Investigation of the pressure–strain-rate correlation and pressure fluctuations in convective and near neutral atmospheric surface layers
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 wal...
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description | 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 t |
doi_str_mv | 10.1017/jfm.2018.576 |
format | Article |
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$2048^{3}$
) 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.</description><identifier>ISSN: 0022-1120</identifier><identifier>EISSN: 1469-7645</identifier><identifier>DOI: 10.1017/jfm.2018.576</identifier><language>eng</language><publisher>Cambridge, UK: Cambridge University Press</publisher><subject>Anisotropy ; Atmospheric boundary layer ; Atmospheric models ; Behavior ; Buoyancy ; Coherence length ; Components ; Computer simulation ; Correlation ; Dynamics ; Eddies ; Fluctuations ; Fluid mechanics ; JFM Papers ; Large eddy simulation ; Length ; Modelling ; Oceanic eddies ; Physics ; Poisson equation ; Pressure ; Reflection ; Scaling ; Statistical methods ; Strain rate ; Studies ; Surface layers ; Velocity ; Wavelengths</subject><ispartof>Journal of fluid mechanics, 2018-11, Vol.854, p.88-120</ispartof><rights>2018 Cambridge University Press</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c302t-a51d2d81738f4d804bd648ea36c31248bd3e07a674951bddba6d7b8906a57fc43</citedby><cites>FETCH-LOGICAL-c302t-a51d2d81738f4d804bd648ea36c31248bd3e07a674951bddba6d7b8906a57fc43</cites><orcidid>0000-0002-3086-5027</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.cambridge.org/core/product/identifier/S0022112018005761/type/journal_article$$EHTML$$P50$$Gcambridge$$H</linktohtml><link.rule.ids>164,314,780,784,27924,27925,55628</link.rule.ids></links><search><creatorcontrib>Ding, Mengjie</creatorcontrib><creatorcontrib>Nguyen, Khuong X.</creatorcontrib><creatorcontrib>Liu, Shuaishuai</creatorcontrib><creatorcontrib>Otte, Martin J.</creatorcontrib><creatorcontrib>Tong, Chenning</creatorcontrib><title>Investigation of the pressure–strain-rate correlation and pressure fluctuations in convective and near neutral atmospheric surface layers</title><title>Journal of fluid mechanics</title><addtitle>J. Fluid Mech</addtitle><description>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.</description><subject>Anisotropy</subject><subject>Atmospheric boundary layer</subject><subject>Atmospheric models</subject><subject>Behavior</subject><subject>Buoyancy</subject><subject>Coherence length</subject><subject>Components</subject><subject>Computer simulation</subject><subject>Correlation</subject><subject>Dynamics</subject><subject>Eddies</subject><subject>Fluctuations</subject><subject>Fluid mechanics</subject><subject>JFM Papers</subject><subject>Large eddy simulation</subject><subject>Length</subject><subject>Modelling</subject><subject>Oceanic eddies</subject><subject>Physics</subject><subject>Poisson equation</subject><subject>Pressure</subject><subject>Reflection</subject><subject>Scaling</subject><subject>Statistical methods</subject><subject>Strain rate</subject><subject>Studies</subject><subject>Surface layers</subject><subject>Velocity</subject><subject>Wavelengths</subject><issn>0022-1120</issn><issn>1469-7645</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNptkLtOwzAUhi0EEqWw8QCWWEmwHcdORlRxqVSJBWbLsZ3WVW7YTqVu7Iy8IU-CexEsLOcM5zvf0fkBuMYoxQjzu3XdpgThIs05OwETTFmZcEbzUzBBiJAEY4LOwYX3a4Rwhko-AZ_zbmN8sEsZbN_BvoZhZeDgjPejM98fXz44abvEyWCg6p0zzYGUnf7FYN2MKoz7gYe2i2C0qmA3Zs91RrpYxqhqoAxt74eVcVbBuFxLZWAjt8b5S3BWy8abq2OfgrfHh9fZc7J4eZrP7heJyhAJicyxJrrAPCtqqgtEK81oYWTGVIYJLSqdGcQl47TMcaV1JZnmVVEiJnNeK5pNwc3BO7j-fYzfi3U_ui6eFIRgxnGJyh11e6CU6713phaDs610W4GR2MUtYtxiF7eIcUc8PeKyrZzVS_Nn_XfhB1rphy4</recordid><startdate>20181110</startdate><enddate>20181110</enddate><creator>Ding, Mengjie</creator><creator>Nguyen, Khuong X.</creator><creator>Liu, Shuaishuai</creator><creator>Otte, Martin J.</creator><creator>Tong, Chenning</creator><general>Cambridge University Press</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TB</scope><scope>7U5</scope><scope>7UA</scope><scope>7XB</scope><scope>88I</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8G5</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H8D</scope><scope>H96</scope><scope>HCIFZ</scope><scope>KR7</scope><scope>L.G</scope><scope>L6V</scope><scope>L7M</scope><scope>M2O</scope><scope>M2P</scope><scope>M7S</scope><scope>MBDVC</scope><scope>P5Z</scope><scope>P62</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>Q9U</scope><scope>S0W</scope><orcidid>https://orcid.org/0000-0002-3086-5027</orcidid></search><sort><creationdate>20181110</creationdate><title>Investigation of the pressure–strain-rate correlation and pressure fluctuations in convective and near neutral atmospheric surface layers</title><author>Ding, Mengjie ; Nguyen, Khuong X. ; Liu, Shuaishuai ; Otte, Martin J. ; Tong, Chenning</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c302t-a51d2d81738f4d804bd648ea36c31248bd3e07a674951bddba6d7b8906a57fc43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Anisotropy</topic><topic>Atmospheric boundary layer</topic><topic>Atmospheric models</topic><topic>Behavior</topic><topic>Buoyancy</topic><topic>Coherence length</topic><topic>Components</topic><topic>Computer simulation</topic><topic>Correlation</topic><topic>Dynamics</topic><topic>Eddies</topic><topic>Fluctuations</topic><topic>Fluid mechanics</topic><topic>JFM Papers</topic><topic>Large eddy simulation</topic><topic>Length</topic><topic>Modelling</topic><topic>Oceanic eddies</topic><topic>Physics</topic><topic>Poisson equation</topic><topic>Pressure</topic><topic>Reflection</topic><topic>Scaling</topic><topic>Statistical methods</topic><topic>Strain rate</topic><topic>Studies</topic><topic>Surface layers</topic><topic>Velocity</topic><topic>Wavelengths</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ding, Mengjie</creatorcontrib><creatorcontrib>Nguyen, Khuong X.</creatorcontrib><creatorcontrib>Liu, Shuaishuai</creatorcontrib><creatorcontrib>Otte, Martin J.</creatorcontrib><creatorcontrib>Tong, Chenning</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Water Resources Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>Aerospace Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>SciTech Premium Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>ProQuest Engineering Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Research Library</collection><collection>Science Database</collection><collection>Engineering Database</collection><collection>Research Library (Corporate)</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>ProQuest Central Basic</collection><collection>DELNET Engineering & Technology Collection</collection><jtitle>Journal of fluid mechanics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ding, Mengjie</au><au>Nguyen, Khuong X.</au><au>Liu, Shuaishuai</au><au>Otte, Martin J.</au><au>Tong, Chenning</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Investigation of the pressure–strain-rate correlation and pressure fluctuations in convective and near neutral atmospheric surface layers</atitle><jtitle>Journal of fluid mechanics</jtitle><addtitle>J. Fluid Mech</addtitle><date>2018-11-10</date><risdate>2018</risdate><volume>854</volume><spage>88</spage><epage>120</epage><pages>88-120</pages><issn>0022-1120</issn><eissn>1469-7645</eissn><abstract>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.</abstract><cop>Cambridge, UK</cop><pub>Cambridge University Press</pub><doi>10.1017/jfm.2018.576</doi><tpages>33</tpages><orcidid>https://orcid.org/0000-0002-3086-5027</orcidid></addata></record> |
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subjects | Anisotropy Atmospheric boundary layer Atmospheric models Behavior Buoyancy Coherence length Components Computer simulation Correlation Dynamics Eddies Fluctuations Fluid mechanics JFM Papers Large eddy simulation Length Modelling Oceanic eddies Physics Poisson equation Pressure Reflection Scaling Statistical methods Strain rate Studies Surface layers Velocity Wavelengths |
title | Investigation of the pressure–strain-rate correlation and pressure fluctuations in convective and near neutral atmospheric surface layers |
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