The Experts below are selected from a list of 282 Experts worldwide ranked by ideXlab platform
T. W. Horst - One of the best experts on this subject based on the ideXlab platform.
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Measurements of Flow Distortion within the IRGASON Integrated Sonic Anemometer and CO $$_2$$
Boundary-Layer Meteorology, 2016Co-Authors: T. W. Horst, Roland Vogt, S P OncleyAbstract:Wind-tunnel and field measurements are analyzed to investigate flow distortion within the IRGASON integrated Sonic Anemometer and CO $$_2$$ 2 /H $$_2$$ 2 O gas analyzer as a function of wind speed, wind direction and attack angle. The wind-tunnel measurements are complimentary to the field measurements, and the dependence of the wind-tunnel mean-wind-component flow-distortion errors on wind direction agrees well with that of the field measurements. The field measurements exhibit significant overestimation of the crosswind variance and underestimation of the momentum flux with respect to an adjacent CSAT3 Sonic, as well as a transfer of turbulent kinetic energy from the streamwise wind component to the cross-stream wind components. In contrast, we find attenuation of only a few percent in the vertical velocity variance and the vertical flux of Sonic temperature. The attenuation of the fluxes appears to be caused to a large extent by decorrelation between the horizontal and vertical-velocity components and between the vertical velocity and Sonic temperature. Additional flow distortion due to transducer shadowing reduces to some extent the overestimation, but also increases the underestimation of the IRGASON turbulence statistics.
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measurements of flow distortion within the irgason integrated Sonic Anemometer and co_2 h_2o gas analyzer
Boundary-Layer Meteorology, 2016Co-Authors: T. W. Horst, Roland Vogt, Stephen P OncleyAbstract:Wind-tunnel and field measurements are analyzed to investigate flow distortion within the IRGASON integrated Sonic Anemometer and CO\(_2\)/H\(_2\)O gas analyzer as a function of wind speed, wind direction and attack angle. The wind-tunnel measurements are complimentary to the field measurements, and the dependence of the wind-tunnel mean-wind-component flow-distortion errors on wind direction agrees well with that of the field measurements. The field measurements exhibit significant overestimation of the crosswind variance and underestimation of the momentum flux with respect to an adjacent CSAT3 Sonic, as well as a transfer of turbulent kinetic energy from the streamwise wind component to the cross-stream wind components. In contrast, we find attenuation of only a few percent in the vertical velocity variance and the vertical flux of Sonic temperature. The attenuation of the fluxes appears to be caused to a large extent by decorrelation between the horizontal and vertical-velocity components and between the vertical velocity and Sonic temperature. Additional flow distortion due to transducer shadowing reduces to some extent the overestimation, but also increases the underestimation of the IRGASON turbulence statistics.
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Correction of a Non-orthogonal, Three-Component Sonic Anemometer for Flow Distortion by Transducer Shadowing
Boundary-Layer Meteorology, 2015Co-Authors: T. W. Horst, S. R. Semmer, G. MacleanAbstract:We propose that flow distortion within a non-orthogonal CSAT3 Sonic Anemometer is primarily due to transducer shadowing, which is caused by wakes in the lee of the acoustic transducers impinging on their measurement paths. The dependence of transducer shadowing on Sonic path geometry, wind direction and atmospheric stability is investigated with simulations that use surface-layer data from the Horizontal Array Turbulence Study (HATS) field program and canopy roughness-sublayer data from the CHATS (Canopy HATS) field program. We demonstrate the efficacy of correcting the CSAT3 for transducer shadowing with measurements of its flow distortion in the NCAR wind tunnel, combined with 6 months of data collected in the atmospheric surface layer with adjacent CSAT3 and orthogonal ATI-K Sonic Anemometers at the NCAR Marshall field site. CSAT3 and ATI-K measurements of the variance of vertical velocity $$\sigma _w^2$$ σ w 2 and the vertical flux of Sonic temperature agree within 1 % after correction of both Sonics for transducer shadowing. Both the simulations of transducer shadowing and the comparison of CSAT3 and ATI-K field data suggest a simple, approximate correction of CSAT3 surface-layer scalar fluxes with an increase on the order of 4–5 %, independent of wind direction and atmospheric stability. We also find that $$\sigma _w/u_*$$ σ w / u ∗ (where $$u_*$$ u ∗ is the friction velocity) and $$r_{uw}$$ r u w (the correlation coefficient) calculated with corrected CSAT3 data are insensitive to wind direction and agree closely with known values of these dimensionless variables for neutral stratification, which is evidence for the efficacy of the correction of the horizontal wind components for transducer shadowing as well.
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using Sonic Anemometer temperature to measure sensible heat flux in strong winds
Atmospheric Measurement Techniques, 2012Co-Authors: S. P. Burns, T. W. Horst, P. D. Blanken, L Jacobsen, R. K. MonsonAbstract:Abstract. Sonic Anemometers simultaneously measure the turbulent fluctuations of vertical wind (w') and Sonic temperature (Ts'), and are commonly used to measure sensible heat flux (H). Our study examines 30-min heat fluxes measured with a Campbell Scientific CSAT3 Sonic Anemometer above a subalpine forest. We compared H calculated with Ts to H calculated with a co-located thermocouple and found that, for horizontal wind speed (U) less than 8 m s−1, the agreement was around ±30 W m−2. However, for U ≈ 8 m s−1, the CSAT H had a generally positive deviation from H calculated with the thermocouple, reaching a maximum difference of ≈250 W m−2 at U ≈ 18 m s−1. With version 4 of the CSAT firmware, we found significant underestimation of the speed of sound and thus Ts in high winds (due to a delayed detection of the Sonic pulse), which resulted in the large CSAT heat flux errors. Although this Ts error is qualitatively similar to the well-known fundamental correction for the crosswind component, it is quantitatively different and directly related to the firmware estimation of the pulse arrival time. For a CSAT running version 3 of the firmware, there does not appear to be a significant underestimation of Ts; however, a Ts error similar to that of version 4 may occur if the CSAT is sufficiently out of calibration. An empirical correction to the CSAT heat flux that is consistent with our conceptual understanding of the Ts error is presented. Within a broader context, the surface energy balance is used to evaluate the heat flux measurements, and the usefulness of side-by-side instrument comparisons is discussed.
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Using Sonic Anemometer temperature to measure sensible heat flux in strong winds
Atmospheric Measurement Techniques Discussions, 2012Co-Authors: S. P. Burns, T. W. Horst, P. D. Blanken, R. K. MonsonAbstract:Abstract. The sensible heat flux (H) is a significant component of the surface energy balance (SEB). Sonic Anemometers simultaneously measure the turbulent fluctuations of vertical wind (w') and Sonic temperature (Ts'), and are commonly used to measure H. Our study examines 30-min heat fluxes measured with a Campbell Scientific model CSAT3 Sonic Anemometer above a subalpine forest. We compare H calculated with Ts to H calculated with a co-located thermocouple and find that for horizontal wind speed (U) less than 8 m s−1 the agreement is ≈±30 W m−2. However, for U >≈ 8 m s−1, the CSAT3 H becomes larger than H calculated with the thermocouple, reaching a maximum difference of ≈250 W m−2 at U ≈ 18 m s−1. H calculated with the thermocouple results in a SEB that is relatively independent of U at high wind speeds. In contrast, the SEB calculated with H from the CSAT3 varies considerably with U, particularly at night. Cospectral analysis of w'Ts' suggest that spurious correlation is a problem during high winds which leads to a positive (additive) increase in H calculated with the CSAT3. At night, when H is typically negative, this CSAT3 error results in a measured H that falsely approaches zero or even becomes positive. Within a broader context, the usefulness of side-by-side instrument comparisons are discussed.
Timothy A Bonin - One of the best experts on this subject based on the ideXlab platform.
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Evaluation of Turbulence Measurement Techniques from a Single Doppler Lidar
Atmospheric Measurement Techniques Discussions, 2017Co-Authors: Timothy A Bonin, S.p. Sandberg, Yelena Pichugina, Steven P. Oncley, A. Choukulkar, W. Alan Brewer, A M Weickmann, Robert M Banta, Douglas E. WolfeAbstract:Measurements of turbulence are essential to understand and quantify the transport and dispersal of heat, moisture, momentum, and trace gases within the planetary boundary layer. Through the years, various techniques to measure turbulence using Doppler lidar observations have been proposed. However, the accuracy of these measurements has rarely been validated against trusted in situ instrumentation. Herein, data from the eXperimental Planetary boundary layer Instrumentation Assessment (XPIA) are used to verify Doppler lidar turbulence profiles through comparison with Sonic Anemometer measurements. For 17 days at the end of the experiment, a single scanning Doppler lidar continuously cycled through different turbulence measurement strategies: velocity azimuth display, six-beam, and range height indicators with a vertical stare. Measurements of turbulence kinetic energy, turbulence intensity, and shear velocity from these techniques are compared with Sonic Anemometer measurements at six heights on a 300-m tower. The six-beam technique is found to generally measure turbulence kinetic energy and turbulence intensity the most accurately at all heights, showing little bias in its observations. Turbulence measurements from the velocity azimuth display method tended to biased low near the surface, as large eddies were not captured by the scan. None of the methods evaluated were able to consistently accurately measure the shear velocity. Each of the scanning strategies assessed had its own strengths and limitations that need to be considered when selecting the method used in future experiments.
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Improvement of Vertical Velocity Statistics Measured by a Doppler Lidar through Comparison with Sonic Anemometer Observations
2016Co-Authors: Timothy A Bonin, Petra M. Klein, Phillip B Chilson, Jennifer F. Newman, Sonia WhartonAbstract:Abstract. Since turbulence measurements from Doppler lidars are being increasingly used within wind energy and boundary-layer meteorology, it is important to assess and improve the accuracy of these observations. While turbulent quantities are measured by Doppler lidars in several different ways, the simplest and most frequently used statistic is vertical velocity variance (σ2ω) from zenith stares. However, the competing effects of signal noise and resolution volume limitations, which respectively increase and decrease σ2ω, reduce the accuracy of these measurements. Herein, an established method that utilizes the autocovariance of the signal to remove noise is evaluated and its skill in also correcting for volume-averaging effects in the calculation of σ2ω is assessed. Additionally, this autocovariance technique is further refined by defining the amount of lag time to use for the most accurate estimates of σ2ω. Through comparison of observations from two Doppler lidars and Sonic Anemometers on a 300-m tower, the autocovariance technique is shown to improve estimates of σ2ω over a variety of atmospheric conditions. After the autocoviance technique is applied, values of σ2ω from the Doppler lidars are generally in close agreement (R2 ≈ 0.95–0.98) with those calculated from Sonic Anemometer measurements.
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Improvement of vertical velocity statistics measured by a Doppler lidar through comparison with Sonic Anemometer observations
Atmospheric Measurement Techniques, 2016Co-Authors: Timothy A Bonin, Petra M. Klein, Phillip B Chilson, Jennifer F. Newman, Sonia WhartonAbstract:Since turbulence measurements from Doppler li-dars are being increasingly used within wind energy and boundary-layer meteorology, it is important to assess and improve the accuracy of these observations. While turbulent quantities are measured by Doppler lidars in several differ-ent ways, the simplest and most frequently used statistic is vertical velocity variance (w 2) from zenith stares. However, the competing effects of signal noise and resolution volume limitations, which respectively increase and decrease w 2 , re-duce the accuracy of these measurements. Herein, an estab-lished method that utilises the autocovariance of the signal to remove noise is evaluated and its skill in correcting for volume-averaging effects in the calculation of w 2 is also as-sessed. Additionally, this autocovariance technique is further refined by defining the amount of lag time to use for the most accurate estimates of w 2 . Through comparison of observa-tions from two Doppler lidars and Sonic Anemometers on a 300 m tower, the autocovariance technique is shown to gener-ally improve estimates of w 2 . After the autocovariance tech-nique is applied, values of w 2 from the Doppler lidars are generally in close agreement (R 2 ≈ 0.95 − 0.98) with those calculated from Sonic Anemometer measurements.
Michael Pirhalla - One of the best experts on this subject based on the ideXlab platform.
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urban wind field analysis from the jack rabbit ii special Sonic Anemometer study
Atmospheric Environment, 2020Co-Authors: Michael Pirhalla, David Heist, Steven G Perry, Steven R Hanna, Thomas Mazzola, Pal S Arya, Viney P AnejaAbstract:Abstract The Jack Rabbit II Special Sonic Anemometer Study (JRII-S), a field project designed to examine the flow and turbulence within a systematically arranged mock-urban environment constructed from CONEX shipping containers, is described in detail. The study involved the deployment of 35 Sonic Anemometers at multiple heights and locations, including a 32 m tall, unobstructed tower located about 115 m outside the building array to document the approach wind flow characteristics. The purpose of this work was to describe the experimental design, analyze the Sonic data, and report observed wind flow patterns within the urban canopy in comparison to the approaching boundary layer flow. We show that the flow within the building array follows a tendency towards one of three generalized flow regimes displaying channeling over a wide range of wind speeds, directions, and stabilities. Two or more Sonic Anemometers positioned only a few meters apart can have vastly different flow patterns that are dictated by the building structures. Within the building array, turbulence values represented by normalized vertical velocity variance (σw2) are at least two to three times greater than that in the approach flow. There is also little evidence that σw2 measured at various heights or locations within the JRII array is a strong function of stability type in contrast to the approach flow. The results reinforce how urban areas create complicated wind patterns, channeling effects, and localized turbulence that can impact the dispersion of an effluent release. These findings can be used to inform the development of improved wind flow algorithms to better characterize pollutant dispersion in fast-response models.
Sonia Wharton - One of the best experts on this subject based on the ideXlab platform.
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Improvement of Vertical Velocity Statistics Measured by a Doppler Lidar through Comparison with Sonic Anemometer Observations
2016Co-Authors: Timothy A Bonin, Petra M. Klein, Phillip B Chilson, Jennifer F. Newman, Sonia WhartonAbstract:Abstract. Since turbulence measurements from Doppler lidars are being increasingly used within wind energy and boundary-layer meteorology, it is important to assess and improve the accuracy of these observations. While turbulent quantities are measured by Doppler lidars in several different ways, the simplest and most frequently used statistic is vertical velocity variance (σ2ω) from zenith stares. However, the competing effects of signal noise and resolution volume limitations, which respectively increase and decrease σ2ω, reduce the accuracy of these measurements. Herein, an established method that utilizes the autocovariance of the signal to remove noise is evaluated and its skill in also correcting for volume-averaging effects in the calculation of σ2ω is assessed. Additionally, this autocovariance technique is further refined by defining the amount of lag time to use for the most accurate estimates of σ2ω. Through comparison of observations from two Doppler lidars and Sonic Anemometers on a 300-m tower, the autocovariance technique is shown to improve estimates of σ2ω over a variety of atmospheric conditions. After the autocoviance technique is applied, values of σ2ω from the Doppler lidars are generally in close agreement (R2 ≈ 0.95–0.98) with those calculated from Sonic Anemometer measurements.
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Improvement of vertical velocity statistics measured by a Doppler lidar through comparison with Sonic Anemometer observations
Atmospheric Measurement Techniques, 2016Co-Authors: Timothy A Bonin, Petra M. Klein, Phillip B Chilson, Jennifer F. Newman, Sonia WhartonAbstract:Since turbulence measurements from Doppler li-dars are being increasingly used within wind energy and boundary-layer meteorology, it is important to assess and improve the accuracy of these observations. While turbulent quantities are measured by Doppler lidars in several differ-ent ways, the simplest and most frequently used statistic is vertical velocity variance (w 2) from zenith stares. However, the competing effects of signal noise and resolution volume limitations, which respectively increase and decrease w 2 , re-duce the accuracy of these measurements. Herein, an estab-lished method that utilises the autocovariance of the signal to remove noise is evaluated and its skill in correcting for volume-averaging effects in the calculation of w 2 is also as-sessed. Additionally, this autocovariance technique is further refined by defining the amount of lag time to use for the most accurate estimates of w 2 . Through comparison of observa-tions from two Doppler lidars and Sonic Anemometers on a 300 m tower, the autocovariance technique is shown to gener-ally improve estimates of w 2 . After the autocovariance tech-nique is applied, values of w 2 from the Doppler lidars are generally in close agreement (R 2 ≈ 0.95 − 0.98) with those calculated from Sonic Anemometer measurements.
Xinhua Zhou - One of the best experts on this subject based on the ideXlab platform.
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recovery of the three dimensional wind and Sonic temperature data from a physically deformed Sonic Anemometer
Atmospheric Measurement Techniques, 2018Co-Authors: Xinhua Zhou, Qinghua Yang, Xiaojie Zhen, Yubin Li, Hui Shen, Ning ZhengAbstract:Abstract. A Sonic Anemometer reports three-dimensional (3-D) wind and Sonic temperature ( Ts) by measuring the time of ultraSonic signals transmitting along each of its three Sonic paths, whose geometry of lengths and angles in the Anemometer coordinate system was precisely determined through production calibrations and the geometry data were embedded into the Sonic Anemometer operating system (OS) for internal computations. If this geometry is deformed, although correctly measuring the time, the Sonic Anemometer continues to use its embedded geometry data for internal computations, resulting in incorrect output of 3-D wind and Ts data. However, if the geometry is remeasured (i.e., recalibrated) and to update the OS, the Sonic Anemometer can resume outputting correct data. In some cases, where immediate recalibration is not possible, a deformed Sonic Anemometer can be used because the ultraSonic signal-transmitting time is still correctly measured and the correct time can be used to recover the data through post processing. For example, in 2015, a Sonic Anemometer was geometrically deformed during transportation to Antarctica. Immediate deployment was critical, so the deformed Sonic Anemometer was used until a replacement arrived in 2016. Equations and algorithms were developed and implemented into the post-processing software to recover wind data with and without transducer-shadow correction and Ts data with crosswind correction. Post-processing used two geometric datasets, production calibration and recalibration, to recover the wind and Ts data from May 2015 to January 2016. The recovery reduced the difference of 9.60 to 8.93 ∘ C between measured and calculated Ts to 0.81 to −0.45 ∘ C, which is within the expected range, due to normal measurement errors. The recovered data were further processed to derive fluxes. As data reacquisition is time-consuming and expensive, this data-recovery approach is a cost-effective and time-saving option for similar cases. The equation development can be a reference for related topics.
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recovery of the 3 dimensional wind and Sonic temperature data from a Sonic Anemometer physically deformed away from manufacture geometrical settings
Atmospheric Measurement Techniques Discussions, 2018Co-Authors: Xinhua Zhou, Qinghua Yang, Xiaojie Zhen, Yubin Li, Hui Shen, Ning ZhengAbstract:Abstract. A Sonic Anemometer (Sonic) reports 3-dimensional wind and Sonic temperature ( T s ) by measuring the time of ultraSonic signals flying along each of its three Sonic paths whose geometry of lengths and angles in the Sonic coordinate system was precisely determined through production calibrations and was embedded into the Sonic’s firmware. If the Sonic path geometry is deformed, although correctly measuring the time, the Sonic continues to use its embedded geometry data for internal computations, resulting in incorrect data. However, if the geometry is re-measured (i.e. recalibrated) to update Sonic firmware, the Sonic can resume reporting correct data. In some cases, where immediate recalibration is not possible, a deformed Sonic can be used because ultraSonic signal-flying time is still correctly measured. For example, transportation of a Sonic to Antarctica in 2015 resulted in a geometrically deformed Sonic. Immediate deployment was critical, so the deformed Sonic had been used until a replacement arrived in 2016. To recover data from this deformed Sonic, equations and algorithms were developed and implemented into the post-processing software to recover wind data with/without transducer shadow correction and T s data with crosswind correction. Using two geometric datasets, production calibration and recalibration, post-processing recovered the wind and T s data from May 2015 to January 2016. The recovery reduced the difference of 9.60 to 8.93 °C between measured and calculated T s to 0.81 to −0.45 °C, which is within the expected range due to normal measurement errors. The recovered data were further processed to derive fluxes. Since such data reacquisition is time-consuming and expensive, this data recovery approach is a cost-effective and time-saving option applicable to similar cases. The equation development can be a reference to the studies on related topics.
