Articles | Volume 8, issue 2
Research article
12 Feb 2015
Research article |  | 12 Feb 2015

A six-beam method to measure turbulence statistics using ground-based wind lidars

A. Sathe, J. Mann, N. Vasiljevic, and G. Lea

Related authors

Evaluation of three lidar scanning strategies for turbulence measurements
Jennifer F. Newman, Petra M. Klein, Sonia Wharton, Ameya Sathe, Timothy A. Bonin, Phillip B. Chilson, and Andreas Muschinski
Atmos. Meas. Tech., 9, 1993–2013,,, 2016
Short summary

Related subject area

Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Validation and Intercomparisons
Atmospheric motion vector (AMV) error characterization and bias correction by leveraging independent lidar data: a simulation using an observing system simulation experiment (OSSE) and optical flow AMVs
Hai Nguyen, Derek Posselt, Igor Yanovsky, Longtao Wu, and Svetla Hristova-Veleva
Atmos. Meas. Tech., 17, 3103–3119,,, 2024
Short summary
Rotary-wing drone-induced flow – comparison of simulations with lidar measurements
Liqin Jin, Mauro Ghirardelli, Jakob Mann, Mikael Sjöholm, Stephan Thomas Kral, and Joachim Reuder
Atmos. Meas. Tech., 17, 2721–2737,,, 2024
Short summary
Application of Doppler sodar in short-term forecasting of PM10 concentration in the air in Krakow (Poland)
Ewa Agnieszka Krajny, Leszek Ośródka, and Marek Jan Wojtylak
Atmos. Meas. Tech., 17, 2451–2464,,, 2024
Short summary
Radiative closure tests of collocated hyperspectral microwave and infrared radiometers
Lei Liu, Natalia Bliankinshtein, Yi Huang, John R. Gyakum, Philip M. Gabriel, Shiqi Xu, and Mengistu Wolde
Atmos. Meas. Tech., 17, 2219–2233,,, 2024
Short summary
Effects of clouds and aerosols on downwelling surface solar irradiance nowcasting and short-term forecasting
Kyriakoula Papachristopoulou, Ilias Fountoulakis, Alkiviadis F. Bais, Basil E. Psiloglou, Nikolaos Papadimitriou, Ioannis-Panagiotis Raptis, Andreas Kazantzidis, Charalampos Kontoes, Maria Hatzaki, and Stelios Kazadzis
Atmos. Meas. Tech., 17, 1851–1877,,, 2024
Short summary

Cited articles

Banakh, V. A. and Smalikho, I. N.: Determination of the turbulent energy dissipation rate from lidar sensing data, Atmos. Ocean. Opt., 10, 295–302, 1997a.
Banakh, V. A. and Smalikho, I. N.: Estimation of the turbulence energy dissipation rate from the pulsed Doppler lidar data, Atmos. Ocean. Opt., 10, 957–965, 1997b.
Banakh, V. A. and Werner, C.: Computer simulation of coherent Doppler lidar measurement of wind velocity and retrieval of turbulent wind statistics, Opt. Eng., 44, 071205,, 2005.
Banakh, V. A., Smalikho, I. N., Köpp, F., and Werner, C.: Representativeness of wind measurements with a CW Doppler lidar in the atmospheric boundary layer, Appl. Opt., 34, 2055–2067,, 1995a.
Banakh, V. A., Werner, C., Kerkis, N. N., Köpp, F., and Smalikho, I. N.: Turbulence measurements with a CW Doppler lidar in the atmospheric boundary layer, Atmos. Ocean. Opt., 8, 955–959, 1995b.
Short summary
A so-called six-beam method is proposed to measure atmospheric turbulence using a ground-based wind lidar. This method is presented as an alternative to the so-called velocity azimuth display (VAD) method that is routinely used in commercial wind lidars, and which usually results in significant averaging effects of measured turbulence.