Horizontal Correlation Functions of Wind Fluctuations in the Mesosphere and Lower Thermosphere
Measurements of kinetic energy in vortical and divergent fluctuations in the mesosphere and lower thermosphere can be used to study stratified turbulence (ST) and gravity waves. This can be done using horizontal correlation functions of the fluctuating component of velocity. This study introduces a...
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description | Measurements of kinetic energy in vortical and divergent fluctuations in the mesosphere and lower thermosphere can be used to study stratified turbulence (ST) and gravity waves. This can be done using horizontal correlation functions of the fluctuating component of velocity. This study introduces a novel method for estimating these correlation functions using radars that observe Doppler shifts of ionized specular meteor trails. The technique solves the correlation functions directly on a longitudinal‐transverse‐up coordinate system, assuming axial symmetry. This procedure is more efficient and leads to smaller uncertainties than a previous approach. The new technique is applied to a year‐long data set from a multistatic specular meteor radar network in Germany, to study the annual variability of kinetic energy within turbulent fluctuations at 87–93 km of altitude. In monthly averages, the kinetic energy is found to be nearly equipartitioned between vortical and divergent modes. Turbulent fluctuations maximize during the winter months with approximately 25% more energy in these months than at other times. The horizontal correlation functions are in agreement with the inertial subrange of ST, exhibiting a 2/3 power law in the horizontal lag direction, with an outermost scale of ST to be about 380 km. This suggests that horizontal correlation functions could be used to estimate turbulent energy transfer rates.
Plain Language Summary
Flows exhibit a phenomenon called turbulence, which transfers energy from large scales into smaller scales. This effect is important to quantify the energy budget of the Earth's upper atmosphere. The range of length scales where this phenomenon occurs is called the inertial subrange of turbulence. The classical theory of isotropic turbulence predicts that this energy transfer occurs on length scales smaller than ∼100 m, at 60–110 km altitude. Recent work has shown that horizontal velocity fluctuations can extend the inertial subrange to length scales of up to hundreds of kilometers horizontally. This type of turbulence is called stratified turbulence (ST). So far no comprehensive study has been made to experimentally examine ST in the mesosphere and lower thermosphere (MLT) region on horizontal mesoscales. This study introduces a method for doing so by measuring how the wind fluctuations are correlated as a function of horizontal separation. This is achieved by using meteor radar measurements. The technique is applied to a year‐lo |
doi_str_mv | 10.1029/2022JD038092 |
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Plain Language Summary
Flows exhibit a phenomenon called turbulence, which transfers energy from large scales into smaller scales. This effect is important to quantify the energy budget of the Earth's upper atmosphere. The range of length scales where this phenomenon occurs is called the inertial subrange of turbulence. The classical theory of isotropic turbulence predicts that this energy transfer occurs on length scales smaller than ∼100 m, at 60–110 km altitude. Recent work has shown that horizontal velocity fluctuations can extend the inertial subrange to length scales of up to hundreds of kilometers horizontally. This type of turbulence is called stratified turbulence (ST). So far no comprehensive study has been made to experimentally examine ST in the mesosphere and lower thermosphere (MLT) region on horizontal mesoscales. This study introduces a method for doing so by measuring how the wind fluctuations are correlated as a function of horizontal separation. This is achieved by using meteor radar measurements. The technique is applied to a year‐long data set over Germany. It is found that the MLT wind fluctuations are compatible with ST theory. The introduced method could potentially be used for routinely measuring how kinetic energy flows from large‐scale to small‐scale atmospheric fluctuations.
Key Points
A more efficient estimator for horizontal correlation functions is introduced
The rotational and divergent correlation functions of mesosphere and lower thermosphere wind fluctuations are found to be balanced at horizontal mesoscales
Horizontal correlations of wind fluctuations follow a 2/3‐power law for horizontal separations of up to 300–400 km</description><identifier>ISSN: 2169-897X</identifier><identifier>ISSN: 2169-8996</identifier><identifier>EISSN: 2169-8996</identifier><identifier>DOI: 10.1029/2022JD038092</identifier><language>eng</language><publisher>Washington: Blackwell Publishing Ltd</publisher><subject>Altitude ; Annual variations ; Coordinate systems ; Coordinates ; Correlation ; Correlation analysis ; Datasets ; Doppler effect ; Doppler sonar ; Eddy kinetic energy ; Energy ; Energy budget ; Energy flow ; Energy transfer ; Fluctuations ; Geophysics ; Gravity waves ; Isotropic turbulence ; Kinetic energy ; Lower mantle ; Lower thermosphere ; Mesosphere ; Meteor trails ; Meteors ; Methods ; Radar ; Radar measurement ; Radar networks ; Thermosphere ; Turbulence ; Turbulent energy ; Turbulent fluctuations ; Upper atmosphere ; Velocity ; Wind fluctuations ; Wind measurement ; Wind variations</subject><ispartof>Journal of geophysical research. Atmospheres, 2023-03, Vol.128 (6), p.n/a</ispartof><rights>2023. The Authors.</rights><rights>2023. This article is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>info:eu-repo/semantics/openAccess</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3699-9282c371b73834ce0791f29b043fe5bb8eb1f78dd432954760cfeef9c6b4dee03</citedby><cites>FETCH-LOGICAL-c3699-9282c371b73834ce0791f29b043fe5bb8eb1f78dd432954760cfeef9c6b4dee03</cites><orcidid>0000-0002-9247-702X ; 0000-0001-5747-2525 ; 0000-0002-2364-8892 ; 0000-0003-2946-9120 ; 0000-0002-7878-0110 ; 0000-0002-3628-5568 ; 0000-0001-7651-708X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1029%2F2022JD038092$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1029%2F2022JD038092$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>230,314,776,780,881,1411,26544,27901,27902,45550,45551</link.rule.ids></links><search><creatorcontrib>Poblet, Facundo L.</creatorcontrib><creatorcontrib>Vierinen, Juha</creatorcontrib><creatorcontrib>Avsarkisov, Victor</creatorcontrib><creatorcontrib>Conte, J. Federico</creatorcontrib><creatorcontrib>Charuvil Asokan, Harikrishnan</creatorcontrib><creatorcontrib>Jacobi, Christoph</creatorcontrib><creatorcontrib>Chau, Jorge L.</creatorcontrib><title>Horizontal Correlation Functions of Wind Fluctuations in the Mesosphere and Lower Thermosphere</title><title>Journal of geophysical research. Atmospheres</title><description>Measurements of kinetic energy in vortical and divergent fluctuations in the mesosphere and lower thermosphere can be used to study stratified turbulence (ST) and gravity waves. This can be done using horizontal correlation functions of the fluctuating component of velocity. This study introduces a novel method for estimating these correlation functions using radars that observe Doppler shifts of ionized specular meteor trails. The technique solves the correlation functions directly on a longitudinal‐transverse‐up coordinate system, assuming axial symmetry. This procedure is more efficient and leads to smaller uncertainties than a previous approach. The new technique is applied to a year‐long data set from a multistatic specular meteor radar network in Germany, to study the annual variability of kinetic energy within turbulent fluctuations at 87–93 km of altitude. In monthly averages, the kinetic energy is found to be nearly equipartitioned between vortical and divergent modes. Turbulent fluctuations maximize during the winter months with approximately 25% more energy in these months than at other times. The horizontal correlation functions are in agreement with the inertial subrange of ST, exhibiting a 2/3 power law in the horizontal lag direction, with an outermost scale of ST to be about 380 km. This suggests that horizontal correlation functions could be used to estimate turbulent energy transfer rates.
Plain Language Summary
Flows exhibit a phenomenon called turbulence, which transfers energy from large scales into smaller scales. This effect is important to quantify the energy budget of the Earth's upper atmosphere. The range of length scales where this phenomenon occurs is called the inertial subrange of turbulence. The classical theory of isotropic turbulence predicts that this energy transfer occurs on length scales smaller than ∼100 m, at 60–110 km altitude. Recent work has shown that horizontal velocity fluctuations can extend the inertial subrange to length scales of up to hundreds of kilometers horizontally. This type of turbulence is called stratified turbulence (ST). So far no comprehensive study has been made to experimentally examine ST in the mesosphere and lower thermosphere (MLT) region on horizontal mesoscales. This study introduces a method for doing so by measuring how the wind fluctuations are correlated as a function of horizontal separation. This is achieved by using meteor radar measurements. The technique is applied to a year‐long data set over Germany. It is found that the MLT wind fluctuations are compatible with ST theory. The introduced method could potentially be used for routinely measuring how kinetic energy flows from large‐scale to small‐scale atmospheric fluctuations.
Key Points
A more efficient estimator for horizontal correlation functions is introduced
The rotational and divergent correlation functions of mesosphere and lower thermosphere wind fluctuations are found to be balanced at horizontal mesoscales
Horizontal correlations of wind fluctuations follow a 2/3‐power law for horizontal separations of up to 300–400 km</description><subject>Altitude</subject><subject>Annual variations</subject><subject>Coordinate systems</subject><subject>Coordinates</subject><subject>Correlation</subject><subject>Correlation analysis</subject><subject>Datasets</subject><subject>Doppler effect</subject><subject>Doppler sonar</subject><subject>Eddy kinetic energy</subject><subject>Energy</subject><subject>Energy budget</subject><subject>Energy flow</subject><subject>Energy transfer</subject><subject>Fluctuations</subject><subject>Geophysics</subject><subject>Gravity waves</subject><subject>Isotropic turbulence</subject><subject>Kinetic energy</subject><subject>Lower mantle</subject><subject>Lower thermosphere</subject><subject>Mesosphere</subject><subject>Meteor trails</subject><subject>Meteors</subject><subject>Methods</subject><subject>Radar</subject><subject>Radar measurement</subject><subject>Radar networks</subject><subject>Thermosphere</subject><subject>Turbulence</subject><subject>Turbulent energy</subject><subject>Turbulent fluctuations</subject><subject>Upper atmosphere</subject><subject>Velocity</subject><subject>Wind fluctuations</subject><subject>Wind measurement</subject><subject>Wind variations</subject><issn>2169-897X</issn><issn>2169-8996</issn><issn>2169-8996</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>3HK</sourceid><recordid>eNp9kMFLwzAUxoMoOOZu3g14dZomaZscZXObYyLIRE-GNn1lGV0zk5Yx_3ozOsWT7_K-9_jxvceH0GVEbiNC5R0llM7HhAki6Qnq0SiRQyFlcvqr0_dzNPB-TUIJwnjMe-hjZp35snWTVXhknYMqa4yt8aSt9UF4bEv8ZuoCT6pWN23WLU2NmxXgJ_DWb1fgAGcBWdgdOLwM8-a4vkBnZVZ5GBx7H71OHpaj2XDxPH0c3S-GmiVSDiUVVLM0ylMmGNdAUhmVVOaEsxLiPBeQR2UqioIzKmOeJkSXAKXUSc4LAML66Krz1c74xtSqti5TESEsVYwkTAbiuiO2zn624Bu1tq2rw1OKhmtxwjllgbr58bHeOyjV1plN5vbBSx1iVn9jDjjr8J2pYP8vq-bTl3Es4vDKN2e3fT8</recordid><startdate>20230327</startdate><enddate>20230327</enddate><creator>Poblet, Facundo L.</creator><creator>Vierinen, Juha</creator><creator>Avsarkisov, Victor</creator><creator>Conte, J. Federico</creator><creator>Charuvil Asokan, Harikrishnan</creator><creator>Jacobi, Christoph</creator><creator>Chau, Jorge L.</creator><general>Blackwell Publishing Ltd</general><general>Wiley</general><scope>24P</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H8D</scope><scope>H96</scope><scope>KL.</scope><scope>KR7</scope><scope>L.G</scope><scope>L7M</scope><scope>3HK</scope><orcidid>https://orcid.org/0000-0002-9247-702X</orcidid><orcidid>https://orcid.org/0000-0001-5747-2525</orcidid><orcidid>https://orcid.org/0000-0002-2364-8892</orcidid><orcidid>https://orcid.org/0000-0003-2946-9120</orcidid><orcidid>https://orcid.org/0000-0002-7878-0110</orcidid><orcidid>https://orcid.org/0000-0002-3628-5568</orcidid><orcidid>https://orcid.org/0000-0001-7651-708X</orcidid></search><sort><creationdate>20230327</creationdate><title>Horizontal Correlation Functions of Wind Fluctuations in the Mesosphere and Lower Thermosphere</title><author>Poblet, Facundo L. ; Vierinen, Juha ; Avsarkisov, Victor ; Conte, J. Federico ; Charuvil Asokan, Harikrishnan ; Jacobi, Christoph ; Chau, Jorge L.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3699-9282c371b73834ce0791f29b043fe5bb8eb1f78dd432954760cfeef9c6b4dee03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Altitude</topic><topic>Annual variations</topic><topic>Coordinate systems</topic><topic>Coordinates</topic><topic>Correlation</topic><topic>Correlation analysis</topic><topic>Datasets</topic><topic>Doppler effect</topic><topic>Doppler sonar</topic><topic>Eddy kinetic energy</topic><topic>Energy</topic><topic>Energy budget</topic><topic>Energy flow</topic><topic>Energy transfer</topic><topic>Fluctuations</topic><topic>Geophysics</topic><topic>Gravity waves</topic><topic>Isotropic turbulence</topic><topic>Kinetic energy</topic><topic>Lower mantle</topic><topic>Lower thermosphere</topic><topic>Mesosphere</topic><topic>Meteor trails</topic><topic>Meteors</topic><topic>Methods</topic><topic>Radar</topic><topic>Radar measurement</topic><topic>Radar networks</topic><topic>Thermosphere</topic><topic>Turbulence</topic><topic>Turbulent energy</topic><topic>Turbulent fluctuations</topic><topic>Upper atmosphere</topic><topic>Velocity</topic><topic>Wind fluctuations</topic><topic>Wind measurement</topic><topic>Wind variations</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Poblet, Facundo L.</creatorcontrib><creatorcontrib>Vierinen, Juha</creatorcontrib><creatorcontrib>Avsarkisov, Victor</creatorcontrib><creatorcontrib>Conte, J. Federico</creatorcontrib><creatorcontrib>Charuvil Asokan, Harikrishnan</creatorcontrib><creatorcontrib>Jacobi, Christoph</creatorcontrib><creatorcontrib>Chau, Jorge L.</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>CrossRef</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>NORA - Norwegian Open Research Archives</collection><jtitle>Journal of geophysical research. Atmospheres</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Poblet, Facundo L.</au><au>Vierinen, Juha</au><au>Avsarkisov, Victor</au><au>Conte, J. Federico</au><au>Charuvil Asokan, Harikrishnan</au><au>Jacobi, Christoph</au><au>Chau, Jorge L.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Horizontal Correlation Functions of Wind Fluctuations in the Mesosphere and Lower Thermosphere</atitle><jtitle>Journal of geophysical research. Atmospheres</jtitle><date>2023-03-27</date><risdate>2023</risdate><volume>128</volume><issue>6</issue><epage>n/a</epage><issn>2169-897X</issn><issn>2169-8996</issn><eissn>2169-8996</eissn><abstract>Measurements of kinetic energy in vortical and divergent fluctuations in the mesosphere and lower thermosphere can be used to study stratified turbulence (ST) and gravity waves. This can be done using horizontal correlation functions of the fluctuating component of velocity. This study introduces a novel method for estimating these correlation functions using radars that observe Doppler shifts of ionized specular meteor trails. The technique solves the correlation functions directly on a longitudinal‐transverse‐up coordinate system, assuming axial symmetry. This procedure is more efficient and leads to smaller uncertainties than a previous approach. The new technique is applied to a year‐long data set from a multistatic specular meteor radar network in Germany, to study the annual variability of kinetic energy within turbulent fluctuations at 87–93 km of altitude. In monthly averages, the kinetic energy is found to be nearly equipartitioned between vortical and divergent modes. Turbulent fluctuations maximize during the winter months with approximately 25% more energy in these months than at other times. The horizontal correlation functions are in agreement with the inertial subrange of ST, exhibiting a 2/3 power law in the horizontal lag direction, with an outermost scale of ST to be about 380 km. This suggests that horizontal correlation functions could be used to estimate turbulent energy transfer rates.
Plain Language Summary
Flows exhibit a phenomenon called turbulence, which transfers energy from large scales into smaller scales. This effect is important to quantify the energy budget of the Earth's upper atmosphere. The range of length scales where this phenomenon occurs is called the inertial subrange of turbulence. The classical theory of isotropic turbulence predicts that this energy transfer occurs on length scales smaller than ∼100 m, at 60–110 km altitude. Recent work has shown that horizontal velocity fluctuations can extend the inertial subrange to length scales of up to hundreds of kilometers horizontally. This type of turbulence is called stratified turbulence (ST). So far no comprehensive study has been made to experimentally examine ST in the mesosphere and lower thermosphere (MLT) region on horizontal mesoscales. This study introduces a method for doing so by measuring how the wind fluctuations are correlated as a function of horizontal separation. This is achieved by using meteor radar measurements. The technique is applied to a year‐long data set over Germany. It is found that the MLT wind fluctuations are compatible with ST theory. The introduced method could potentially be used for routinely measuring how kinetic energy flows from large‐scale to small‐scale atmospheric fluctuations.
Key Points
A more efficient estimator for horizontal correlation functions is introduced
The rotational and divergent correlation functions of mesosphere and lower thermosphere wind fluctuations are found to be balanced at horizontal mesoscales
Horizontal correlations of wind fluctuations follow a 2/3‐power law for horizontal separations of up to 300–400 km</abstract><cop>Washington</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1029/2022JD038092</doi><tpages>19</tpages><orcidid>https://orcid.org/0000-0002-9247-702X</orcidid><orcidid>https://orcid.org/0000-0001-5747-2525</orcidid><orcidid>https://orcid.org/0000-0002-2364-8892</orcidid><orcidid>https://orcid.org/0000-0003-2946-9120</orcidid><orcidid>https://orcid.org/0000-0002-7878-0110</orcidid><orcidid>https://orcid.org/0000-0002-3628-5568</orcidid><orcidid>https://orcid.org/0000-0001-7651-708X</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Altitude Annual variations Coordinate systems Coordinates Correlation Correlation analysis Datasets Doppler effect Doppler sonar Eddy kinetic energy Energy Energy budget Energy flow Energy transfer Fluctuations Geophysics Gravity waves Isotropic turbulence Kinetic energy Lower mantle Lower thermosphere Mesosphere Meteor trails Meteors Methods Radar Radar measurement Radar networks Thermosphere Turbulence Turbulent energy Turbulent fluctuations Upper atmosphere Velocity Wind fluctuations Wind measurement Wind variations |
title | Horizontal Correlation Functions of Wind Fluctuations in the Mesosphere and Lower Thermosphere |
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