16th International Symposium for the Advancement of Boundary-Layer Remote Sensing (ISARS 2012)
Description:
The 16th International Symposium for the Advancement of Boundary-Layer Remote Sensing (ISARS 2012) was held 5-8 June 2012, in Boulder, Colorado, USA. The ISARS 2012 special collection of papers in the Journal of Applied Meteorology and Climatology (JAMC) and the Journal of Atmospheric and Oceanic Technology (JTECH) is a selection of extended papers from that symposium.
ISARS was founded in 1981 as the International Society of Acoustic Remote Sensing of the Atmosphere and Oceans. An ISARS symposium is held every two years, with a particular focus on atmospheric and oceanic boundary layers and related applications. The foci of the special collection are broad and include such topics as: new directions for boundary-layer remote sensing; the physical basis for boundary layer remote sensing; description of boundary layer physics; complex terrain meteorology; new models; operational applications; wind energy; air quality; aviation; urban meteorology; and polar science.
Collection organizer:
Stuart Bradley, University of Auckland, New Zealand
16th International Symposium for the Advancement of Boundary-Layer Remote Sensing (ISARS 2012)
Abstract
Different certification procedures in wind energy, such as power performance testing or load estimation, require measurements of the wind speed, which is set in relation to the electrical power output or the turbine loading. The wind shear affects the behavior of the turbine as hub heights and rotor diameters of modern wind turbines increase. Different measurement methods have been developed to take the wind shear into account. In this paper an approach is presented where the wind speed is measured from the nacelle of a wind turbine using a scanning lidar system.
The measurement campaign was performed on the two-bladed Controls Advanced Research Turbine (CART-2) at the National Wind Technology Center in Colorado. The wind speed of the turbine inflow was measured and recalculated in three different ways: using an anemometer installed on a meteorological mast, using the nacelle-based lidar scanner, and using the wind turbine itself. Here, the wind speed was recalculated from turbine data using the wind turbine as a big horizontal anemometer. Despite the small number of useful data, the correlation between this so-called rotor effective wind speed and the wind speed measured by the scanning nacelle-based lidar is high.
It could be demonstrated that a nacelle-based scanning lidar system provides accurate measurements of the wind speed converted by a wind turbine. This is a first step, and it provides evidence to support further investigations using a much more extensive dataset and refines the parameters in the measurement process.
Abstract
Different certification procedures in wind energy, such as power performance testing or load estimation, require measurements of the wind speed, which is set in relation to the electrical power output or the turbine loading. The wind shear affects the behavior of the turbine as hub heights and rotor diameters of modern wind turbines increase. Different measurement methods have been developed to take the wind shear into account. In this paper an approach is presented where the wind speed is measured from the nacelle of a wind turbine using a scanning lidar system.
The measurement campaign was performed on the two-bladed Controls Advanced Research Turbine (CART-2) at the National Wind Technology Center in Colorado. The wind speed of the turbine inflow was measured and recalculated in three different ways: using an anemometer installed on a meteorological mast, using the nacelle-based lidar scanner, and using the wind turbine itself. Here, the wind speed was recalculated from turbine data using the wind turbine as a big horizontal anemometer. Despite the small number of useful data, the correlation between this so-called rotor effective wind speed and the wind speed measured by the scanning nacelle-based lidar is high.
It could be demonstrated that a nacelle-based scanning lidar system provides accurate measurements of the wind speed converted by a wind turbine. This is a first step, and it provides evidence to support further investigations using a much more extensive dataset and refines the parameters in the measurement process.
Abstract
Stratocumulus (Sc) clouds occur frequently over the cold waters of the southeastern Pacific Ocean. Data collected during two Pan American Climate Study research cruises in the tropical eastern Pacific illuminate many aspects of this Sc-topped marine boundary layer (MBL). Here the focus is on understanding gaps in detectable wind-profiler reflectivities during two boreal autumn cruises. After rigorous quality control that included applying the Riddle threshold of minimum signal-to-noise ratio (SNR) detectability, there are many instances with no measurable atmospheric signals through a depth of up to several hundred meters, often lasting for an hour or more. Rain gauge data from the autumn 2004 cruise are used to calibrate the profiler, which allows SNR to be converted to both equivalent reflectivity and the structure-function parameter of the index of refraction
Abstract
Stratocumulus (Sc) clouds occur frequently over the cold waters of the southeastern Pacific Ocean. Data collected during two Pan American Climate Study research cruises in the tropical eastern Pacific illuminate many aspects of this Sc-topped marine boundary layer (MBL). Here the focus is on understanding gaps in detectable wind-profiler reflectivities during two boreal autumn cruises. After rigorous quality control that included applying the Riddle threshold of minimum signal-to-noise ratio (SNR) detectability, there are many instances with no measurable atmospheric signals through a depth of up to several hundred meters, often lasting for an hour or more. Rain gauge data from the autumn 2004 cruise are used to calibrate the profiler, which allows SNR to be converted to both equivalent reflectivity and the structure-function parameter of the index of refraction
Abstract
Currently used methods to estimate surface pollutant emissions require a set of specific air-sampling surveys. Data from a network of ground-based sodars and a network of air-quality stations in Moscow, Russia, are used to estimate the emission rates of carbon monoxide (CO) and nitric oxide (NO). The sodar network, consisting of three “LATAN-3” Doppler sodars and three “MTP-5” microwave temperature profilers, is used to measure the vertical profiles of vertical and horizontal wind velocity, wind direction, and temperature, which are used to determine the average mixing-layer height. The network of ground-based air-quality stations, consisting of 17 automated stations distributed uniformly across Moscow, continuously measured the CO and NO concentrations. This study focuses on an anticyclonic episode of high surface pressure over Moscow during 30 July–1 August 2012. After sunrise, the solar-induced convection effectively moderated the pollutant levels in the lowest 100–200 m. After sunset, convective mixing stopped and the wind weakened, which allowed CO and NO to reach hazardous levels. With an assumption of an average mixing-layer height of 150 m, the resulting estimate of surface emission of CO is ~6 μg m−2 s−1, whereas that for NO is ~0.6 μg m−2 s−1.
Abstract
Currently used methods to estimate surface pollutant emissions require a set of specific air-sampling surveys. Data from a network of ground-based sodars and a network of air-quality stations in Moscow, Russia, are used to estimate the emission rates of carbon monoxide (CO) and nitric oxide (NO). The sodar network, consisting of three “LATAN-3” Doppler sodars and three “MTP-5” microwave temperature profilers, is used to measure the vertical profiles of vertical and horizontal wind velocity, wind direction, and temperature, which are used to determine the average mixing-layer height. The network of ground-based air-quality stations, consisting of 17 automated stations distributed uniformly across Moscow, continuously measured the CO and NO concentrations. This study focuses on an anticyclonic episode of high surface pressure over Moscow during 30 July–1 August 2012. After sunrise, the solar-induced convection effectively moderated the pollutant levels in the lowest 100–200 m. After sunset, convective mixing stopped and the wind weakened, which allowed CO and NO to reach hazardous levels. With an assumption of an average mixing-layer height of 150 m, the resulting estimate of surface emission of CO is ~6 μg m−2 s−1, whereas that for NO is ~0.6 μg m−2 s−1.
Abstract
A major risk to helicopters is the unexpected encounter of degraded visual environments in close-to-ground operations, where a loss of visibility often is caused by clouds of dust (brownout) or snow (whiteout) stirred up by intense downwash. The understanding of the phenomenon is limited, and there is a need for instruments that can measure flow fields on scales larger than a few meters with good resolution. This paper reports on the use of synchronized continuous-wave Doppler lidars for rotorcraft downwash flow field studies.
Built from a modified ZephIR wind lidar and a double-prism arrangement for agile beam steering, a wind scanner—WindScanner—has been developed at the Department of Wind Energy at the Technical University of Denmark (DTU) Risø campus. The WindScanner measures the line-of-sight component of the airflow remotely and by rapid steering, the line-of-sight direction and the focus position; all points in space within a cone with a full opening angle of 120° can be reached from about 8 m out to some hundred meters depending on the range resolution required.
The first two-dimensional mean wind fields measured in a horizontal plane and in a vertical plane below a hovering search and rescue helicopter are presented. Since the line-of-sight directions of the two synchronized WindScanners were scanned within the plane of interest, the influence of the wind component perpendicular to the plane was avoided. The results also demonstrate the possibilities within less demanding flows encountered within complex terrain and wind-energy-related research for which the WindScanner technology primarily has been developed.
Abstract
A major risk to helicopters is the unexpected encounter of degraded visual environments in close-to-ground operations, where a loss of visibility often is caused by clouds of dust (brownout) or snow (whiteout) stirred up by intense downwash. The understanding of the phenomenon is limited, and there is a need for instruments that can measure flow fields on scales larger than a few meters with good resolution. This paper reports on the use of synchronized continuous-wave Doppler lidars for rotorcraft downwash flow field studies.
Built from a modified ZephIR wind lidar and a double-prism arrangement for agile beam steering, a wind scanner—WindScanner—has been developed at the Department of Wind Energy at the Technical University of Denmark (DTU) Risø campus. The WindScanner measures the line-of-sight component of the airflow remotely and by rapid steering, the line-of-sight direction and the focus position; all points in space within a cone with a full opening angle of 120° can be reached from about 8 m out to some hundred meters depending on the range resolution required.
The first two-dimensional mean wind fields measured in a horizontal plane and in a vertical plane below a hovering search and rescue helicopter are presented. Since the line-of-sight directions of the two synchronized WindScanners were scanned within the plane of interest, the influence of the wind component perpendicular to the plane was avoided. The results also demonstrate the possibilities within less demanding flows encountered within complex terrain and wind-energy-related research for which the WindScanner technology primarily has been developed.
Abstract
The structure and dynamic characteristics of the Kelvin–Helmholtz billows (KHB), observed with a sodar in the stable atmospheric boundary layer, are studied by means of composite analysis, which consists in the averaging of samples selected according to certain criteria. Using a specific kind of this method allowed the authors to obtain the fine structure of the perturbation velocity fields from the sodar data. The events of most pronounced KHB were visually selected from echograms of continuous sodar measurements in the Moscow region over 2008–10. The composite patterns of KHB have been constructed for a few cases of clear inclined–stripes echogram patterns to derive a typical finescale structure of billows and a spatial distribution of wind speed and shear within them. The interconnection between echo intensity and wind shear variations within such patterns is shown. The typical distributions of velocity perturbation within various forms of billows are found.
Abstract
The structure and dynamic characteristics of the Kelvin–Helmholtz billows (KHB), observed with a sodar in the stable atmospheric boundary layer, are studied by means of composite analysis, which consists in the averaging of samples selected according to certain criteria. Using a specific kind of this method allowed the authors to obtain the fine structure of the perturbation velocity fields from the sodar data. The events of most pronounced KHB were visually selected from echograms of continuous sodar measurements in the Moscow region over 2008–10. The composite patterns of KHB have been constructed for a few cases of clear inclined–stripes echogram patterns to derive a typical finescale structure of billows and a spatial distribution of wind speed and shear within them. The interconnection between echo intensity and wind shear variations within such patterns is shown. The typical distributions of velocity perturbation within various forms of billows are found.
Abstract
In this paper a Gabor transform–based algorithm is applied to identify and eliminate intermittent signal contamination in UHF wind profiling radars, such as that produced by migrating birds. The algorithm is applied in the time domain, and so it can be used to improve the accuracy of UHF radar wind profiler data in real time—an essential requirement if these wind profiler data are to be assimilated into operational weather forecast models. The added value of using a moment-level Weber–Wuertz pattern recognition scheme that follows the Gabor transform processing is demonstrated.
Abstract
In this paper a Gabor transform–based algorithm is applied to identify and eliminate intermittent signal contamination in UHF wind profiling radars, such as that produced by migrating birds. The algorithm is applied in the time domain, and so it can be used to improve the accuracy of UHF radar wind profiler data in real time—an essential requirement if these wind profiler data are to be assimilated into operational weather forecast models. The added value of using a moment-level Weber–Wuertz pattern recognition scheme that follows the Gabor transform processing is demonstrated.
Abstract
On a uniform terrain site, differences between a sodar and a mast-mounted cup anemometer will arise because of turbulent fluctuations and wind components being measured in different spaces, and because of the inherent difference between scalar and vector averaging. This paper develops theories for turbulence-related random fluctuations resulting from finite sampling rates and sampling from spatially distributed volumes. Coefficients of determination (R 2) are predicted comparable to those obtained in practice. It is shown that more than two-thirds of the reduction in R 2 arises from differences in the winds measured by mast instruments and by sodars, rather than by sodar errors: both instruments are measuring accurately, but just not in the same place or at the same time. The result is that sodars being used operationally should be able to measure winds to a root-mean-square accuracy of around 2%.
Abstract
On a uniform terrain site, differences between a sodar and a mast-mounted cup anemometer will arise because of turbulent fluctuations and wind components being measured in different spaces, and because of the inherent difference between scalar and vector averaging. This paper develops theories for turbulence-related random fluctuations resulting from finite sampling rates and sampling from spatially distributed volumes. Coefficients of determination (R 2) are predicted comparable to those obtained in practice. It is shown that more than two-thirds of the reduction in R 2 arises from differences in the winds measured by mast instruments and by sodars, rather than by sodar errors: both instruments are measuring accurately, but just not in the same place or at the same time. The result is that sodars being used operationally should be able to measure winds to a root-mean-square accuracy of around 2%.
Abstract
Boundary layer conditions in polar regions have been shown to have a significant impact on the levels of trace gases in the lower atmosphere. The ability to properly describe boundary layer characteristics (e.g., stability, depth, and variations on diurnal and seasonal scales) is essential to understanding the processes that control chemical budgets and surface fluxes in these regions. Surface turbulence data measured from 3D sonic anemometers on an 8-m tower at Summit Station, Greenland, were used for estimating boundary layer depths (BLD) in stable to weakly stable conditions. The turbulence-derived BLD estimates were evaluated for June 2010 using direct BLD measurements from an acoustic sounder located approximately 50 m away from the tower. BLDs during this period varied diurnally; minimum values were less than 10 m, and maximum values were greater than 150 m. BLD estimates provided a better comparison with sodar observations during stable conditions. Ozone and nitrogen oxides were also measured at the meteorological tower and investigated for their dependency on boundary layer structure. These analyses, in contrast to observations from South Pole, Antarctica, did not show a clear relation between surface-layer atmospheric trace-gas levels and the stable boundary layer.
Abstract
Boundary layer conditions in polar regions have been shown to have a significant impact on the levels of trace gases in the lower atmosphere. The ability to properly describe boundary layer characteristics (e.g., stability, depth, and variations on diurnal and seasonal scales) is essential to understanding the processes that control chemical budgets and surface fluxes in these regions. Surface turbulence data measured from 3D sonic anemometers on an 8-m tower at Summit Station, Greenland, were used for estimating boundary layer depths (BLD) in stable to weakly stable conditions. The turbulence-derived BLD estimates were evaluated for June 2010 using direct BLD measurements from an acoustic sounder located approximately 50 m away from the tower. BLDs during this period varied diurnally; minimum values were less than 10 m, and maximum values were greater than 150 m. BLD estimates provided a better comparison with sodar observations during stable conditions. Ozone and nitrogen oxides were also measured at the meteorological tower and investigated for their dependency on boundary layer structure. These analyses, in contrast to observations from South Pole, Antarctica, did not show a clear relation between surface-layer atmospheric trace-gas levels and the stable boundary layer.
Abstract
Investigations of lidar-assisted control to optimize the energy yield and to reduce loads of wind turbines have increased significantly in recent years. For this kind of control, it is crucial to know the correlation between the rotor effective wind speed and the wind preview provided by a nacelle- or spinner-based lidar system. If on the one hand, the assumed correlation is overestimated, then the uncorrelated frequencies of the preview will cause unnecessary control action, inducing undesired loads. On the other hand, the benefits of the lidar-assisted controller will not be fully exhausted, if correlated frequencies are filtered out. To avoid these miscalculations, this work presents a method to model the correlation between lidar systems and wind turbines using Kaimal wind spectra. The derived model accounts for different measurement configurations and spatial averaging of the lidar system, different rotor sizes, and wind evolution. The method is compared to real measurement data with promising results. In addition, examples depict how this model can be used to design an optimal controller and how the configuration of a lidar system is optimized for a given turbine to improve the correlation.
Abstract
Investigations of lidar-assisted control to optimize the energy yield and to reduce loads of wind turbines have increased significantly in recent years. For this kind of control, it is crucial to know the correlation between the rotor effective wind speed and the wind preview provided by a nacelle- or spinner-based lidar system. If on the one hand, the assumed correlation is overestimated, then the uncorrelated frequencies of the preview will cause unnecessary control action, inducing undesired loads. On the other hand, the benefits of the lidar-assisted controller will not be fully exhausted, if correlated frequencies are filtered out. To avoid these miscalculations, this work presents a method to model the correlation between lidar systems and wind turbines using Kaimal wind spectra. The derived model accounts for different measurement configurations and spatial averaging of the lidar system, different rotor sizes, and wind evolution. The method is compared to real measurement data with promising results. In addition, examples depict how this model can be used to design an optimal controller and how the configuration of a lidar system is optimized for a given turbine to improve the correlation.
Abstract
The DeTect Inc. RAPTOR velocity–azimuth display boundary layer (VAD-BL) radar wind profiler is a pulsed Doppler radar used to make automatic unattended measurements of wind profiles in the lower atmosphere. All data products are produced on site, in real time, and utilize quality control software to screen out interference. The nominal frequencies are 915 and 1290 MHz but other frequencies can be accommodated. While the architecture is similar to other boundary layer wind profilers, the RAPTOR VAD-BL is designed to provide consistently superior data quality due to its antenna design and signal processing capabilities. The antenna is a high-performance parabolic reflector with a feed that is designed in house for the operational frequency of the radar. The antenna is mounted on a robust military-grade azimuth-only positioner. The RAPTOR VAD-BL can collect data from several opposing beam positions with the goal of producing higher-quality wind data using the velocity–azimuth display (VAD) algorithm. The Advanced Signal Processing Engine (ASPEN) software used to calculate winds outperforms conventional consensus algorithms. The health and status of all critical subsystems is monitored via the profiler health monitor (PHM), a stand-alone monitor with its own microprocessor. Results from systems deployed for operational applications show the potential for the retrieval of high-quality data with excellent height coverage and a solid design that allows the antenna to perform under sustained high wind loading.
Abstract
The DeTect Inc. RAPTOR velocity–azimuth display boundary layer (VAD-BL) radar wind profiler is a pulsed Doppler radar used to make automatic unattended measurements of wind profiles in the lower atmosphere. All data products are produced on site, in real time, and utilize quality control software to screen out interference. The nominal frequencies are 915 and 1290 MHz but other frequencies can be accommodated. While the architecture is similar to other boundary layer wind profilers, the RAPTOR VAD-BL is designed to provide consistently superior data quality due to its antenna design and signal processing capabilities. The antenna is a high-performance parabolic reflector with a feed that is designed in house for the operational frequency of the radar. The antenna is mounted on a robust military-grade azimuth-only positioner. The RAPTOR VAD-BL can collect data from several opposing beam positions with the goal of producing higher-quality wind data using the velocity–azimuth display (VAD) algorithm. The Advanced Signal Processing Engine (ASPEN) software used to calculate winds outperforms conventional consensus algorithms. The health and status of all critical subsystems is monitored via the profiler health monitor (PHM), a stand-alone monitor with its own microprocessor. Results from systems deployed for operational applications show the potential for the retrieval of high-quality data with excellent height coverage and a solid design that allows the antenna to perform under sustained high wind loading.