Access the full text.
Sign up today, get DeepDyve free for 14 days.
J. F. Barlow, T. M. Dunbar, E. G. Nemitz, C. R. Wood, M. W. Gallagher, F. Davies, E. O’Connor, R. M. Harrison (2011)
Boundary layer dynamics over London, UK, as observed using Doppler lidar during REPARTEE-IIAtmos. Chem. Phys., 11
V. A. Banakh, I. N. Smalikho, A. V. Falits, A. M. Sherstobitov (2021)
Estimating the parameters of wind turbulence from spectra of radial velocity measured by a pulsed Doppler lidarRemote Sens., 13
S. Tucker, C. Senff, A. Weickmann, W. Brewer, R. Banta, S. Sandberg, D. Law, R. Hardesty (2009)
Doppler Lidar Estimation of Mixing Height Using Turbulence, Shear, and Aerosol ProfilesJournal of Atmospheric and Oceanic Technology, 26
Y. Pichugina, R. Banta (2010)
Stable Boundary Layer Depth from High-Resolution Measurements of the Mean Wind ProfileJournal of Applied Meteorology and Climatology, 49
R. Hogan, A. Grant, A. Illingworth, G. Pearson, E. O'connor (2009)
Vertical velocity variance and skewness in clear and cloud‐topped boundary layers as revealed by Doppler lidarQuarterly Journal of the Royal Meteorological Society, 135
(2018)
Doppler lidar observation of the mixing height in Indianapolis using an automated composite fuzzy logic approach
(2014)
From case studies to long-term assessment,” Atmos
C. Helmis, G. Sgouros, M. Tombrou, Klaus Schäfer, C. Münkel, E. Bossioli, A. Dandou (2012)
A Comparative Study and Evaluation of Mixing-Height Estimation Based on Sodar-RASS, Ceilometer Data and Numerical Model SimulationsBoundary-Layer Meteorology, 145
J. Schween, A. Hirsikko, U. Löhnert, S. Crewell (2014)
Mixing-layer height retrieval with ceilometer and Doppler lidar: from case studies to long-term assessmentAtmospheric Measurement Techniques, 7
A. Grachev, E. Andreas, C. Fairall, P. Guest, P. Persson (2012)
The Critical Richardson Number and Limits of Applicability of Local Similarity Theory in the Stable Boundary LayerBoundary-Layer Meteorology, 147
H. Baumert, H. Peters (2008)
Turbulence closure: turbulence, waves and the wave-turbulence transition – Part 1: Vanishing mean shearOcean Science, 5
V. Banakh, I. Smalikho, A. Falits (2021)
Estimation of the height of the turbulent mixing layer from data of Doppler lidar measurements using conical scanning by a probe beamAtmospheric Measurement Techniques, 14
V. Banakh, I. Smalikho, A. Falits (2020)
Wind-Temperature Regime and Wind Turbulence in a Stable Boundary Layer of the Atmosphere: Case StudyRemote. Sens., 12
V. Vakkari, E. O'connor, A. Nisantzi, R. Mamouri, D. Hadjimitsis (2014)
Low-level mixing height detection in coastal locations with a scanning Doppler lidarAtmospheric Measurement Techniques, 8
Meng Huang, Zhiqiu Gao, Shiguang Miao, Fei Chen, M. Lemone, Ju Li, Fei Hu, Linlin Wang (2017)
Estimate of Boundary-Layer Depth Over Beijing, China, Using Doppler Lidar Data During SURF-2015Boundary-Layer Meteorology, 162
F. Gibert, N. Arnault, J. Cuesta, R. Plougonven, P. Flamant (2011)
Internal gravity waves convectively forced in the atmospheric residual layer during the morning transitionQuarterly Journal of the Royal Meteorological Society, 137
V. Banakh, I. Smalikho, A. Falits, A. Sherstobitov (2021)
Estimating the parameters of wind turbulence from spectra of radial velocity measured by a pulsed Doppler lidarIOP Conference Series: Earth and Environmental Science, 1040
I. Smalikho, V. Banakh (2017)
Measurements of wind turbulence parameters by a conically scanning coherent Doppler lidar in the atmospheric boundary layerAtmospheric Measurement Techniques Discussions, 10
F. Barlow, T. Dunbar, E. Nemitz, C. Wood, M. Gallagher, F. Davies, E. O'connor, R. Harrison (2011)
of Birmingham Boundary layer dynamics over London, UK, as observed using Doppler lidar during REPARTEE-II
I. Petenko, S. Argentini, G. Casasanta, C. Genthon, M. Kallistratova (2019)
Stable Surface-Based Turbulent Layer During the Polar Winter at Dome C, Antarctica: Sodar and In Situ ObservationsBoundary-Layer Meteorology, 171
(2020)
Case study,” Remote Sens
(2021)
Determination of the height of the turbulent mixing air layer based on estimation of the parameters of wind turbulence from lidar dataОптика атмосферы и океана
E. O'connor, A. Illingworth, I. Brooks, C. Westbrook, R. Hogan, F. Davies, B. Brooks (2010)
A Method for Estimating the Turbulent Kinetic Energy Dissipation Rate from a Vertically Pointing Doppler Lidar, and Independent Evaluation from Balloon-Borne In Situ MeasurementsJournal of Atmospheric and Oceanic Technology, 27
Time series of the turbulent mixing layer altitude derived from the altitude-time distributions of the turbulence kinetic energy dissipation rate and of the gradient Richardson number are compared. We have found that the estimates of the turbulent mixing layer altitude from the altitude-time distributions of the Richardson number and of the turbulence kinetic energy dissipation rate are close only under the conditions of atmospheric boundary layer instability due to convection. In other cases, the mixing layer altitude derived from the Richardson number can be significantly underestimated.
Atmospheric and Oceanic Optics – Springer Journals
Published: Feb 1, 2023
Keywords: wind lidar; temperature profiler; turbulent mixing layer altitude; Richardson number; turbulent energy dissipation rate
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.