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Wandering of tornado-like vortices consists in random oscillations of the vortex core from its time-averaged position, which complicates efforts to characterize vortex characteristics. A procedure is then necessary to retrieve characteristics of tornado-like vortices not affected by wandering smoothing effects. This study explores two procedures to correct wandering effects on Particle Image Velocimetry data obtained from a down-scaled model of the WindEEE Dome simulator. The first procedure re-centers the velocity data as a function of the instantaneous location of the vortex center. The second procedure treats the time-averaged vortex velocity field as the convolution of a bi-variate normal probability density function, which represents the distribution of vortex center locations over horizontal planes orthogonal to the vortex axis and the instantaneous tornado velocity field. Depending on swirl ratio and vortex height, wandering amplitude was generally from 5% to 9% of the updraft radius. The re-centering procedure was found to be more accurate than the deconvolution procedure. When applied to the turbulence statistics of the velocity field, the correction revealed that a higher level of turbulence at the center of low swirl tornadoes is a result of wandering. Also, the corrected shear stresses revealed a spiral pattern for cases of higher swirl. Wandering effects increases with reducing swirl ratio. For this experiment, swirl ratio is reduced from 0.96 down to 0.22 and errors on the vortex core radius as high as 50% and reduction of the maximum tangential velocity of 13% were observed.

The eXperimental Planetary boundary layer Instrumentation Assessment (XPIA) field campaign took place in March through May 2015 at the Boulder Atmospheric Observatory, utilizing its 300 m meteorological tower, instrumented with two sonic anemometers mounted on opposite sides of the tower at six heights. This allowed for at least one sonic anemometer at each level to be upstream of the tower at all times and for identification of the times when a sonic anemometer is in the wake of the tower frame. Other instrumentation, including profiling and scanning lidars aided in the identification of the tower wake. Here we compare pairs of sonic anemometers at the same heights to identify the range of directions that are affected by the tower for each of the opposing booms. The mean velocity and turbulent kinetic energy are used to quantify the wake impact on these first- and second-order wind measurements, showing up to a 50 % reduction in wind speed and an order of magnitude increase in turbulent kinetic energy. Comparisons of wind speeds from profiling and scanning lidars confirmed the extent of the tower wake, with the same reduction in wind speed observed in the tower wake, and a speed-up effect around the wake boundaries. Wind direction differences between pairs of sonic anemometers and between sonic anemometers and lidars can also be significant, as the flow is deflected by the tower structure. Comparisons of lengths of averaging intervals showed a decrease in wind speed deficit with longer averages, but the flow deflection remains constant over longer averages. Furthermore, asymmetry exists in the tower effects due to the geometry and placement of the booms on the triangular tower. An analysis of the percentage of observations in the wake that must be removed from 2 min mean wind speed and 20 min turbulent values showed that removing even small portions of the time interval due to wakes impacts these two quantities. However, a vast majority of intervals have no observations in the tower wake, so removing the full 2 or 20 min intervals does not diminish the XPIA dataset.

To assess current capabilities for measuring flow within the atmospheric boundary layer, including within wind farms, the U.S. Department of Energy sponsored the eXperimental Planetary boundary layer Instrumentation Assessment (XPIA) campaign at the Boulder Atmospheric Observatory (BAO) in spring 2015. Herein, we summarize the XPIA field experiment, highlight novel measurement approaches, and quantify uncertainties associated with these measurement methods. Line-of-sight velocities measured by scanning lidars and radars exhibit close agreement with tower measurements, despite differences in measurement volumes. Virtual towers of wind measurements, from multiple lidars or radars, also agree well with tower and profiling lidar measurements. Estimates of winds over volumes from scanning lidars and radars are in close agreement, enabling the assessment of spatial variability. Strengths of the radar systems used here include high scan rates, large domain coverage, and availability during most precipitation events, but they struggle at times to provide data during periods with limited atmospheric scatterers. In contrast, for the deployment geometry tested here, the lidars have slower scan rates and less range but provide more data during nonprecipitating atmospheric conditions. Microwave radiometers provide temperature profiles with approximately the same uncertainty as radio acoustic sounding systems (RASS). Using a motion platform, we assess motion-compensation algorithms for lidars to be mounted on offshore platforms. Finally, we highlight cases for validation of mesoscale or large-eddy simulations, providing information on accessing the archived dataset. We conclude that modern remote sensing systems provide a generational improvement in observational capabilities, enabling the resolution of finescale processes critical to understanding inhomogeneous boundary layer flows.

Accurate three-dimensional information of wind flow fields can be an important tool in not only visualizing complex flow but also understanding the underlying physical processes and improving flow modeling. However, a thorough analysis of the measurement uncertainties is required to properly interpret results. The XPIA (eXperimental Planetary boundary layer Instrumentation Assessment) field campaign conducted at the Boulder Atmospheric Observatory (BAO) in Erie, CO, from 2 March to 31 May 2015 brought together a large suite of in situ and remote sensing measurement platforms to evaluate complex flow measurement strategies. In this paper, measurement uncertainties for different single and multi-Doppler strategies using simple scan geometries (conical, vertical plane and staring) are investigated. The tradeoffs (such as time–space resolution vs. spatial coverage) among the different measurement techniques are evaluated using co-located measurements made near the BAO tower. Sensitivity of the single-/multi-Doppler measurement uncertainties to averaging period are investigated using the sonic anemometers installed on the BAO tower as the standard reference. Finally, the radiometer measurements are used to partition the measurement periods as a function of atmospheric stability to determine their effect on measurement uncertainty. It was found that with an increase in spatial coverage and measurement complexity, the uncertainty in the wind measurement also increased. For multi-Doppler techniques, the increase in uncertainty for temporally uncoordinated measurements is possibly due to requiring additional assumptions of stationarity along with horizontal homogeneity and less representative line-of-sight velocity statistics. It was also found that wind speed measurement uncertainty was lower during stable conditions compared to unstable conditions.

Accurate three-dimensional information of wind flow fields can be an important tool in not only visualizing complex flow, but also understanding the underlying physical processes and improving flow modeling. However, a thorough analysis of the measurement uncertainties is required to properly interpret results. The XPIA (eXperimental Planetary boundary layer Instrumentation Assessment) field campaign conducted at the Boulder Atmospheric Observatory (BAO) in Erie, CO from 2 March–31 May 2015 brought together a large suite of in-situ and remote sensing measurement platforms to evaluate complex flow measurement strategies. In this paper, measurement uncertainties for different single and multi-Doppler strategies are investigated. The tradeoffs (such as time/space resolution vs. spatial coverage) among the different measurement techniques are evaluated using co-located measurements made near the BAO tower. Sensitivity of the single/multi Doppler measurement uncertainties to averaging period are investigated using the sonic anemometers installed on the BAO tower as the standard reference. Finally, the radiometer measurements are used to partition the measurement periods as a function of atmospheric stability to determine their effect on measurement uncertainty. It was found that with increase in spatial coverage and measurement complexity, the uncertainty in the wind measurement also increased. For multi-Doppler techniques, the increase in uncertainty for temporally uncoordinated measurements is possibly due to requiring additional assumptions of stationarity and/or horizontal homogeneity. It was also found that wind speed measurement uncertainty was lower during stable conditions compared to unstable conditions.

The eXperimental Planetary boundary layer Instrumentation Assessment (XPIA) field campaign took place in March through May 2015 at the Boulder Atmospheric Observatory, utilizing its 300-meter meteorological tower, instrumented with two sonic anemometers mounted on opposite sides of the tower at six heights. This allowed for at least one sonic anemometer at each level to be upstream of the tower at all times, and for identification of the times when a sonic anemometer is in the wake of the tower frame. Other instrumentation, including profiling and scanning lidars aided in the identification of the tower wake. Here we compare pairs of sonic anemometers at the same heights to identify the range of directions that are affected by the tower for each of the opposing booms. The mean velocity and turbulent kinetic energy are used to quantify the wake impact on these first- and second-order wind measurements, showing up to a 50 % reduction in wind speed and an order of magnitude increase in turbulent kinetic energy. Comparisons of wind speeds from profiling and scanning lidars confirmed the extent of the tower wake, with the same reduction in wind speed observed in the tower wake, and a speed-up effect around the wake boundaries. Wind direction differences between pairs of sonic anemometers and between sonic anemometers and lidars can also be significant, as the flow is deflected by the tower structure. Comparisons of lengths of averaging intervals showed a decrease in wind speed deficit with longer averages, but the flow deflection remains constant over longer averages. Furthermore, asymmetry exists in the tower effects due to the geometry and placement of the booms on the triangular tower. An analysis of the percentage of observations in the wake that must be removed from 2-min mean wind speed and 20-min turbulent values showed that removing even small portions of the time interval due to wakes impacts these two quantities. However, a vast majority of intervals have no observations in the tower wake, so removing the full 2- or 20-min intervals does not diminish the XPIA dataset.

Vertical profiles of the 3D wind velocity are retrieved from triple range-height-indicator (RHI) scans performed with multiple simultaneous scanning Doppler wind lidars. This test is part of the eXperimental Planetary boundary layer Instrumentation Assessment (XPIA) campaign carried out at the Boulder Atmospheric Observatory. The three wind velocity components are retrieved, then compared with the data acquired through various profiling wind lidars, and high-frequency wind data obtained from sonic anemometers installed on a 300-m meteorological tower. The results show that the magnitude of the horizontal wind velocity and the wind direction obtained from the triple RHI scans are generally retrieved with good accuracy. However, poor accuracy is obtained for the evaluation of the vertical velocity, which is mainly due to its typically smaller magnitude, and the error propagation connected with the data retrieval procedure and accuracy in the experimental setup.

Dynamics and instabilities occurring in the near-wake of wind turbines have a crucial role for the wake downstream evolution, and for the onset of far-wake instabilities. Furthermore, wake dynamics significantly affect the intra-wind farm wake flow, wake interactions and potential power losses. Therefore, the physical understanding and predictability of wind turbine wake instabilities become a nodal point for prediction of wind power harvesting and optimization of wind farm layout. This study is focused on the prediction of the hub vortex instability encountered within wind turbine wakes under different operational conditions of the wind turbine. Linear stability analysis of the wake flow is performed by means of a novel approach that enables to take effects of turbulence on wake instabilities into account. Stability analysis is performed by using as base flow the time-averaged wake velocity field at a specific downstream location. The latter is modeled through Carton-McWilliams velocity profiles by mimicking the presence of the hub vortex and helicoidal tip vortices, and matching the wind turbine thrust coefficient predicted through the actuator disc model. The results show that hub vortex instability is promoted by increasing the turbine thrust coefficient. Indeed, a larger aerodynamic load produces an enhanced wake velocity deficit and axial shear, which are considered the main sources for the wake instability. Nonetheless, wake swirl also promotes hub vortex instability, and it can also affect the azimuthal wavenumber of the most unstable mode.

The near wake of wind turbines is characterized by the presence of the hub vortex, which is a coherent vorticity structure generated from the interaction between the root vortices and the boundary layer evolving over the turbine nacelle. Bymoving downstream, the hub vortex undergoes an instability with growth rate, azimuthal and axial wavenumbers determined by the characteristics of the incoming wind and turbine aerodynamics. Thus, a large variability of the hub vortex instability is expected for wind energy applications with consequent effects on wake downstream evolution, wake interactions within a wind farm, power production, and fatigue loads on turbines invested by wakes generated upstream. In order to predict characteristics of the hub vortex instability for different operating conditions, linear stability analysis is carried out by considering different statistics of the incoming wind turbulence, thrust coefficient, tip speed ratio, and blade lift distribution of a wind turbine. Axial and azimuthal wake velocity fields are modeled through Carton-McWilliams velocity profiles by mimicking the presence of the hub vortex, helicoidal tip vortices, and matching the wind turbine thrust coefficient predicted through the actuator disk model. The linear stability analysis shows that hub vortex instability is strongly affected by the wind turbine loading conditions, and specifically it is promoted by a larger thrust coefficient. A higher load of the wind turbines produces an enhanced axial velocity deficit and, in turn, higher shear in the radial direction of the streamwise velocity. The axial velocity shear within the turbine wake is also the main physical mechanism promoting the hub vortex instability when varying the lift distribution over the blade span for a specific loading condition. Cases with a larger velocity deficit in proximity of the wake center and less aerodynamic load towards the blade tip result to be more unstable. Moreover, wake swirl promotes hub vortex instability, and it can also affect the azimuthal wave number of the most unstable mode. Finally, higher Reynolds stresses and turbulent eddy viscosity decrease both growth rate and azimuthal wave number of the most unstable mode.