Measuring the turbulence profile in the lower atmospheric boundary layer

Iersel, M. van; Paulson, Daniel A.; Wu, Chensheng; Ferlic, Nathaniel A.; Rzasa, John R.; Davis, Christophér C.; Walker, Michael M.; Bowden, Mary; Spychalsky, Jonathan; Titus, Franklin

doi:10.1364/ao.58.006934

Cited by 14 publications

(7 citation statements)

References 11 publications

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“…Several measurement campaigns have used thermal probes/ resistance thermometers with weather balloons to measure temperature fluctuations at different heights in the atmosphere. [8][9][10] But balloon based profiles suffer from the fact that the measurements are spaced apart in time. At the United States Air Force Institute of Technology (AFIT), we have been using time-lapse imagery from a single camera and multiple cameras to remotely measure and characterize lower atmosphere turbulence.…”

Section: Introductionmentioning

confidence: 99%

Attempting to understand the vertical distribution of turbulence in the surface layer from multi-camera time-lapse imagery

Wilson,

Bose,

Freeman

et al. 2023

Unconventional Imaging, Sensing, and Adaptive Optics 2023

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In an earlier work, we demonstrated a method to profile turbulence using time-lapse imagery of a distant target from five spatially separated cameras. Extended features on the target were tracked and by measuring the variances of the difference in wavefront tilts sensed between cameras due to all pairs of target features, turbulence information along the imaging path could be extracted. The method is relatively low cost and does not require sophisticated instrumentation. Turbulence can be sensed remotely from a single site without deployment of sources or sensors at the target location. Additionally, the method is phase-based, and hence has an advantage over irradiance-based techniques which suffer from saturation issues. The same concept has been applied to understand how turbulence changes with altitude in the surface layer. Short exposure images of a 30 m tall water tower were analyzed to obtain turbulence profiles along the imaging path. The experiment was performed over two clear days from mid-morning to early afternoon. The turbulence profiles show a drop in turbulence with altitude as expected. However, the rate at which turbulence decreased with altitude was different close to the ground from at higher altitudes.

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Section: Introductionmentioning

confidence: 99%

Attempting to understand the vertical distribution of turbulence in the surface layer from multi-camera time-lapse imagery

Wilson,

Bose,

Freeman

et al. 2023

Unconventional Imaging, Sensing, and Adaptive Optics 2023

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“…1 Weather balloons provide temperature and wind profiles throughout the atmosphere which allows for a derived measurement of Cn 2 . 2,3 Laser guidestar based sensing systems such as Slope Detection and Ranging (SLODAR) which work by measuring correlation between wavefront slopes measured by Shack-Hartmann Sensors and Scintillation Detection and Ranging (SCIDAR) which uses pupil plane correlation of scintillation, can provide vertical profiles of Cn 2 . 4,5 Acoustic sounding based techniques such as Sound Detection and Ranging (SODAR) can provide derived turbulence information too.…”

Section: Introductionmentioning

confidence: 99%

A new approach to profiling atmospheric turbulence using a dynamically ranged Raleigh beacon system

Wilson,

Bose,

Zuraski

et al. 2023

Unconventional Imaging, Sensing, and Adaptive Optics 2023

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The Turbulence and Aerosol Research Dynamic Interrogation System (TARDIS) is an optical sensing system that is based on dynamically changing the range between the collecting sensor and Rayleigh beacon during a static period of relatively unchanging turbulence-induced wavefront perturbations. In the past, obtaining measurement-based estimates of the turbulence strength profile from TARDIS was based around collating segmented refractive index structure parameter, Cn2 values traced to specific layers of the atmosphere. These values were developed from Fried parameter segments, which were deduced from differential tilt variance measurements from neighboring subapertures on the Shack-Hartmann wavefront sensor. In this work, we will exploit the crossings between the sensing paths from the different beacon locations (during a static period) to the wavefront sensor subapertures to derive turbulence profiles along the path. The differential tilt variance between a pair of subapertures due to a pair of beacons at two different ranges in a crossed sensing path configuration has a unique turbulence weighting function associated with it which depends on the geometry of the beacons and the subapertures. By using these unique path weighting functions along with the corresponding measured differential tilt variances for all configurations where the sensing paths cross, Cn2 profiles along the path can be constructed. The derivation of the weighting functions will be discussed and derived profiles will be compared to measurements from other profiling instruments such as MZA’s DELTA-Sky and to numerical weather prediction models.

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“…In addition, using the Radiosonde and sounding balloon, turbulence profile can be acquired at high spatial resolutions [18][19][20][21][22]. In the near-surface, researchers mostly use the relationship between C 2 n and the temperature structure constant C 2 T [23][24][25]. A large aperture scintillometer (LAS) can measure the path-averaged C 2 n within a certain distance in high time resolution, which is also a common instrument using the intensity scintillation principle [26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Turbulence Detection in the Atmospheric Boundary Layer Using Coherent Doppler Wind Lidar and Microwave Radiometer

Jiang

Yuan

et al. 2022

Remote Sensing

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The refractive index structure constant (Cn2) is a key parameter used in describing the influence of turbulence on laser transmissions in the atmosphere. Three different methods for estimating Cn2 were analyzed in detail. A new method that uses a combination of these methods for continuous Cn2 profiling with both high temporal and spatial resolution is proposed and demonstrated. Under the assumption of the Kolmogorov “2/3 law”, the Cn2 profile can be calculated by using the wind field and turbulent kinetic energy dissipation rate (TKEDR) measured by coherent Doppler wind lidar (CDWL) and other meteorological parameters derived from a microwave radiometer (MWR). In a horizontal experiment, a comparison between the results from our new method and measurements made by a large aperture scintillometer (LAS) is conducted. The correlation coefficient, mean error, and standard deviation between them in a six-day observation are 0.8073, 8.18 × 10−16 m−2/3, and 1.27 × 10−15 m−2/3, respectively. In the vertical direction, the continuous profiling results of Cn2 and other turbulence parameters with high resolution in the atmospheric boundary layer (ABL) are retrieved. In addition, the limitation and uncertainty of this method under different circumstances were analyzed, which shows that the relative error of Cn2 estimation normally does not exceed 30% under the convective boundary layer (CBL).

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Measuring the turbulence profile in the lower atmospheric boundary layer

Cited by 14 publications

References 11 publications

Attempting to understand the vertical distribution of turbulence in the surface layer from multi-camera time-lapse imagery

Attempting to understand the vertical distribution of turbulence in the surface layer from multi-camera time-lapse imagery

A new approach to profiling atmospheric turbulence using a dynamically ranged Raleigh beacon system

Turbulence Detection in the Atmospheric Boundary Layer Using Coherent Doppler Wind Lidar and Microwave Radiometer

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