Abstract

This paper evaluates the wake vortex characteristics using pulsed coherent Doppler lidar (PCDL) under near-ground effect (NGE). A wake vortex visualization demonstrator (V2D) is developed in order to visualize wake vortex in real-time. The combination of radial velocity distribution and FFT spectrum characterization are used to identify the core position of wake vortex. The velocity envelope and Burnham-Hallock model correction are used to retrieve the circulation of wake vortex under NGE. The circulation error, which is caused by PCDL scanning mode, is simulated and corrected. To investigate the dissipation rate’s effect on wake vortex in real atmosphere, the cross wind and atmospheric turbulence are concurrently retrieved from the same measurement of wake vortex by using structure function. The statistics of wake vortex parameters are analyzed, based on the measurement campaign at Beijing Capital International Airport (BCIA) in 2017.

© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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    [Crossref]
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    [Crossref]
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  40. V. Banakh, I. Smalikho, E. Pichugina, and W. Brewer, “Representativeness of measurements of the dissipation rate of turbulence energy by scanning Doppler lidar,” Atmos. Oceanic Opt. 23(1), 48–54 (2010).
    [Crossref]
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2019 (1)

H. Zhang, S. Wu, Q. Wang, B. Liu, B. Yin, and X. Zhai, “Airport low-level wind shear lidar observation at beijing capital international airport,” Infrared Phys. Technol. 96, 113–122 (2019).
[Crossref]

2018 (4)

X. Zhai, S. Wu, B. Liu, X. Song, and J. Yin, “Shipborne wind measurement and motion-induced error correction by coherent doppler lidar over yellow sea in 2014,” Atmos. Meas. Tech. 11(3), 1313–1331 (2018).
[Crossref]

N. Bodini, J. Lundquist, and R. Newsom, “Estimation of turbulence dissipation rate and its variability from sonic anemometer and wind Doppler lidar during the XPIA field campaign,” Atmos. Meas. Tech. 11(7), 4291–4308 (2018).
[Crossref]

V. Banakh and I. Smalikho, “Lidar Studies of Wind Turbulence in the Stable Atmospheric Boundary Layer,” Remote Sens. 10(8), 1219 (2018).
[Crossref]

H. Gao, J. Li, P. W. Chan, K. K. Hon, and X. Wang, “Parameter-retrieval of dry-air wake vortices with a scanning Doppler Lidar,” Opt. Express 26(13), 16377–16392 (2018).
[Crossref] [PubMed]

2017 (5)

M. Lin, W. Huang, Z. Zhang, C. Xu, and G. Cui, “Numerical study of aircraft wake vortex evolution near ground in stable atmospheric boundary layer,” Chin. J. Aeronauti. 30(6), 1866–1876 (2017).
[Crossref]

M. Lin, G. Cui, and Z. Zhang, “A new vortex sheet model for simulating aircraft wake vortex evolution,” Chin. J. Aeronauti. 30(4), 1315–1326 (2017).
[Crossref]

X. Zhai, S. Wu, and B. Liu, “Doppler lidar investigation of wind turbine wake characteristics and atmospheric turbulence under different surface roughness,” Opt. Express 25(12), A515–A529 (2017).
[Crossref] [PubMed]

I. Smalikho and V. Banakh, “Measurements of wind turbulence parameters by a conically scanning coherent Doppler lidar in the atmospheric boundary layer,” Atmos. Meas. Tech. 10(11), 4191–4208 (2017).
[Crossref]

P. W. Chan, J. Wurman, and P. Robinson, “LIDAR ground-based velocity track display analyses and surface observations of a vortex shedding event observed at the Hong Kong International Airport on April 11, 2011,” Atmosfera 30(4), 275–285 (2017).
[Crossref]

2016 (2)

S. Wu, B. Liu, J. Liu, X. Zhai, C. Feng, G. Wang, H. Zhang, J. Yin, X. Wang, R. Li, and D. Gallacher, “Wind turbine wake visualization and characteristics analysis by Doppler lidar,” Opt. Express 24(10), A762–A780 (2016).
[Crossref] [PubMed]

F. Holzäpfel, A. Stephan, T. Heel, and S. Körner, “Enhanced wake vortex decay in ground proximity triggered by plate lines,” Aircr. Eng. Aerosp. Technol. 88(2), 206–214 (2016).
[Crossref]

2015 (2)

2010 (2)

I. Smalikho and S. Rahm, “Lidar investigations of the effects of wind and atmospheric turbulence on an aircraft wake vortex,” Atmos. Oceanic Opt. 23(2), 137–146 (2010).
[Crossref]

V. Banakh, I. Smalikho, E. Pichugina, and W. Brewer, “Representativeness of measurements of the dissipation rate of turbulence energy by scanning Doppler lidar,” Atmos. Oceanic Opt. 23(1), 48–54 (2010).
[Crossref]

2008 (1)

S. Rahm and I. Smalikho, “Aircraft wake vortex measurement with airborne coherent Doppler lidar,” J. Aircr. 45(4), 1148–1155 (2008).
[Crossref]

2007 (2)

F. Holzäpfel and M. Steen, “Aircraft wake-vortex evolution in ground proximity: analysis and parameterization,” AIAA J. 45(1), 218–227 (2007).
[Crossref]

F. Holzäpfel and M. Steen, “Aircraft wake-vortex evolution in ground proximity: analysis and parameterization,” AIAA J. 45(1), 218–227 (2007).
[Crossref]

2005 (3)

R. Frehlich and R. Sharman, “Maximum likelihood estimates of vortex parameters from simulated coherent Doppler lidar data,” J. Atmos. Ocean. Technol. 22(2), 117–130 (2005).
[Crossref]

T. Gerz, F. Holzäpfel, W. Bryant, F. Köpp, M. Frech, A. Tafferner, and G. Winckelmans, “Research towards a wake-vortex advisory system for optimal aircraft spacing,” C. R. Phys. 6(4-5), 501–523 (2005).
[Crossref]

I. Smalikho, F. Köpp, and S. Rahm, “Measurement of atmospheric turbulence by 2-μ m Doppler lidar,” J. Atmos. Ocean. Technol. 22(11), 1733–1747 (2005).
[Crossref]

2004 (1)

F. Köpp, S. Rahm, and I. Smalikho, “Characterization of aircraft wake vortices by 2-μ m pulsed Doppler lidar,” J. Atmos. Ocean. Technol. 21(2), 194–206 (2004).
[Crossref]

2003 (2)

F. Holzäpfel, T. Gerz, F. Köpp, E. Stumpf, M. Harris, R. I. Young, and A. Dolfi-Bouteyre, “Strategies for circulation evaluation of aircraft wake vortices measured by lidar,” J. Atmos. Ocean. Technol. 20(8), 1183–1195 (2003).
[Crossref]

F. Holzäpfel, “Probabilistic two-phase wake vortex decay and transport model,” J. Aircr. 40, 323–331 (2003).
[Crossref]

2002 (1)

T. Gerz, F. Holzäpfel, and D. Darracq, “Commercial aircraft wake vortices,” Prog. Aerosp. Sci. 38(3), 181–208 (2002).
[Crossref]

Banakh, V.

V. Banakh and I. Smalikho, “Lidar Studies of Wind Turbulence in the Stable Atmospheric Boundary Layer,” Remote Sens. 10(8), 1219 (2018).
[Crossref]

I. Smalikho and V. Banakh, “Measurements of wind turbulence parameters by a conically scanning coherent Doppler lidar in the atmospheric boundary layer,” Atmos. Meas. Tech. 10(11), 4191–4208 (2017).
[Crossref]

V. Banakh, I. Smalikho, E. Pichugina, and W. Brewer, “Representativeness of measurements of the dissipation rate of turbulence energy by scanning Doppler lidar,” Atmos. Oceanic Opt. 23(1), 48–54 (2010).
[Crossref]

Banakh, V. A.

Barr, K.

D. Jacob, D. Lai, D. Delisi, D. Hutton, K. Barr, S. Shald, S. Hannon, and P. Gatt, “Assessment of Lockheed Martin’s Aircraft Wake Vortex Circulation Estimation Algorithms Using Simulated Lidar Data,” in 3rd AIAA Atmospheric Space Environments Conference (2011), p. 3196.
[Crossref]

Bodini, N.

N. Bodini, J. Lundquist, and R. Newsom, “Estimation of turbulence dissipation rate and its variability from sonic anemometer and wind Doppler lidar during the XPIA field campaign,” Atmos. Meas. Tech. 11(7), 4291–4308 (2018).
[Crossref]

Brewer, W.

V. Banakh, I. Smalikho, E. Pichugina, and W. Brewer, “Representativeness of measurements of the dissipation rate of turbulence energy by scanning Doppler lidar,” Atmos. Oceanic Opt. 23(1), 48–54 (2010).
[Crossref]

Bryant, W.

T. Gerz, F. Holzäpfel, W. Bryant, F. Köpp, M. Frech, A. Tafferner, and G. Winckelmans, “Research towards a wake-vortex advisory system for optimal aircraft spacing,” C. R. Phys. 6(4-5), 501–523 (2005).
[Crossref]

Chan, P. W.

H. Gao, J. Li, P. W. Chan, K. K. Hon, and X. Wang, “Parameter-retrieval of dry-air wake vortices with a scanning Doppler Lidar,” Opt. Express 26(13), 16377–16392 (2018).
[Crossref] [PubMed]

P. W. Chan, J. Wurman, and P. Robinson, “LIDAR ground-based velocity track display analyses and surface observations of a vortex shedding event observed at the Hong Kong International Airport on April 11, 2011,” Atmosfera 30(4), 275–285 (2017).
[Crossref]

Cui, G.

M. Lin, W. Huang, Z. Zhang, C. Xu, and G. Cui, “Numerical study of aircraft wake vortex evolution near ground in stable atmospheric boundary layer,” Chin. J. Aeronauti. 30(6), 1866–1876 (2017).
[Crossref]

M. Lin, G. Cui, and Z. Zhang, “A new vortex sheet model for simulating aircraft wake vortex evolution,” Chin. J. Aeronauti. 30(4), 1315–1326 (2017).
[Crossref]

Darracq, D.

T. Gerz, F. Holzäpfel, and D. Darracq, “Commercial aircraft wake vortices,” Prog. Aerosp. Sci. 38(3), 181–208 (2002).
[Crossref]

Delisi, D.

D. Jacob, D. Lai, D. Delisi, D. Hutton, K. Barr, S. Shald, S. Hannon, and P. Gatt, “Assessment of Lockheed Martin’s Aircraft Wake Vortex Circulation Estimation Algorithms Using Simulated Lidar Data,” in 3rd AIAA Atmospheric Space Environments Conference (2011), p. 3196.
[Crossref]

Delisi, D. P.

D. Jacob, D. Y. Lai, M. J. Pruis, and D. P. Delisi, “Assessment of WakeMod 4: A New Standalone Wake Vortex Algorithm for Estimating Circulation Strength and Position,” in 7th AIAA Atmospheric and Space Environments Conference (2015), p. 3176.
[Crossref]

D. Jacob, D. Y. Lai, M. J. Pruis, and D. P. Delisi, “Assessment of WakeMod 4: A New Standalone Wake Vortex Algorithm for Estimating Circulation Strength and Position,” in 7th AIAA Atmospheric and Space Environments Conference (2015), p. 3176.
[Crossref]

Dolfi-Bouteyre, A.

F. Holzäpfel, T. Gerz, F. Köpp, E. Stumpf, M. Harris, R. I. Young, and A. Dolfi-Bouteyre, “Strategies for circulation evaluation of aircraft wake vortices measured by lidar,” J. Atmos. Ocean. Technol. 20(8), 1183–1195 (2003).
[Crossref]

Feng, C.

Frech, M.

T. Gerz, F. Holzäpfel, W. Bryant, F. Köpp, M. Frech, A. Tafferner, and G. Winckelmans, “Research towards a wake-vortex advisory system for optimal aircraft spacing,” C. R. Phys. 6(4-5), 501–523 (2005).
[Crossref]

Frehlich, R.

R. Frehlich and R. Sharman, “Maximum likelihood estimates of vortex parameters from simulated coherent Doppler lidar data,” J. Atmos. Ocean. Technol. 22(2), 117–130 (2005).
[Crossref]

Gallacher, D.

Gao, H.

Gatt, P.

D. Jacob, D. Lai, D. Delisi, D. Hutton, K. Barr, S. Shald, S. Hannon, and P. Gatt, “Assessment of Lockheed Martin’s Aircraft Wake Vortex Circulation Estimation Algorithms Using Simulated Lidar Data,” in 3rd AIAA Atmospheric Space Environments Conference (2011), p. 3196.
[Crossref]

Gerz, T.

T. Gerz, F. Holzäpfel, W. Bryant, F. Köpp, M. Frech, A. Tafferner, and G. Winckelmans, “Research towards a wake-vortex advisory system for optimal aircraft spacing,” C. R. Phys. 6(4-5), 501–523 (2005).
[Crossref]

F. Holzäpfel, T. Gerz, F. Köpp, E. Stumpf, M. Harris, R. I. Young, and A. Dolfi-Bouteyre, “Strategies for circulation evaluation of aircraft wake vortices measured by lidar,” J. Atmos. Ocean. Technol. 20(8), 1183–1195 (2003).
[Crossref]

T. Gerz, F. Holzäpfel, and D. Darracq, “Commercial aircraft wake vortices,” Prog. Aerosp. Sci. 38(3), 181–208 (2002).
[Crossref]

Hamilton, D.

F. Proctor, D. Hamilton, and J. Han, “Wake vortex transport and decay in ground effect-Vortex linking with the ground,” in 38th Aerospace Sciences Meeting and Exhibit (2000), p. 757.
[Crossref]

Han, J.

F. Proctor, D. Hamilton, and J. Han, “Wake vortex transport and decay in ground effect-Vortex linking with the ground,” in 38th Aerospace Sciences Meeting and Exhibit (2000), p. 757.
[Crossref]

Hannon, S.

D. Jacob, D. Lai, D. Delisi, D. Hutton, K. Barr, S. Shald, S. Hannon, and P. Gatt, “Assessment of Lockheed Martin’s Aircraft Wake Vortex Circulation Estimation Algorithms Using Simulated Lidar Data,” in 3rd AIAA Atmospheric Space Environments Conference (2011), p. 3196.
[Crossref]

Harris, M.

F. Holzäpfel, T. Gerz, F. Köpp, E. Stumpf, M. Harris, R. I. Young, and A. Dolfi-Bouteyre, “Strategies for circulation evaluation of aircraft wake vortices measured by lidar,” J. Atmos. Ocean. Technol. 20(8), 1183–1195 (2003).
[Crossref]

Heel, T.

F. Holzäpfel, A. Stephan, T. Heel, and S. Körner, “Enhanced wake vortex decay in ground proximity triggered by plate lines,” Aircr. Eng. Aerosp. Technol. 88(2), 206–214 (2016).
[Crossref]

Hinton, D.

R. Perry, D. Hinton, R. Stuever, R. Perry, D. Hinton, and R. Stuever, “NASA wake vortex research for aircraft spacing,” in 35th Aerospace Sciences Meeting and Exhibit (1997), p. 57.
[Crossref]

R. Perry, D. Hinton, R. Stuever, R. Perry, D. Hinton, and R. Stuever, “NASA wake vortex research for aircraft spacing,” in 35th Aerospace Sciences Meeting and Exhibit (1997), p. 57.
[Crossref]

D. Hinton, “An aircraft vortex spacing system (AVOSS) for dynamical wake vortex spacing criteria,” (1996).

Hinton, D. A.

D. A. Hinton, “An aircraft vortex spacing system (AVOSS) for dynamical wake vortex spacing criteria.” (1996).

Holzäpfel, F.

F. Holzäpfel, A. Stephan, T. Heel, and S. Körner, “Enhanced wake vortex decay in ground proximity triggered by plate lines,” Aircr. Eng. Aerosp. Technol. 88(2), 206–214 (2016).
[Crossref]

I. N. Smalikho, V. A. Banakh, F. Holzäpfel, and S. Rahm, “Method of radial velocities for the estimation of aircraft wake vortex parameters from data measured by coherent Doppler lidar,” Opt. Express 23(19), A1194–A1207 (2015).
[Crossref] [PubMed]

F. Holzäpfel and M. Steen, “Aircraft wake-vortex evolution in ground proximity: analysis and parameterization,” AIAA J. 45(1), 218–227 (2007).
[Crossref]

F. Holzäpfel and M. Steen, “Aircraft wake-vortex evolution in ground proximity: analysis and parameterization,” AIAA J. 45(1), 218–227 (2007).
[Crossref]

T. Gerz, F. Holzäpfel, W. Bryant, F. Köpp, M. Frech, A. Tafferner, and G. Winckelmans, “Research towards a wake-vortex advisory system for optimal aircraft spacing,” C. R. Phys. 6(4-5), 501–523 (2005).
[Crossref]

F. Holzäpfel, “Probabilistic two-phase wake vortex decay and transport model,” J. Aircr. 40, 323–331 (2003).
[Crossref]

F. Holzäpfel, T. Gerz, F. Köpp, E. Stumpf, M. Harris, R. I. Young, and A. Dolfi-Bouteyre, “Strategies for circulation evaluation of aircraft wake vortices measured by lidar,” J. Atmos. Ocean. Technol. 20(8), 1183–1195 (2003).
[Crossref]

T. Gerz, F. Holzäpfel, and D. Darracq, “Commercial aircraft wake vortices,” Prog. Aerosp. Sci. 38(3), 181–208 (2002).
[Crossref]

Hon, K. K.

Huang, W.

M. Lin, W. Huang, Z. Zhang, C. Xu, and G. Cui, “Numerical study of aircraft wake vortex evolution near ground in stable atmospheric boundary layer,” Chin. J. Aeronauti. 30(6), 1866–1876 (2017).
[Crossref]

Hutton, D.

D. Jacob, D. Lai, D. Delisi, D. Hutton, K. Barr, S. Shald, S. Hannon, and P. Gatt, “Assessment of Lockheed Martin’s Aircraft Wake Vortex Circulation Estimation Algorithms Using Simulated Lidar Data,” in 3rd AIAA Atmospheric Space Environments Conference (2011), p. 3196.
[Crossref]

Jacob, D.

D. Jacob, D. Lai, D. Delisi, D. Hutton, K. Barr, S. Shald, S. Hannon, and P. Gatt, “Assessment of Lockheed Martin’s Aircraft Wake Vortex Circulation Estimation Algorithms Using Simulated Lidar Data,” in 3rd AIAA Atmospheric Space Environments Conference (2011), p. 3196.
[Crossref]

D. Jacob, D. Y. Lai, M. J. Pruis, and D. P. Delisi, “Assessment of WakeMod 4: A New Standalone Wake Vortex Algorithm for Estimating Circulation Strength and Position,” in 7th AIAA Atmospheric and Space Environments Conference (2015), p. 3176.
[Crossref]

D. Jacob, D. Y. Lai, M. J. Pruis, and D. P. Delisi, “Assessment of WakeMod 4: A New Standalone Wake Vortex Algorithm for Estimating Circulation Strength and Position,” in 7th AIAA Atmospheric and Space Environments Conference (2015), p. 3176.
[Crossref]

Köpp, F.

T. Gerz, F. Holzäpfel, W. Bryant, F. Köpp, M. Frech, A. Tafferner, and G. Winckelmans, “Research towards a wake-vortex advisory system for optimal aircraft spacing,” C. R. Phys. 6(4-5), 501–523 (2005).
[Crossref]

I. Smalikho, F. Köpp, and S. Rahm, “Measurement of atmospheric turbulence by 2-μ m Doppler lidar,” J. Atmos. Ocean. Technol. 22(11), 1733–1747 (2005).
[Crossref]

F. Köpp, S. Rahm, and I. Smalikho, “Characterization of aircraft wake vortices by 2-μ m pulsed Doppler lidar,” J. Atmos. Ocean. Technol. 21(2), 194–206 (2004).
[Crossref]

F. Holzäpfel, T. Gerz, F. Köpp, E. Stumpf, M. Harris, R. I. Young, and A. Dolfi-Bouteyre, “Strategies for circulation evaluation of aircraft wake vortices measured by lidar,” J. Atmos. Ocean. Technol. 20(8), 1183–1195 (2003).
[Crossref]

Körner, S.

F. Holzäpfel, A. Stephan, T. Heel, and S. Körner, “Enhanced wake vortex decay in ground proximity triggered by plate lines,” Aircr. Eng. Aerosp. Technol. 88(2), 206–214 (2016).
[Crossref]

Lai, D.

D. Jacob, D. Lai, D. Delisi, D. Hutton, K. Barr, S. Shald, S. Hannon, and P. Gatt, “Assessment of Lockheed Martin’s Aircraft Wake Vortex Circulation Estimation Algorithms Using Simulated Lidar Data,” in 3rd AIAA Atmospheric Space Environments Conference (2011), p. 3196.
[Crossref]

Lai, D. Y.

D. Jacob, D. Y. Lai, M. J. Pruis, and D. P. Delisi, “Assessment of WakeMod 4: A New Standalone Wake Vortex Algorithm for Estimating Circulation Strength and Position,” in 7th AIAA Atmospheric and Space Environments Conference (2015), p. 3176.
[Crossref]

D. Jacob, D. Y. Lai, M. J. Pruis, and D. P. Delisi, “Assessment of WakeMod 4: A New Standalone Wake Vortex Algorithm for Estimating Circulation Strength and Position,” in 7th AIAA Atmospheric and Space Environments Conference (2015), p. 3176.
[Crossref]

Li, J.

Li, R.

Lin, M.

M. Lin, W. Huang, Z. Zhang, C. Xu, and G. Cui, “Numerical study of aircraft wake vortex evolution near ground in stable atmospheric boundary layer,” Chin. J. Aeronauti. 30(6), 1866–1876 (2017).
[Crossref]

M. Lin, G. Cui, and Z. Zhang, “A new vortex sheet model for simulating aircraft wake vortex evolution,” Chin. J. Aeronauti. 30(4), 1315–1326 (2017).
[Crossref]

Liu, B.

H. Zhang, S. Wu, Q. Wang, B. Liu, B. Yin, and X. Zhai, “Airport low-level wind shear lidar observation at beijing capital international airport,” Infrared Phys. Technol. 96, 113–122 (2019).
[Crossref]

X. Zhai, S. Wu, B. Liu, X. Song, and J. Yin, “Shipborne wind measurement and motion-induced error correction by coherent doppler lidar over yellow sea in 2014,” Atmos. Meas. Tech. 11(3), 1313–1331 (2018).
[Crossref]

X. Zhai, S. Wu, and B. Liu, “Doppler lidar investigation of wind turbine wake characteristics and atmospheric turbulence under different surface roughness,” Opt. Express 25(12), A515–A529 (2017).
[Crossref] [PubMed]

S. Wu, B. Liu, J. Liu, X. Zhai, C. Feng, G. Wang, H. Zhang, J. Yin, X. Wang, R. Li, and D. Gallacher, “Wind turbine wake visualization and characteristics analysis by Doppler lidar,” Opt. Express 24(10), A762–A780 (2016).
[Crossref] [PubMed]

Liu, J.

Lundquist, J.

N. Bodini, J. Lundquist, and R. Newsom, “Estimation of turbulence dissipation rate and its variability from sonic anemometer and wind Doppler lidar during the XPIA field campaign,” Atmos. Meas. Tech. 11(7), 4291–4308 (2018).
[Crossref]

Newsom, R.

N. Bodini, J. Lundquist, and R. Newsom, “Estimation of turbulence dissipation rate and its variability from sonic anemometer and wind Doppler lidar during the XPIA field campaign,” Atmos. Meas. Tech. 11(7), 4291–4308 (2018).
[Crossref]

Nguyen, C.

D. Ramsey and C. Nguyen, “Characterizing aircraft wake vortices with ground-based pulsed coherent Lidar: effects of vortex circulation strength and Lidar signal-to-noise ratio on the spectral signature,” in 3rd AIAA Atmospheric Space Environments Conference (2011), p. 3198.
[Crossref]

Perry, R.

R. Perry, D. Hinton, R. Stuever, R. Perry, D. Hinton, and R. Stuever, “NASA wake vortex research for aircraft spacing,” in 35th Aerospace Sciences Meeting and Exhibit (1997), p. 57.
[Crossref]

R. Perry, D. Hinton, R. Stuever, R. Perry, D. Hinton, and R. Stuever, “NASA wake vortex research for aircraft spacing,” in 35th Aerospace Sciences Meeting and Exhibit (1997), p. 57.
[Crossref]

Pichugina, E.

V. Banakh, I. Smalikho, E. Pichugina, and W. Brewer, “Representativeness of measurements of the dissipation rate of turbulence energy by scanning Doppler lidar,” Atmos. Oceanic Opt. 23(1), 48–54 (2010).
[Crossref]

Proctor, F.

F. Proctor, D. Hamilton, and J. Han, “Wake vortex transport and decay in ground effect-Vortex linking with the ground,” in 38th Aerospace Sciences Meeting and Exhibit (2000), p. 757.
[Crossref]

Pruis, M. J.

D. Jacob, D. Y. Lai, M. J. Pruis, and D. P. Delisi, “Assessment of WakeMod 4: A New Standalone Wake Vortex Algorithm for Estimating Circulation Strength and Position,” in 7th AIAA Atmospheric and Space Environments Conference (2015), p. 3176.
[Crossref]

D. Jacob, D. Y. Lai, M. J. Pruis, and D. P. Delisi, “Assessment of WakeMod 4: A New Standalone Wake Vortex Algorithm for Estimating Circulation Strength and Position,” in 7th AIAA Atmospheric and Space Environments Conference (2015), p. 3176.
[Crossref]

Rahm, S.

I. N. Smalikho, V. A. Banakh, F. Holzäpfel, and S. Rahm, “Method of radial velocities for the estimation of aircraft wake vortex parameters from data measured by coherent Doppler lidar,” Opt. Express 23(19), A1194–A1207 (2015).
[Crossref] [PubMed]

I. Smalikho and S. Rahm, “Lidar investigations of the effects of wind and atmospheric turbulence on an aircraft wake vortex,” Atmos. Oceanic Opt. 23(2), 137–146 (2010).
[Crossref]

S. Rahm and I. Smalikho, “Aircraft wake vortex measurement with airborne coherent Doppler lidar,” J. Aircr. 45(4), 1148–1155 (2008).
[Crossref]

I. Smalikho, F. Köpp, and S. Rahm, “Measurement of atmospheric turbulence by 2-μ m Doppler lidar,” J. Atmos. Ocean. Technol. 22(11), 1733–1747 (2005).
[Crossref]

F. Köpp, S. Rahm, and I. Smalikho, “Characterization of aircraft wake vortices by 2-μ m pulsed Doppler lidar,” J. Atmos. Ocean. Technol. 21(2), 194–206 (2004).
[Crossref]

Ramsey, D.

D. Ramsey and C. Nguyen, “Characterizing aircraft wake vortices with ground-based pulsed coherent Lidar: effects of vortex circulation strength and Lidar signal-to-noise ratio on the spectral signature,” in 3rd AIAA Atmospheric Space Environments Conference (2011), p. 3198.
[Crossref]

Robinson, P.

P. W. Chan, J. Wurman, and P. Robinson, “LIDAR ground-based velocity track display analyses and surface observations of a vortex shedding event observed at the Hong Kong International Airport on April 11, 2011,” Atmosfera 30(4), 275–285 (2017).
[Crossref]

Shald, S.

D. Jacob, D. Lai, D. Delisi, D. Hutton, K. Barr, S. Shald, S. Hannon, and P. Gatt, “Assessment of Lockheed Martin’s Aircraft Wake Vortex Circulation Estimation Algorithms Using Simulated Lidar Data,” in 3rd AIAA Atmospheric Space Environments Conference (2011), p. 3196.
[Crossref]

Sharman, R.

R. Frehlich and R. Sharman, “Maximum likelihood estimates of vortex parameters from simulated coherent Doppler lidar data,” J. Atmos. Ocean. Technol. 22(2), 117–130 (2005).
[Crossref]

Smalikho, I.

V. Banakh and I. Smalikho, “Lidar Studies of Wind Turbulence in the Stable Atmospheric Boundary Layer,” Remote Sens. 10(8), 1219 (2018).
[Crossref]

I. Smalikho and V. Banakh, “Measurements of wind turbulence parameters by a conically scanning coherent Doppler lidar in the atmospheric boundary layer,” Atmos. Meas. Tech. 10(11), 4191–4208 (2017).
[Crossref]

V. Banakh, I. Smalikho, E. Pichugina, and W. Brewer, “Representativeness of measurements of the dissipation rate of turbulence energy by scanning Doppler lidar,” Atmos. Oceanic Opt. 23(1), 48–54 (2010).
[Crossref]

I. Smalikho and S. Rahm, “Lidar investigations of the effects of wind and atmospheric turbulence on an aircraft wake vortex,” Atmos. Oceanic Opt. 23(2), 137–146 (2010).
[Crossref]

S. Rahm and I. Smalikho, “Aircraft wake vortex measurement with airborne coherent Doppler lidar,” J. Aircr. 45(4), 1148–1155 (2008).
[Crossref]

I. Smalikho, F. Köpp, and S. Rahm, “Measurement of atmospheric turbulence by 2-μ m Doppler lidar,” J. Atmos. Ocean. Technol. 22(11), 1733–1747 (2005).
[Crossref]

F. Köpp, S. Rahm, and I. Smalikho, “Characterization of aircraft wake vortices by 2-μ m pulsed Doppler lidar,” J. Atmos. Ocean. Technol. 21(2), 194–206 (2004).
[Crossref]

Smalikho, I. N.

Song, X.

X. Zhai, S. Wu, B. Liu, X. Song, and J. Yin, “Shipborne wind measurement and motion-induced error correction by coherent doppler lidar over yellow sea in 2014,” Atmos. Meas. Tech. 11(3), 1313–1331 (2018).
[Crossref]

Steen, M.

F. Holzäpfel and M. Steen, “Aircraft wake-vortex evolution in ground proximity: analysis and parameterization,” AIAA J. 45(1), 218–227 (2007).
[Crossref]

F. Holzäpfel and M. Steen, “Aircraft wake-vortex evolution in ground proximity: analysis and parameterization,” AIAA J. 45(1), 218–227 (2007).
[Crossref]

Stephan, A.

F. Holzäpfel, A. Stephan, T. Heel, and S. Körner, “Enhanced wake vortex decay in ground proximity triggered by plate lines,” Aircr. Eng. Aerosp. Technol. 88(2), 206–214 (2016).
[Crossref]

Stuever, R.

R. Perry, D. Hinton, R. Stuever, R. Perry, D. Hinton, and R. Stuever, “NASA wake vortex research for aircraft spacing,” in 35th Aerospace Sciences Meeting and Exhibit (1997), p. 57.
[Crossref]

R. Perry, D. Hinton, R. Stuever, R. Perry, D. Hinton, and R. Stuever, “NASA wake vortex research for aircraft spacing,” in 35th Aerospace Sciences Meeting and Exhibit (1997), p. 57.
[Crossref]

Stumpf, E.

F. Holzäpfel, T. Gerz, F. Köpp, E. Stumpf, M. Harris, R. I. Young, and A. Dolfi-Bouteyre, “Strategies for circulation evaluation of aircraft wake vortices measured by lidar,” J. Atmos. Ocean. Technol. 20(8), 1183–1195 (2003).
[Crossref]

Tafferner, A.

T. Gerz, F. Holzäpfel, W. Bryant, F. Köpp, M. Frech, A. Tafferner, and G. Winckelmans, “Research towards a wake-vortex advisory system for optimal aircraft spacing,” C. R. Phys. 6(4-5), 501–523 (2005).
[Crossref]

Wang, G.

Wang, Q.

H. Zhang, S. Wu, Q. Wang, B. Liu, B. Yin, and X. Zhai, “Airport low-level wind shear lidar observation at beijing capital international airport,” Infrared Phys. Technol. 96, 113–122 (2019).
[Crossref]

Wang, X.

Winckelmans, G.

T. Gerz, F. Holzäpfel, W. Bryant, F. Köpp, M. Frech, A. Tafferner, and G. Winckelmans, “Research towards a wake-vortex advisory system for optimal aircraft spacing,” C. R. Phys. 6(4-5), 501–523 (2005).
[Crossref]

Wu, S.

H. Zhang, S. Wu, Q. Wang, B. Liu, B. Yin, and X. Zhai, “Airport low-level wind shear lidar observation at beijing capital international airport,” Infrared Phys. Technol. 96, 113–122 (2019).
[Crossref]

X. Zhai, S. Wu, B. Liu, X. Song, and J. Yin, “Shipborne wind measurement and motion-induced error correction by coherent doppler lidar over yellow sea in 2014,” Atmos. Meas. Tech. 11(3), 1313–1331 (2018).
[Crossref]

X. Zhai, S. Wu, and B. Liu, “Doppler lidar investigation of wind turbine wake characteristics and atmospheric turbulence under different surface roughness,” Opt. Express 25(12), A515–A529 (2017).
[Crossref] [PubMed]

S. Wu, B. Liu, J. Liu, X. Zhai, C. Feng, G. Wang, H. Zhang, J. Yin, X. Wang, R. Li, and D. Gallacher, “Wind turbine wake visualization and characteristics analysis by Doppler lidar,” Opt. Express 24(10), A762–A780 (2016).
[Crossref] [PubMed]

Wurman, J.

P. W. Chan, J. Wurman, and P. Robinson, “LIDAR ground-based velocity track display analyses and surface observations of a vortex shedding event observed at the Hong Kong International Airport on April 11, 2011,” Atmosfera 30(4), 275–285 (2017).
[Crossref]

Xu, C.

M. Lin, W. Huang, Z. Zhang, C. Xu, and G. Cui, “Numerical study of aircraft wake vortex evolution near ground in stable atmospheric boundary layer,” Chin. J. Aeronauti. 30(6), 1866–1876 (2017).
[Crossref]

Yin, B.

H. Zhang, S. Wu, Q. Wang, B. Liu, B. Yin, and X. Zhai, “Airport low-level wind shear lidar observation at beijing capital international airport,” Infrared Phys. Technol. 96, 113–122 (2019).
[Crossref]

Yin, J.

X. Zhai, S. Wu, B. Liu, X. Song, and J. Yin, “Shipborne wind measurement and motion-induced error correction by coherent doppler lidar over yellow sea in 2014,” Atmos. Meas. Tech. 11(3), 1313–1331 (2018).
[Crossref]

S. Wu, B. Liu, J. Liu, X. Zhai, C. Feng, G. Wang, H. Zhang, J. Yin, X. Wang, R. Li, and D. Gallacher, “Wind turbine wake visualization and characteristics analysis by Doppler lidar,” Opt. Express 24(10), A762–A780 (2016).
[Crossref] [PubMed]

Young, R. I.

F. Holzäpfel, T. Gerz, F. Köpp, E. Stumpf, M. Harris, R. I. Young, and A. Dolfi-Bouteyre, “Strategies for circulation evaluation of aircraft wake vortices measured by lidar,” J. Atmos. Ocean. Technol. 20(8), 1183–1195 (2003).
[Crossref]

Zhai, X.

H. Zhang, S. Wu, Q. Wang, B. Liu, B. Yin, and X. Zhai, “Airport low-level wind shear lidar observation at beijing capital international airport,” Infrared Phys. Technol. 96, 113–122 (2019).
[Crossref]

X. Zhai, S. Wu, B. Liu, X. Song, and J. Yin, “Shipborne wind measurement and motion-induced error correction by coherent doppler lidar over yellow sea in 2014,” Atmos. Meas. Tech. 11(3), 1313–1331 (2018).
[Crossref]

X. Zhai, S. Wu, and B. Liu, “Doppler lidar investigation of wind turbine wake characteristics and atmospheric turbulence under different surface roughness,” Opt. Express 25(12), A515–A529 (2017).
[Crossref] [PubMed]

S. Wu, B. Liu, J. Liu, X. Zhai, C. Feng, G. Wang, H. Zhang, J. Yin, X. Wang, R. Li, and D. Gallacher, “Wind turbine wake visualization and characteristics analysis by Doppler lidar,” Opt. Express 24(10), A762–A780 (2016).
[Crossref] [PubMed]

Zhang, H.

H. Zhang, S. Wu, Q. Wang, B. Liu, B. Yin, and X. Zhai, “Airport low-level wind shear lidar observation at beijing capital international airport,” Infrared Phys. Technol. 96, 113–122 (2019).
[Crossref]

S. Wu, B. Liu, J. Liu, X. Zhai, C. Feng, G. Wang, H. Zhang, J. Yin, X. Wang, R. Li, and D. Gallacher, “Wind turbine wake visualization and characteristics analysis by Doppler lidar,” Opt. Express 24(10), A762–A780 (2016).
[Crossref] [PubMed]

Zhang, Z.

M. Lin, W. Huang, Z. Zhang, C. Xu, and G. Cui, “Numerical study of aircraft wake vortex evolution near ground in stable atmospheric boundary layer,” Chin. J. Aeronauti. 30(6), 1866–1876 (2017).
[Crossref]

M. Lin, G. Cui, and Z. Zhang, “A new vortex sheet model for simulating aircraft wake vortex evolution,” Chin. J. Aeronauti. 30(4), 1315–1326 (2017).
[Crossref]

AIAA J. (2)

F. Holzäpfel and M. Steen, “Aircraft wake-vortex evolution in ground proximity: analysis and parameterization,” AIAA J. 45(1), 218–227 (2007).
[Crossref]

F. Holzäpfel and M. Steen, “Aircraft wake-vortex evolution in ground proximity: analysis and parameterization,” AIAA J. 45(1), 218–227 (2007).
[Crossref]

Aircr. Eng. Aerosp. Technol. (1)

F. Holzäpfel, A. Stephan, T. Heel, and S. Körner, “Enhanced wake vortex decay in ground proximity triggered by plate lines,” Aircr. Eng. Aerosp. Technol. 88(2), 206–214 (2016).
[Crossref]

Atmos. Meas. Tech. (3)

X. Zhai, S. Wu, B. Liu, X. Song, and J. Yin, “Shipborne wind measurement and motion-induced error correction by coherent doppler lidar over yellow sea in 2014,” Atmos. Meas. Tech. 11(3), 1313–1331 (2018).
[Crossref]

N. Bodini, J. Lundquist, and R. Newsom, “Estimation of turbulence dissipation rate and its variability from sonic anemometer and wind Doppler lidar during the XPIA field campaign,” Atmos. Meas. Tech. 11(7), 4291–4308 (2018).
[Crossref]

I. Smalikho and V. Banakh, “Measurements of wind turbulence parameters by a conically scanning coherent Doppler lidar in the atmospheric boundary layer,” Atmos. Meas. Tech. 10(11), 4191–4208 (2017).
[Crossref]

Atmos. Oceanic Opt. (2)

V. Banakh, I. Smalikho, E. Pichugina, and W. Brewer, “Representativeness of measurements of the dissipation rate of turbulence energy by scanning Doppler lidar,” Atmos. Oceanic Opt. 23(1), 48–54 (2010).
[Crossref]

I. Smalikho and S. Rahm, “Lidar investigations of the effects of wind and atmospheric turbulence on an aircraft wake vortex,” Atmos. Oceanic Opt. 23(2), 137–146 (2010).
[Crossref]

Atmosfera (1)

P. W. Chan, J. Wurman, and P. Robinson, “LIDAR ground-based velocity track display analyses and surface observations of a vortex shedding event observed at the Hong Kong International Airport on April 11, 2011,” Atmosfera 30(4), 275–285 (2017).
[Crossref]

C. R. Phys. (1)

T. Gerz, F. Holzäpfel, W. Bryant, F. Köpp, M. Frech, A. Tafferner, and G. Winckelmans, “Research towards a wake-vortex advisory system for optimal aircraft spacing,” C. R. Phys. 6(4-5), 501–523 (2005).
[Crossref]

Chin. J. Aeronauti. (2)

M. Lin, W. Huang, Z. Zhang, C. Xu, and G. Cui, “Numerical study of aircraft wake vortex evolution near ground in stable atmospheric boundary layer,” Chin. J. Aeronauti. 30(6), 1866–1876 (2017).
[Crossref]

M. Lin, G. Cui, and Z. Zhang, “A new vortex sheet model for simulating aircraft wake vortex evolution,” Chin. J. Aeronauti. 30(4), 1315–1326 (2017).
[Crossref]

Infrared Phys. Technol. (1)

H. Zhang, S. Wu, Q. Wang, B. Liu, B. Yin, and X. Zhai, “Airport low-level wind shear lidar observation at beijing capital international airport,” Infrared Phys. Technol. 96, 113–122 (2019).
[Crossref]

J. Aircr. (2)

F. Holzäpfel, “Probabilistic two-phase wake vortex decay and transport model,” J. Aircr. 40, 323–331 (2003).
[Crossref]

S. Rahm and I. Smalikho, “Aircraft wake vortex measurement with airborne coherent Doppler lidar,” J. Aircr. 45(4), 1148–1155 (2008).
[Crossref]

J. Atmos. Ocean. Technol. (4)

F. Holzäpfel, T. Gerz, F. Köpp, E. Stumpf, M. Harris, R. I. Young, and A. Dolfi-Bouteyre, “Strategies for circulation evaluation of aircraft wake vortices measured by lidar,” J. Atmos. Ocean. Technol. 20(8), 1183–1195 (2003).
[Crossref]

F. Köpp, S. Rahm, and I. Smalikho, “Characterization of aircraft wake vortices by 2-μ m pulsed Doppler lidar,” J. Atmos. Ocean. Technol. 21(2), 194–206 (2004).
[Crossref]

I. Smalikho, F. Köpp, and S. Rahm, “Measurement of atmospheric turbulence by 2-μ m Doppler lidar,” J. Atmos. Ocean. Technol. 22(11), 1733–1747 (2005).
[Crossref]

R. Frehlich and R. Sharman, “Maximum likelihood estimates of vortex parameters from simulated coherent Doppler lidar data,” J. Atmos. Ocean. Technol. 22(2), 117–130 (2005).
[Crossref]

Opt. Express (4)

Opt. Lett. (1)

Prog. Aerosp. Sci. (1)

T. Gerz, F. Holzäpfel, and D. Darracq, “Commercial aircraft wake vortices,” Prog. Aerosp. Sci. 38(3), 181–208 (2002).
[Crossref]

Remote Sens. (1)

V. Banakh and I. Smalikho, “Lidar Studies of Wind Turbulence in the Stable Atmospheric Boundary Layer,” Remote Sens. 10(8), 1219 (2018).
[Crossref]

Other (16)

I. Smalikho and V. Banakh, “Investigation of feasibility of wind turbulence measurement by a pulsed coherent Doppler lidar in the atmospheric boundary layer,” In EPJ Web of Conferences (176, p. 06016), EDP Sciences (2018).
[Crossref]

S. S. Krause, Aircraft safety: accident investigations, analyses, and applications (McGraw-Hill New York, 2003).

F. Barbaresco, A. Jeantet, and U. Meier, “Wake vortex detection & monitoring by X-band Doppler radar: Paris Orly radar campaign results,” in Radar systems,2007IET international conference on (IET2007), pp. 1–5.

R. Perry, D. Hinton, R. Stuever, R. Perry, D. Hinton, and R. Stuever, “NASA wake vortex research for aircraft spacing,” in 35th Aerospace Sciences Meeting and Exhibit (1997), p. 57.
[Crossref]

D. A. Hinton, “An aircraft vortex spacing system (AVOSS) for dynamical wake vortex spacing criteria.” (1996).

D. Hinton, “An aircraft vortex spacing system (AVOSS) for dynamical wake vortex spacing criteria,” (1996).

D. Vicroy, P. Vijgen, H. Reimer, J. Gallegos, and P. Spalart, “Recent NASA wake-vortex flight tests, flow-physics database and wake-development analysis,” in AIAA and SAE,1998 World Aviation Conference (1998), p. 5592.

D. Jacob, D. Y. Lai, M. J. Pruis, and D. P. Delisi, “Assessment of WakeMod 4: A New Standalone Wake Vortex Algorithm for Estimating Circulation Strength and Position,” in 7th AIAA Atmospheric and Space Environments Conference (2015), p. 3176.
[Crossref]

S. Wu, B. Liu, and J. Liu, “Aircraft Wake Vortex Measurement with Coherent Doppler Lidar,” in EPJ Web of Conferences (EDP Sciences2016), p. 14008.
[Crossref]

J. Li, P. Chan, T. Wang, and X. Wang, “Circulation retrieval of wake vortex with a side-looking scanning Lidar,” in Radar (RADAR),2016CIE International Conference on (IEEE2016), pp. 1–4.
[Crossref]

D. Ramsey and C. Nguyen, “Characterizing aircraft wake vortices with ground-based pulsed coherent Lidar: effects of vortex circulation strength and Lidar signal-to-noise ratio on the spectral signature,” in 3rd AIAA Atmospheric Space Environments Conference (2011), p. 3198.
[Crossref]

D. Jacob, D. Lai, D. Delisi, D. Hutton, K. Barr, S. Shald, S. Hannon, and P. Gatt, “Assessment of Lockheed Martin’s Aircraft Wake Vortex Circulation Estimation Algorithms Using Simulated Lidar Data,” in 3rd AIAA Atmospheric Space Environments Conference (2011), p. 3196.
[Crossref]

V. Banakh and I. Smalikho, Coherent Doppler wind lidars in a turbulent atmosphere (Artech House, 2013).

F. Proctor, D. Hamilton, and J. Han, “Wake vortex transport and decay in ground effect-Vortex linking with the ground,” in 38th Aerospace Sciences Meeting and Exhibit (2000), p. 757.
[Crossref]

D. Jacob, D. Y. Lai, M. J. Pruis, and D. P. Delisi, “Assessment of WakeMod 4: A New Standalone Wake Vortex Algorithm for Estimating Circulation Strength and Position,” in 7th AIAA Atmospheric and Space Environments Conference (2015), p. 3176.
[Crossref]

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Supplementary Material (1)

NameDescription
» Visualization 1       The evolution animation of the radial velocity distribution of wake vortex affected area can be viewed in visualization 1.

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Figures (17)

Fig. 1
Fig. 1 (a) A schematic photograph of PCDL system Wind3D 6000 (b) lidar observational transverse mode: Range Height Indicator (RHI) (c) sketch map of wake vortex observation under NGE.
Fig. 2
Fig. 2 Flow chart of lidar observation and data batching process.
Fig. 3
Fig. 3 Wake vortex location determination (a) the two-dimensional radial velocity distribution when an A388 crossed the scanning plane during Jan. 31 2017 at BCIA (b) Corresponding function D v ( R k ;n).
Fig. 4
Fig. 4 (a) Left wake vortex spectrum distribution at fixed range bin and different elevation, (b) ambient spectrum distribution from scan measurement without wake vortex disturbance, (c) spectrum of left wake vortex and ambient at elevation angle of 7 .6 (above left wake vortex core position), (d) same as Fig. 4(c), but for elevation angle of 4 .0 (below left wake vortex core position).
Fig. 5
Fig. 5 (a) the spectrum difference obtained from the left wake vortex range bin and corresponding ambient measurement, (b) same as Fig. 5(a), but for right wake vortex.
Fig. 6
Fig. 6 (a) Spectrum taken from Fig. 5(a) for the case when data was measured above the left vortex core and selected minimal and maximal value of the radial velocity distribution in the sensing volume. (b) Radial velocity as a function of the range and elevation, the rea and black curves represent the ranges in front of and behind the wake vortex, respectively. (c) radial velocity as function of elevation angles in front of (red line) and behind (black line) the wake vortex, and the mean background wind velocity (blue line). The x-axis is elevation angle number l.
Fig. 7
Fig. 7 (a) Velocity envelopes along elevation angles within 8-11 (from top to bottom) range bins. The red (blue) curves show the positive (negative) envelopes corresponding to the maximal (minimal) value of the radial velocity distribution in the sensing volume. (b) the velocity envelope of left and right wake vortex before (dot-line) and after (solid line) background wind velocity subtraction. (c) circulation of a pair of wake vortex as a function of the radial distance to the core position.
Fig. 8
Fig. 8 (a) BH model fitting using PCDL measured data without NGE, (b) same as Fig. 8(a), but for the case with NGE. (c) simulated tangential velocity distribution before (blue) and after (red) scaling correction where PCDL scans downward and wake vortex moves downward (d) same as Fig. 8(c), but for the case when PCDL scans downward and wake vortex moves downward.
Fig. 9
Fig. 9 (a) The radial velocity distribution using RHI scanning mode (b) the mean horizontal wind component (c) The two-dimensional distribution of the mean radial velocity and (d) radial velocity fluctuation during 20:11-20:15 Jan. 23 2017 at BCIA without wake vortex disturbance.
Fig. 10
Fig. 10 Structure function estimates of turbulence using 20 RHI scans on 20:11-20:15 Jan. 23 2017 at BCIA with the height of 75 m. Curves shows calculations of the corrected structure function (black dots), the von Kármán model (black line), the Kolmogorov model (blue line) and the corrected von Kármán model (red line) taking the volume average effect of lidar detection into consideration.
Fig. 11
Fig. 11 The schematic diagram of lidar scanning, assuming the lidar scans from bottom to top and the wake vortex moves downward.
Fig. 12
Fig. 12 Scaling correction simulation at different lidar scanning velocity (a) (b), wake vortex vertical movement (c) (d), wake vortex location (e) (f).
Fig. 13
Fig. 13 (a) Trajectories of left (red squares) and right (black squares) wake vortex axes (see Visualization 1) (b) wake vortex vertical movement velocity (c) circulation evolution before scaling correction and (d) circulation evolution after scaling correction.
Fig. 14
Fig. 14 Spatiotemporal distributions of the (a) standard deviation of velocity (m/s) (b) crosswind velocity (m/s) (c) turbulence energy dissipation rate and (d) integral scale of turbulence obtained from measurements by the PCDL on 24 Jan. 2017 at BCIA.
Fig. 15
Fig. 15 (a) Spatiotemporal distribution of the parameter γ obtained from measurements by PCDL on 24 Jan 2017 at BCIA, (b) corresponding histogram of parameter γ.
Fig. 16
Fig. 16 Time averaged turbulence parameters (a) integral scale (b) TDER and (c) σ v during 00-06 LST (black dots), 09-18 LST (blue dots) and 19-24 LST (red dots), respectively.
Fig. 17
Fig. 17 Measurement results from selected heavy aircraft types on 24 Jan. 2017 at BCIA (a) the normalized distance between the cores of the wake vortex (b) the tilt angles of a pair of vortex (c) the normalized transverse distance (d) normalized transverse component of the vortex core movement speed (e) the normalized core altitude (f) normalized vertical component of the vortex core movement speed (g) normalized circulation for upward wake vortex and (h) normalized circulation for downward wake vortex.

Tables (4)

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Table 1 The specifications of the PCDL and wind profiler lidar.

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Table 2 Experimental configuration for RHI scanning mode.

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Table 3 Simulation parameters in determination of wake vortex circulation from PCDL measurement.

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Table 4 Specific parameters of different aircraft type used in statistics analysis.

Equations (25)

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D v ( R k )=| V max ( R k )|+| V min ( R k )|,
v 0 = Γ 2π ( r r 2 + r 0 2 ),
< V c (h) > E = ( N s L) 1 n=1 N s hδ< h kl <h+δ L V D ( h kl ,n) (cos φ l ) 1 ,
< V D ( R k , φ l ) > E =< V D ( h kl ) > E cos φ l ,
V D ' ( R k , φ l ,n)= V D ( R k , φ l ,n)< V D ( R k1 , φ l ) > E ,
D raw (s,h)= ( N s L) 1 n=1 N hδ< h kli <h+δ L D ^ raw ( r i , h kli ,n) ,
D e (s,h)= ( N s L) 1 n=1 N hδ< h kli <h+δ L D ^ e ( r i , h kli ,n) ,
D ^ raw ( r i , h kli ,n)=[ V D ' ( R k + r i , φ l ,n) V D ' ( R k , φ l ,n) ] 2 ,
D ^ e ( r i , h kli ,n)=[e( R k + r i , φ l ,n)e( R k , φ l ,n) ] 2 ,
D wgtcalculate (s)= D raw (s)- D e (s),
D wgtmodel (s)= ε 2/3 G s (s,ΔR, L i ),
G s (s,ΔR, L i )=0.497 C K s 2/3 0 dξ(1cosξ)exp[ (ξΔR/s) 2 /(2π)] [ ξ 2 + (0.746s/ L i ) 2 ] 5/6 ,
γ= { I 1 i=1 I [ D wgtcalculate (iΔr)/ D wgtmodel (iΔr)1] 2 } 1/2 ,
ε= [ 2 1/3 π 3 Γ(1/3)Γ(4/3) ] 3/2 σ 3 L 0 =0.933668 σ 3 L 0 ,
L i = π Γ(5/6) Γ(1/3) L 0 =0.7468343 L 0 ,
X 2 = X 0 +Δt V crosswind ,
Y 2 = Y 0 +Δt V wv ,
r t = ( X 2 X 1 ) 2 + ( Y 2 Y 1 ) 2 ,
ΔΓ( t 0 +Δt)=2π V t ( t 0 +Δt)Δr,
Δr= V wv Δt cos θ 0 ,
ΔΓ( t 0 +Δt)= 2π V t ( t 0 +Δt) V wv Δθ V scan cos θ 0 ,
b 0 =(π/4) B a ,
Γ 0 =Mg/(ρ b 0 V a ),
w 0 = Γ 0 /(2π b 0 ),
t 0 = b 0 / w 0 ,

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