Measurements of the budgets of the subgrid-scale stress and temperature flux in a convective atmospheric surface layer

2013 ◽  
Vol 729 ◽  
pp. 388-422 ◽  
Author(s):  
Khuong X. Nguyen ◽  
Thomas W. Horst ◽  
Steven P. Oncley ◽  
Chenning Tong
Keyword(s):  
Surface Layer ◽  
Strain Rate ◽  
Atmospheric Surface Layer ◽  
Pressure Sensors ◽  
Sensor Arrays ◽  
Field Measurements ◽  
Subgrid Scale ◽  
Scalar Flux ◽  
Surface Layers ◽  
Rate Correlation

AbstractThe dynamics of the subgrid-scale (SGS) stress and scalar flux in the convective atmospheric surface layer are studied through the budgets of the SGS turbulence kinetic energy (TKE), the SGS stress and the SGS temperature flux using field measurements from the Advection Horizontal Array Turbulence Study (AHATS). The array technique, which employs sensor arrays to perform filter operations to obtain the SGS velocity and temperature, is extended to include pressure sensors to measure the fluctuating pressure, enabling separation of the resolvable- and subgrid-scale pressure, and therefore for the first time allowing for measurement of the pressure covariance terms and the full SGS budgets. The non-dimensional forms of the SGS budget terms are obtained as functions of the stability parameter $z/ L$ and the ratio of the wavelength of the spectral peak of the vertical velocity to the filter width, ${\Lambda }_{w} / {\Delta }_{f} $. The results show that the SGS TKE budget is a balance among the production, transport and dissipation. The SGS shear stress budget and the SGS temperature flux budgets are dominated by the production and pressure destruction, with the latter causing return to isotropy. The budgets of the SGS normal stress components are more complex. Most notably the pressure–strain-rate correlation includes two competing processes, return to isotropy and generation of anisotropy, the latter due to ground blockage of the large convective eddies. For neutral surface layers, return to isotropy dominates. For unstable surface layers return to isotropy dominates for small filter widths, whereas for large filter widths the ground blockage effect dominates, resulting in strong anisotropy. The results in the present study, particularly for the pressure–strain-rate correlation, have strong implications for modelling the SGS stress and flux using their transport equations in the convective atmospheric boundary layer.

Investigation of subgrid-scale physics in the convective atmospheric surface layer using the budgets of the conditional mean subgrid-scale stress and temperature flux

2015 ◽  
Vol 772 ◽  
pp. 295-329 ◽  
Author(s):  
Khuong X. Nguyen ◽  
Chenning Tong
Keyword(s):  
Surface Layer ◽  
Strain Rate ◽  
Atmospheric Surface Layer ◽  
Wall Pressure ◽  
Subgrid Scale ◽  
Surface Layers ◽  
Conditional Mean ◽  
Stress Components ◽  
Pressure Transport ◽  
Rate Correlation

The subgrid-scale (SGS) physics in the convective atmospheric surface layer is studied using the SGS stress and SGS scalar flux. We derive the budget equations for the conditional mean SGS stress and SGS temperature flux and show that, for transport-equation-based SGS models, the budget terms must be correctly predicted by the SGS model in order for large-eddy simulation (LES) to reproduce the resolvable-scale velocity and temperature probability density functions. Field data from the Advection Horizontal Array Turbulence Study, which notably includes measurements of the fluctuating pressure and the advection of the velocity and temperature fields, are then used to analyse the budget equations. The results reveal the complex behaviour of the dynamics of the convective atmospheric surface layer. The budgets of the conditional mean SGS shear stress and SGS temperature flux are an approximate balance between the conditional mean production and pressure destruction, with the latter causing return to isotropy. The budgets of the normal SGS stress components are more complex. For strongly convective surface layers, energy is redistributed from the (smaller) vertical to the (larger) horizontal stress components during downdrafts, resulting in generation of anisotropy by the conditional mean SGS pressure–strain-rate correlation; wall pressure reflections can also enhance the anisotropy. The conditional mean SGS pressure transport, meanwhile, is a significant source of energy during updrafts as a result of the near-wall pressure minima. The vertical advection also plays a significant role in the transfer of SGS energy. For weakly convective surface layers, pressure transport is small while the SGS pressure–strain-rate correlation reverts to its usual role of causing return to isotropy. The results of the present study, particularly for the conditional mean SGS pressure–strain-rate correlation, provide new insights into the SGS physics first educed in a recent analysis of the mean SGS budgets by Nguyen et al. (J. Fluid Mech., vol. 729, 2013, pp. 388–422) and have important implications for near-wall models utilizing SGS transport equations in the convective atmospheric surface layer.

Investigation of the pressure–strain-rate correlation and pressure fluctuations in convective and near neutral atmospheric surface layers

2018 ◽  
Vol 854 ◽  
pp. 88-120 ◽  
Author(s):  
Mengjie Ding ◽  
Khuong X. Nguyen ◽  
Shuaishuai Liu ◽  
Martin J. Otte ◽  
Chenning Tong
Keyword(s):  
Surface Layer ◽  
Strain Rate ◽  
Mixed Layer ◽  
Free Space ◽  
Coherence Length ◽  
Pressure Fluctuations ◽  
Neutral Surface ◽  
Surface Layers ◽  
Neutral Surface Layer ◽  
Rate Correlation

The pressure–strain-rate correlation and pressure fluctuations in convective and near neutral atmospheric surface layers are investigated. Their scaling properties, spectral characteristics, the contributions from the different source terms in the pressure Poisson equation and the effects of the wall are investigated using high-resolution (up to $2048^{3}$) large-eddy simulation fields and through spectral predictions. The pressure–strain-rate correlation was found to have the mixed-layer and surface-layer scaling in the strongly convective and near neutral atmospheric surface layers, respectively. Its apparent surface-layer scaling in the moderately convective surface layer is due to the slow variations of the mixed-layer contribution, and is an inherent problem for single-point statistics in a multi-scale surface layer. In the strongly convective surface layer the pressure spectrum has an approximate $k^{-5/3}$ scaling range for small wavenumbers ($kz\ll 1$) due to the turbulent–turbulent contribution, and does not follow the surface-layer scaling, where $k$ and $z$ are the horizontal wavenumber and the distance from the surface respectively. The pressure–strain-rate cospectrum components have a $k^{-1}$ scaling range, consistent with our prediction using the surface layer parameters. It is dominated by the buoyancy contribution. Thus the anisotropy in the surface layer is due to the energy redistribution caused by the density fluctuations of the large eddies, rather than the turbulent–turbulent (inertial) effects. In the near neutral surface layer, the turbulent–turbulent and rapid contributions are primarily responsible for redistribution of energy from the streamwise velocity component to the vertical and spanwise components, respectively. The pressure–strain-rate cospectra peak near $kz\sim 1$, and have some similarities to those in the strongly convective surface layer for $kz\ll 1$. For the moderately convective surface layer, the pressure–strain-rate cospectra change signs at scales of the order of the Obukhov length, thereby imposing it as a horizontal length scale in the surface layer. This result provides strong support to the multipoint Monin–Obukhov similarity recently proposed by Tong & Nguyen (J. Atmos. Sci., vol. 72, 2015, pp. 4337–4348). We further decompose the pressure into the free-space (infinite domain), the wall reflection and the harmonic contributions. In the strongly convective surface layer, the free-space contribution to the pressure–strain-rate correlation is dominated by the buoyancy part, and is the main cause of the surface-layer anisotropy. The wall reflection enhances the anisotropy for most of the surface layer, suggesting that the pressure source has a large coherence length. In the near neutral surface layer, the wall reflection is small, suggesting a much smaller source coherence length. The present study also clarifies the understanding of the role of the turbulent–turbulent pressure, and has implications for understanding the dynamics and structure as well as modelling the atmospheric surface layer.

scholarly journals An Extremum Solution of the Monin–Obukhov Similarity Equations

2010 ◽  
Vol 67 (2) ◽  
pp. 485-499 ◽  
Author(s):  
Jingfeng Wang ◽  
Rafael L. Bras
Keyword(s):  
Surface Layer ◽  
Atmospheric Surface Layer ◽  
Turbulent Transport ◽  
Asymptotic Properties ◽  
Field Measurements ◽  
Surface Heat ◽  
Heat Fluxes ◽  
Obukhov Length ◽  
Surface Heat Fluxes ◽  
Momentum And Heat Fluxes

Abstract An extremum hypothesis of turbulent transport in the atmospheric surface layer is postulated. The hypothesis has led to a unique solution of Monin–Obukhov similarity equations in terms of simple expressions linking shear stress (momentum flux) and heat flux to mean wind shear and temperature gradient. The extremum solution is consistent with the well-known asymptotic properties of the surface layer. Validation of the extremum solution has been made by comparison to field measurements of momentum and heat fluxes. Furthermore, a modeling test of predicting surface heat fluxes using the results of this work is presented. A critical reexamination of the interpretation of the Obukhov length is given.

scholarly journals Resolvable- and Subgrid-Scale Measurement in the Atmospheric Surface Layer: Technique and Issues

1998 ◽  
Vol 55 (20) ◽  
pp. 3114-3126 ◽  
Author(s):  
Chenning Tong ◽  
John C. Wyngaard ◽  
Samir Khanna ◽  
James G. Brasseur
Keyword(s):  
Surface Layer ◽  
Atmospheric Surface Layer ◽  
Subgrid Scale ◽  
Layer Technique

scholarly journals A Priori Field Study of the Subgrid-Scale Heat Fluxes and Dissipation in the Atmospheric Surface Layer

2001 ◽  
Vol 58 (18) ◽  
pp. 2673-2698 ◽  
Author(s):  
Fernando Porté-Agel ◽  
Marc B. Parlange ◽  
Charles Meneveau ◽  
William E. Eichinger
Keyword(s):  
Surface Layer ◽  
Field Study ◽  
Atmospheric Surface Layer ◽  
A Priori ◽  
Heat Fluxes ◽  
Subgrid Scale

Investigation of the subgrid-scale fluxes and their production rates in a convective atmospheric surface layer using measurement data

2010 ◽  
Vol 660 ◽  
pp. 282-315 ◽  
Author(s):  
QINGLIN CHEN ◽  
SHUAISHUAI LIU ◽  
CHENNING TONG
Keyword(s):  
Surface Layer ◽  
Production Rate ◽  
Atmospheric Surface Layer ◽  
Potential Temperature ◽  
Measurement Data ◽  
Temperature Fluctuations ◽  
Positive Temperature ◽  
Subgrid Scale ◽  
Mean Values ◽  
Conditional Statistics

The subgrid-scale (SGS) potential temperature flux and stress in the atmospheric surface layer are studied using field measurement data. We analyse the mean values of the SGS temperature flux, the SGS temperature flux production rate, the SGS temperature variance production rate, the SGS stress and the SGS stress production rate conditional on both the resolvable-scale velocity and temperature, which must be reproduced by SGS models for large-eddy simulation to reproduce the one-point resolvable-scale velocity–temperature joint probability density function (JPDF). The results show that the conditional statistics generally depend on the resolvable-scale velocity and temperature fluctuations, indicating that these conditional variables have strong influences on the resolvable-scale statistics. The dependencies of the conditional SGS stress and the SGS stress production rate, which are partly due to the effects of flow history and buoyancy, suggest that model predictions of the SGS stress also affect the resolvable-scale temperature statistics. The results for the conditional flux and the conditional flux production rate vectors have similar trends. These conditional vectors are also well aligned. The positive temperature fluctuations associated with updrafts are found to have a qualitatively different influence on the conditional statistics than the negative temperature fluctuations associated with downdrafts. The conditional temperature flux and the temperature flux production rate predicted using several SGS models are compared with measurements in statistical a priori tests. The predictions using the nonlinear model are found to be closely related to the predictions using the Smagorinsky model. Several potential effects of the SGS model deficiencies on the resolvable-scale statistics, such as the overprediction of the vertical mean temperature gradient and the underprediction of the vertical temperature flux, are identified. The results suggest that efforts to improve the LES prediction of a resolvable-scale statistic must consider all the relevant SGS components identified using the JPDF equation and the surface layer dynamics. This study also provides impetus for further investigations of the JPDF equation, especially analytical studies on the relationship between the JPDF and the SGS terms that govern its evolution.

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