Revisiting the formulations for the longitudinal velocity variance in the unstable atmospheric surface layer

2014 ◽  
Vol 141 (690) ◽  
pp. 1699-1711 ◽  
Author(s):  
T. Banerjee ◽  
G. G. Katul ◽  
S. T. Salesky ◽  
M. Chamecki
Keyword(s):  
Surface Layer ◽  
Atmospheric Surface Layer ◽  
Longitudinal Velocity ◽  
Velocity Variance

scholarly journals A Spectral Budget Model for the Longitudinal Turbulent Velocity in the Stable Atmospheric Surface Layer

2015 ◽  
Vol 73 (1) ◽  
pp. 145-166 ◽  
Author(s):  
Tirtha Banerjee ◽  
Dan Li ◽  
Jehn-Yih Juang ◽  
Gabriel Katul
Keyword(s):  
Surface Layer ◽  
Atmospheric Surface Layer ◽  
Longitudinal Velocity ◽  
Turbulent Velocity ◽  
Correction Function ◽  
Inertial Subrange ◽  
Temperature Profiles ◽  
Budget Model ◽  
The Mean ◽  
The Stability

Abstract A spectral budget model is developed to describe the scaling behavior of the longitudinal turbulent velocity variance with the stability parameter and the normalized height in an idealized stably stratified atmospheric surface layer (ASL), where z is the height from the surface, L is the Obukhov length, and δ is the boundary layer height. The proposed framework employs Kolmogorov’s hypothesis for describing the shape of the longitudinal velocity spectra in the inertial subrange, Heisenberg’s eddy viscosity as a closure for the pressure redistribution and turbulent transfer terms, and the Monin–Obukhov similarity theory (MOST) scaling for linking the mean longitudinal velocity and temperature profiles to ζ. At a given friction velocity , reduces with increasing ζ as expected. The model is consistent with the disputed z-less stratification when the stability correction function for momentum increases with increasing ζ linearly or as a power law with the exponent exceeding unity. For the Businger–Dyer stability correction function for momentum, which varies linearly with ζ, the limit of the z-less onset is . The proposed framework explains why does not follow MOST scaling even when the mean velocity and temperature profiles may follow MOST in the ASL. It also explains how δ ceases to be a scaling variable in more strongly stable (although well-developed turbulent) ranges.

Probability law of turbulent kinetic energy in the atmospheric surface layer

2021 ◽  
Vol 6 (7) ◽  
Author(s):  
Mohammad Allouche ◽  
Gabriel G. Katul ◽  
Jose D. Fuentes ◽  
Elie Bou-Zeid
Keyword(s):  
Surface Layer ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Atmospheric Surface Layer

scholarly journals Whirlwinds and Hairpins in the Atmospheric Surface Layer

2016 ◽  
Vol 73 (12) ◽  
pp. 4927-4943 ◽  
Author(s):  
Steven P. Oncley ◽  
Oscar Hartogensis ◽  
Chenning Tong
Keyword(s):  
Surface Layer ◽  
Atmospheric Surface Layer ◽  
Dust Devils ◽  
Hairpin Vortices ◽  
Structure And Dynamics ◽  
Fixed Array ◽  
Visual Observations

Abstract Vortices in the atmospheric surface layer are characterized using observations at unprecedented resolution from a fixed array of 31 turbulence sensors. During the day, these vortices likely are dust devils, though no visual observations are available for confirmation. At night, hairpin vortices appear to have been observed. The structure and dynamics of several types of vortices are described and related to other vortex investigations, including tornadoes and hurricanes.

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