Wind–Temperature Regime and Wind Turbulence in a Stable Boundary Layer of the Atmosphere: Case Study

Abstract

The paper presents the results of probing the stable atmospheric boundary layer in the coastal zone of Lake Baikal with a coherent Doppler wind lidar and a microwave temperature profiler. Two-dimensional height–temporal distributions of the wind velocity vector components, temperature, and parameters characterizing atmospheric stability and wind turbulence were obtained. The parameters of the low-level jets and the atmospheric waves arising in the stable boundary layer were determined. It was shown that the stable atmospheric boundary layer has an inhomogeneous fine scale layered structure characterized by strong variations of the Richardson number Ri. Layers with large Richardson numbers alternate with layers where Ri is less than the critical value of the Richardson number Ricr = 0.25. The channels of decreased stability, where the conditions are close to neutral stratification 0 < Ri < 0.25, arise in the zone of the low-level jets. The wind turbulence in the central part of the observed jets, where Ri > Ricr, is weak, increases considerably to the periphery of jets, at heights where Ri < Ricr. The turbulence may intensify at the appearance of internal atmospheric waves.

Estimation of the height of the turbulent mixing layer from data of Doppler lidar measurements using conical scanning by a probe beam

“…The results shown in Fig. 6 do not contradict the known experimental data relative to estimates of the absolute values of the mixing layer height at different times of the day and night (Tucker et al, 2009;Barlow et al, 2011;Vakkari et al, 2015;Huang et al, 2017;Bonin et al, 2018;Manninen et al, 2018). Nevertheless, we made an attempt to determine the accuracy of the lidar estimate of the mixing layer height for conditions of this experiment.…”

“…There are different technical facilities that are widely used for turbulent parameter estimation in the atmospheric boundary layer (ABL) and determining the mixing layer height. Doppler sodars, radio acoustic systems, and Doppler lidars are the most suitable for this task, as they allow for meteorological data to be measured in real time with the required space and time resolution (Bonin et al, 2018;Emeis et al, 2008;Hogan et al, 2009;Tucker et al, 2009;Pichugina and Banta, 2010;Barlow et al, 2011;Helmis et al, 2012;Schween et al, 2014;Vakkari et al, 2015;Huang et al, 2017;Petenko et al, 2019). From the data of lidar measurements, the variance of radial velocity σ 2 r (h), variances of vertical σ 2 w (h) and horizontal σ 2 u (h) and σ 2 v (h) wind vector components, turbulence kinetic energy (TKE) E(h), and turbulent energy dissipation rate ε(h) can be estimated at different heights h.…”

“…In Bonin et al (2018), Hogan et al (2009), Tucker et al (2009), Pichugina and Banta (2010), Barlow et al (2011), Schween et al (2014), Vakkari et al (2015), and Huang et al (2017), the mixing layer height (MLH) h mix was determined from the decrease in the variance σ 2 α (h) (α = r, w, u, v are indexes for designating the radial, vertical, and two horizontal components of wind velocity vector, respectively) with height h down to some minimum threshold value σ 2 α (h mix ) = Thr α , at which the turbulence intensity becomes insufficient for efficient air mixing. The variances and MLH were estimated from pulsed coherent Doppler lidar (PCDL) V. A. Banakh et al: MLH estimation from PCDL and temperature profiler data data through the use of various measurement strategies and data processing algorithms (Bonin et al, 2018;Hogan et al, 2009;Tucker et al, 2009;Pichugina and Banta, 2010;Barlow et al, 2011;Schween et al, 2014;Vakkari et al, 2015;Huang et al, 2017;Manninen et al, 2018): (i) in the fixed strictly vertical direction of the probing beam (vertical stare mode), (ii) by scanning in vertical plane, and (iii) by conical scanning by a beam around the vertical axis at a certain elevation angle ϕ. In Bonin et al (2018), the "composite fuzzy logic approach" based on the use of all three measurement geometries was applied to determine h mix .…”

Spatiotemporal Dynamics of the Kinetic Energy in the Atmospheric Boundary Layer from Minisodar Measurements

“…A number of remote sensing methods of the wind velocity have been developed with application of lidars, radars, and sodars [4][5][6][7]. Thus, in [8] a coherent wind lidar was used to study the spatiotemporal distribution of the wind velocity and its variance in the stable atmospheric boundary layer at altitudes of 100-500 m. The SLODAR method [9][10][11] of remote determination of the wind speed and turbulent characteristics above large telescopes in the daytime should also be mentioned here.…”

Estimation of the height of turbulent mixing layer from data of Doppler lidar measurements using conical scanning by a probe beam

“…CC BY 4.0 License. energy dissipation rate () h  remains reliable even during the appearance of IGWs with quite a high amplitude of harmonic oscillations of wind vector components (Banakh and Smalikho, 2018;Banakh et al, 2020).…”