vegetation. We compare the performance of the new and three previously published algorithms over two contrasting types of forest: a boreal coniferous forest with a relatively open structure and a dense beech forest. For the beech forest site, both summer (full leaf) and winter (bare trees) scans are analyzed, thereby testing the algorithm over a wide spectrum of PAIs. Whereas all tested algorithms give qualitatively similar results, absolute differences are large (up to 400 % for the average PAI at one site). A comparison with ground-based estimates shows that the new algorithm performs well for the tested sites, and further and more importantly – it never produces clearly dubious results. Specific weak points for estimation of PAD from airborne lidar data are addressed; the influence of ground reflections and the effect of small-scale heterogeneity, and we show how the effect of these points is minimized using the new algorithm. We further show that low-resolution gridding of PAD will lead to a negative bias in the resulting estimate according to Jensen’s inequality for concave functions, and that the severity of this bias is method-dependent. As a result, PAI magnitude as well as heterogeneity scales should be carefully considered when setting the resolution for PAD gridding of airborne lidar scans.

Wind profiles with a negative gradient are frequently occurring over the Baltic Sea and are important to take into consideration for offshore wind power as they affect not only the power production, but also the loads on the structure and the behavior of the wake behind the turbine. In this study, we classified non-normal profiles as wind profiles having negative shear in at least one part of the profile between 28 and 300 m: low-level jets (with a local wind maximum in the profile), profiles with a local minimum, and negative profiles. Using observations spanning over 3 years, we show that the non-normal wind profiles are common over the Baltic Sea in late spring and summer, with a peak of 40 % relative occurrence in May. Negative profiles (in the 28–300 m layer) were mostly occurring during unstable conditions, in contrast to low-level jets that primarily occurred in stable stratification. There were indications that the the zone with strong shear during low-level jets could cause a relative suppression of the variance for large turbulent eddies compared to the peak of the velocity spectra, in the layer below the jet core. Swell conditions were found to be favourable for the occurrence of negative profiles and profiles with a local minimum, as the waves fed energy into the surface layer, resulting in an increase of the wind speed from below.

Non-idealized wind profiles frequently occur over the Baltic Sea and are important to take into consideration for offshore wind power, as they affect not only the power production but also the loads on the structure and the behavior of the wake behind the turbine. In this observational study, we classified non-idealized profiles as the following wind profiles having negative shear in at least one part of the lidar wind profile between 28 and 300 m: low-level jets (with a local wind maximum in the profile), profiles with a local minimum and negative profiles. Using observations spanning over 3 years, we show that these non-idealized profiles are common over the Baltic Sea in late spring and summer, with a peak of 40 % relative occurrence in May. Negative profiles (in the 28–300 m layer) mostly occurred during unstable conditions, in contrast to low-level jets that primarily occurred in stable stratification. There were indications that the strong shear zone of low-level jets could cause a relative suppression of the variance for large turbulent eddies compared to the peak of the velocity spectra, in the layer below the jet core. Swell conditions were found to be favorable for the occurrence of negative profiles and profiles with a local minimum, as the waves fed energy into the surface layer, resulting in an increase in the wind speed from below.

In this work a new step in understanding the wind turbine (WT) wake behavior on forested areas is made. For this analysis, a pair of real scale WTs located on a site with moderately complex terrain and heterogeneous forest is simulated using Large Eddy Simulation (LES). This simulation is compared with met mast and power output measurements of two WTs in Ryningsnas, Sweden, considering near neutral stratification in the atmospheric boundary layer (ABL). Three validation steps are followed; first, the undisturbed wind profile is compared with met mast data and another similar LES code. Then, the wake for each WT wake impacting on the met mast at different directions is addressed. A feature of this pair of WTs is that these have different hub heights, but the same rated power and rotor diameter, which helps provide insight into how the tip clearance over the forest affects the operation and wake characteristics. Finally, power output deficits when the WTs are operating in each others wakes are compared to observed power deficits. For these simulations SOWFA, the Open FOAM project for wind farms simulation in ABL, is used. In this code, three new additions are made; the forest model, the mesh modification for complex terrain and the representation of the WT using an actuator disc model with local force adaptation for wind farm flows. The simulation results show a good performance on quantitatively and qualitatively capturing the velocity in the wake, but for TKE the simulation underestimates the magnitude, and fails to match the measured structure of the wake for one of two WTs. The power deficit on the impacted WTs is well captured, despite the complexity related to turbines with different hub heights. This study makes one of the first steps on validating LES simulations for wind farms in forest.

In-cloud ice mass accretion on wind turbines is a common challenge that is faced by energy companies operating in cold climates. On-shore wind farms in Scandinavia are often located in regions near patches of forest, the heterogeneity length scales of which are often less than the resolution of many numerical weather prediction (NWP) models. The representation of these forests—including the cloud water response to surface roughness and albedo effects that are related to them—must therefore be parameterized in NWP models used as meteorological input in ice prediction systems, resulting in an uncertainty that is poorly understood and, to the present date, not quantified. The sensitivity of ice accretion forecasts to the subgrid representation of forests is examined in this study. A single column version of the HARMONIE-AROME three-dimensional (3D) NWP model is used to determine the sensitivity of the forecast of ice accretion on wind turbines to the subgrid forest fraction. Single column simulations of a variety of icing cases at a location in northern Sweden were examined in order to investigate the impact of vegetation cover on ice accretion in varying levels of solar insolation and wind magnitudes. In mid-winter cases, the wind speed response to surface roughness was the primary driver of the vegetation effect on ice accretion. In autumn cases, the cloud water response to surface albedo effects plays a secondary role in the impact of in-cloud ice accretion, with the wind response to surface roughness remaining the primary driver for the surface vegetation impact on icing. Two different surface boundary layer (SBL) forest canopy subgrid parameterizations were tested in this study that feature different methods for calculating near-surface profiles of wind, temperature, and moisture, with the ice mass accretion again following the wind response to surface vegetation between both of these schemes.

With an increasing interest in offshore wind energy, focus has been directed towards large semi-enclosed basins such as the Baltic Sea as potential sites to set up wind turbines. The meteorology of this inland sea in particular is strongly affected by the surrounding land, creating mesoscale conditions that are important to take into consideration when planning for new wind farms. This paper presents a comparison between data from four state-of-the-art reanalyses (MERRA2, ERA5, UERRA, NEWA) and observations from LiDAR. The comparison is made for four sites in the Baltic Sea with wind profiles up to 300 m. The findings provide insight into the accuracy of reanalyses for wind resource assessment. In general, the reanalyses underestimate the average wind speed. The average shear is too low in NEWA, while ERA5 and UERRA predominantly overestimate the shear. MERRA2 suffers from insufficient vertical resolution, which limits its usefulness in evaluating the wind profile. It is also shown that low-level jets, a very frequent mesoscale phenomenon in the Baltic Sea during late spring, can appear in a wide range of wind speeds. The observed frequency of low-level jets is best captured by UERRA. In terms of general wind characteristics, ERA5, UERRA, and NEWA are similar, and the best choice depends on the application.

In-cloud ice mass accretion on wind turbines is a common challenge faced by energy companies operating in cold climates. On-shore wind farms in Scandinavia are often located in regions near patches of forest, the heterogeneity length scales of which are often less than the resolution of many numerical weather prediction (NWP) models. The representation of these forests--including the cloud water response to surface roughness and albedo effects related to them--must therefore be parameterized in NWP models used as meteorological input in ice prediction systems, resulting in an uncertainty that is poorly understood and to present date not quantified. The sensitivity of ice accretion forecasts to the subgrid representation of forests is examined in this study. A single column version of the HARMONIE-AROME 3D NWP model is used to determine the sensitivity of the forecast of ice accretion on wind turbines to the subgrid forest fraction. Single column simulations of a variety of icing cases at a location in northern Sweden were examined in order to investigate the impact of vegetation cover on ice accretion in varying levels of solar insulation and wind magnitudes. In mid-winter cases, the wind speed response to surface roughness was the primary driver of the vegetation effect on ice accretion. In early season cases, the cloud water response to surface albedo effects plays a secondary role in the impact of in-cloud ice accretion, with the wind response to surface roughness remaining the primary driver for the surface vegetation impact on icing. Two different surface boundary layer (SBL) forest canopy subgrid parameterizations were tested in this study that feature different methods for calculating near-surface profiles of wind, temperature, and moisture, with the ice mass accretion again following the wind response to surface vegetation between both of these schemes.

The New European Wind Atlas (NEWA), the largest European project on wind resource assessment technology, has developed mesoscale-to-microscale wind atlas and site assessment methodologies alongside a validation strategy that leverages data from large field experiments as well as wind resource campaigns from industry through a formal verification and validation process. A probabilistic wind atlas approach, based on a multi-physics ensemble, provides means to quantify the uncertainty associated to the mesoscale configuration. Offline meso-micro coupling has been adopted to provide a modular approach for microscale models of different fidelities to share common mesoscale input data. An opensource model chain based on WRF and OpenFOAM codes has been released as reference for future model development and validation activities in connection to wind assessment best practices and standards.

A conically scanning, continuous-wave LIDAR is placed on an island in the central Baltic Sea with large open-water fetch, providing wind and turbulence profiles up to 300 m height. LIDAR and Weather Research and Forecasting (WRF) profiles from one year are used to characterize the marine boundary layer, at the same time performing an evaluation of the WRF model against LIDAR measurements with a focus on low-level jet representation. A good agreement is found between the average wind speed profile in WRF and LIDAR, with the largest bias occurring during stable conditions. The LLJ frequency is highest in May with frequency of occurrence ranging between 18% and 27% depending on the method of detection. Most of the LLJs occur during nighttime, indicating that most of them do not have local origin. For cases with simultaneous LLJs in both data sets the WRF agrees well with the LIDAR. In many cases, however, the LLJ is misplaced in time or space in the WRF simulations compared to the LIDAR. This shows that models still must be improved to capture mesoscale effects in the coastal zone.

Presentation at the NEWA Final Workshop in Bilbao. TheRyningsnäs atmospheric boundary-layer experiment in a Swedish forested landscape is used to set up a benchmark for wind energy flow models to simulate the flow above a forest canopy that is characterized using aerial laser scans. The footprint characteristics of the canopy are visible in the profiles. The benchmark includes results from RANS and LES models showing good consistency in the mean velocity profiles and less agreement in TKE profiles.&nbsp

The aim of the present work is to obtain a better understanding of how to model the thermally stratified wind field over a forest during full diurnal cycles. The setup of the study assumes a horizontally homogeneous forest, with the objective of finding a simple and efficient way to model the canopy flow using time-dependent input data, obtained from measurements and mesoscale simulations. With this, new insights can be gained for future microscale modelling of complex forested terrains using mesoscale input data. In terrain without forest a diurnal cycle is commonly simulated by imposing time-dependent ground temperature. However, the presence of forests partially isolates the temperature at ground level from the flow above the canopy, making this common approach ineffective. This work proposes imposing the time-dependent net radiation at the forest canopy top to drive the thermal stratification changes along the diurnal cycle. To this end, several full days of simulation are driven by prescribing the net radiative heat flux balance measured on top of the canopy, together with a geostrophic pressure gradient. The advantage of the method is its simplicity and that the input data can be easily obtained from mesoscale modelling. When compared to the observations at the Swedish site Ryningsnas, the new method dramatically improves estimations of wind speed, wind direction and turbulent kinetic energy compared to simulations that only assume neutral stratification. Out of the variables studied, temperature and turbulent heat flux profiles were the ones that qualitatively followed the measurements the best, while wind speed and turbulent kinetic energy showed a larger disagreement.

The capability of a model based on Large-Eddy Simulations to reproduce turbulence measurements over a forest of heterogeneous density is assessed. Measurements are obtained from an experimental campaign with a continuous wave lidar mounted on the nacelle of a wind turbine (not considered in this work) that scans over a cone in the upstream direction. The measurements are then compared with the results of the LES of the atmospheric boundary layer in neutral stability conditions. The model comprises a full description of the forest over a large area upstream of the lidar by using plant area density data obtained with airborne laser scans, which also provides the terrain elevation. Although the relatively restricted mesh refinement of the LES leads to a limited representation of turbulence towards higher frequencies, comparisons with the measurements show that the model is capable of reproducing the turbulence levels and spatial coherence in the hypothetical rotor plane. Results permit to conclude that the LES-based model is a suitable tool to identify and predict the microscale effects that terrain features have in the wind resource for sites of high complexity. This work exemplifies the challenges associated to the process and interpretation of data from the employed lidar and its setup, for which a filtering technique potentially useful in future studies is presented.

This study presents an evaluation of wind field simulations, in neutral atmospheric conditions, above a heterogeneous forest. The calculations were performed with Large-Eddy Simulation (LES) code OpenFOAM, with explicit modelling of the forest through drag coefficient and forest density. The findings indicate that a large modelling domain is needed in order to reproduce the measurements in different wind directions, since the effect of far upwind forest characteristics influence the wind and turbulence profiles. It is further shown that even though the low resolution of the LES simulations lead to slightly misrepresented single point turbulence characteristics, two point turbulence characteristics are well predicted due to spatial filtering of the small scales.

This article describes a study where modellers were challenged to compute the wind at aforested site with moderately complex topography. The target was to match the measured windprofile at one exact location for three directions. The input to the modellers consisted of detailedinformation of forest densities and ground height derived from Airborne Laser Scans (ALS). Allparticipating models except two used the full detailed ground and forest information to modelthe forest which is considered a significant progress. The ALS based data resulted in reasonableagreement of the wind profile and turbulence magnitude. The best performance was found tobe that of LES using a very large domain. For the RANS type of models the constants in theturbulence closure was shown to be of great significance for the turbulence level, but of muchless importance for the wind speed profile. Overall, the article gives an overview of how welldifferent types of models are able to capture the flow physics at a moderate complex forestedsite.

Applying erroneous roughness lengths can have a large impact on the estimated performance of wind turbines, particularly in forested areas. In this study, a new method called the Objective Roughness Approach (ORA), which converts tree height maps created using airborne lidar scans to roughness maps suitable for wind modeling, is evaluated via cross-predictions between different anemometers at a complex forested site with seven tall meteorological masts using the Wind Atlas Analysis and Application program (WAsP). The cross-predictions were made using ORA maps created at four spatial resolutions and from four freely available roughness maps based on land-use classifications. The validation showed that the use of ORA maps resulted in a closer agreement with observational data for all investigated resolutions compared to the land-use maps. Further, when using the ORA maps, the risk of making large errors (25 %) in predicted power density was reduced by 40–50 % compared to satellite based products with the same resolution. The results could be further improved for high-resolution ORA maps by adding the displacement height. The improvement when using the ORA maps came down to two factors, first they had a higher roughness length for forests, which was confirmed to by increasing the forest roughness value of the land-use based maps to the value of the ORA map, and second, due to the higher resolution of the ORA data, since the ORA maps with the highest resolution had the largest reduction in mean absolute errors.

This article describes a study in which modellers were challenged to compute the wind field at a forested site with moderately complex topography. The task was to model the wind field in stationary conditions with neutral stratification by using the wind velocity measured at 100 m at a metmast as the only reference. Detailed maps of terrain elevation and forest densities were provided as the only inputs, derived from airborne laser scans (ALSs) with a resolution of 10 m × 10 m covering an area of 50 km × 50 km, that closely match the actual forest and elevation of the site. The participants were free to apply their best practices for the simulation to decide the size of the domain, the value of the geostrophic wind, and every other modelling parameter. The comparison of the results with the measurements is shown for the vertical profiles of wind speed, shear, wind direction, and turbulent kinetic energy. The ALS-based data resulted in reasonable agreement of the wind profile and turbulence magnitude. The best performance was found to be that of large-eddy simulations using a very large domain. For the Reynolds-averaged Navier–Stokes type of models, the constants in the turbulence closure were shown to have a great influence on the yielded turbulence level, but were of much less importance for the wind speed profile. Of the variety of closure constants used by the participating modellers, the closure constants from Sogachev and Panferov (2006) proved to agree best with the measurements. Particularly the use of Cμ≈0.03 in the k–ε model obtained better agreement with turbulence level measurements. All except two participating models used the full detailed ground and forest information to model the forest, which is considered significant progress compared to previous conventional approaches. Overall, the article gives an overview of how well different types of models are able to capture the flow physics at a moderately complex forested site.

A solution of the inviscid rapid distortion equations for a stratified flow with homogeneous shear is proposed, extending the work of Hanazaki & Hunt (J. Fluid Mech., vol. 507, 2004, pp. 1–42) to the two horizontal velocity components. The analytical solution allows for the determination of the spectral tensor evolution at any given time starting from a known initial condition. By following the same approach as that adopted by Mann (J. Fluid Mech., vol. 273, 1994, pp. 141–168), a model for the spectral velocity tensor in the atmospheric boundary layer is obtained, where the spectral tensor, assumed to be isotropic at the initial time, evolves until the breakup time where the spectral tensor is supposed to achieve its final state observed in the boundary layer. The model predictions are compared with atmospheric measurements obtained over a forested area, giving the opportunity to calibrate the model parameters, and further validation is provided by additional low-roughness data. Characteristic values of the model coefficients and their dependence on the Richardson number are proposed and discussed.

An analysis and interpretation of measurements from a 138-m tall tower located in a forested landscape is presented. Measurement errors and statistical uncertainties are carefully evaluated to ensu ...

The New European Wind Atlas project will create a freely accessible wind atlas covering Europe and Turkey, develop the model chain to create the atlas and perform a series of experiments on flow in many different kinds of complex terrain to validate the models. This paper describes the experiments of which some are nearly completed while others are in the planning stage. All experiments focus on the flow properties that are relevant for wind turbines, so the main focus is the mean flow and the turbulence at heights between 40 and 300 m. Also extreme winds, wind shear and veer, and diurnal and seasonal variations of the wind are of interest. Common to all the experiments is the use of Doppler lidar systems to supplement and in some cases replace completely meteorological towers. Many of the lidars will be equipped with scan heads that will allow for arbitrary scan patterns by several synchronized systems. Two pilot experiments, one in Portugal and one in Germany, show the value of using multiple synchronized, scanning lidar, both in terms of the accuracy of the measurements and the atmospheric physical processes that can be studied. The experimental data will be used for validation of atmospheric flow models and will by the end of the project be freely available. This article is part of the themed issue ‘Wind energy in complex terrains’.

Calculation of momentum flux using Monin–Obukhov similarity theory over forested areas is well known to underestimate the flux. Several suggestions of corrections to the standard flux-profile expre ...

A new model to determine the spectral velocity tensor in a stably stratified flow is proposed. This model is complementary to the Mann model as it solves the stratified inviscid Rapid Distortion Theory equations analytically, allowing for the determination of the single and two-point velocity spectra as well as the temperature-velocity cross-spectra. The model has been here calibrated and validated against field measurements conducted over a forested area with measurements up to 140 m, therefore covering a region of interest for wind-energy applications.

Meso-scale models are increasingly used for estimating wind resources for wind turbine siting. In this study, we investigate how the Weather Research and Forecasting (WRF) model performs using standard model settings in two different planetary boundary layer schemes for a forested landscape and how this performance is changed when enhancing the roughness by a factor four in one of the schemes. The model simulations were evaluated using data from a 138 m tall mast in southeastern Sweden, where an experiment with six sonic anemometers and standard meteorological instrumentation was performed 2010-2012. The land cover around the mast is dominated by forest and for the most common wind direction, the forest extends more than 200 km from the mast. The two low-roughness simulations showed differences both in terms of estimated wind resource and wind shear. The simulation with enhanced roughness results in an improved correlation with measured data for near-neutral situations in the observed height range, whereas the correlation is deteriorated relative to the standard setup for stable atmospheric stratifications for heights above approximately 80 m. The inclusion of the displacement height in the post-processing of the results is also discussed.

This presentation was part of theSP3 WORKSHOP on Science of air-sea interaction new challenges for floating wind.