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Coupling wind LiDAR fixed and volumetric scans for enhanced characterization of wind turbulence and flow three‐dimensionality
Summary Over the last decades, pulsed light detection and ranging (LiDAR) anemometry has gained growing attention in probing the marine atmospheric boundary layer (MABL) due to its ease of use combined with compelling spatio‐temporal resolution. Among several scanning strategies, fixed scans represe...
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Published in: | Wind energy (Chichester, England) England), 2024-11, Vol.27 (11), p.1229-1244 |
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creator | Puccioni, Matteo Moss, Coleman Iungo, Giacomo Valerio |
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Over the last decades, pulsed light detection and ranging (LiDAR) anemometry has gained growing attention in probing the marine atmospheric boundary layer (MABL) due to its ease of use combined with compelling spatio‐temporal resolution. Among several scanning strategies, fixed scans represent the most prominent choice when high‐frequency resolution is required; however, no information is provided about the spatial heterogeneity of the wind field. On the other hand, volumetric scans allow for the characterization of the spatial variability of the wind field with much lower temporal resolution than fixed scans. In this work, the recently developed “LiDAR Statistical Barnes Objective Analysis” (LiSBOA) algorithm for the optimal design of LiDAR scans and retrieval of wind velocity statistics is tailored for applications in the MABL. The LiDAR data, collected during a recent experimental campaign over Lake Lavon in Texas, show a good consistency of mean velocity profiles between fixed and LiSBOA‐interpolated volumetric data, thus further encouraging the use of coupled fixed and volumetric scans for simultaneous characterizations of wind turbulence statistics along the vertical direction and volumetric heterogeneity of the wind field. |
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Over the last decades, pulsed light detection and ranging (LiDAR) anemometry has gained growing attention in probing the marine atmospheric boundary layer (MABL) due to its ease of use combined with compelling spatio‐temporal resolution. Among several scanning strategies, fixed scans represent the most prominent choice when high‐frequency resolution is required; however, no information is provided about the spatial heterogeneity of the wind field. On the other hand, volumetric scans allow for the characterization of the spatial variability of the wind field with much lower temporal resolution than fixed scans. In this work, the recently developed “LiDAR Statistical Barnes Objective Analysis” (LiSBOA) algorithm for the optimal design of LiDAR scans and retrieval of wind velocity statistics is tailored for applications in the MABL. The LiDAR data, collected during a recent experimental campaign over Lake Lavon in Texas, show a good consistency of mean velocity profiles between fixed and LiSBOA‐interpolated volumetric data, thus further encouraging the use of coupled fixed and volumetric scans for simultaneous characterizations of wind turbulence statistics along the vertical direction and volumetric heterogeneity of the wind field.</description><identifier>ISSN: 1095-4244</identifier><identifier>EISSN: 1099-1824</identifier><identifier>DOI: 10.1002/we.2865</identifier><language>eng</language><publisher>Bognor Regis: John Wiley & Sons, Inc</publisher><subject>Algorithms ; Atmospheric boundary layer ; Boundary layers ; Frequency dependence ; Heterogeneity ; LiDAR ; marine atmospheric boundary layer ; Spatial heterogeneity ; Statistical analysis ; Temporal resolution ; Turbulence ; Turbulent flow ; Velocity ; Velocity distribution ; Velocity measurement ; Wind ; Wind speed</subject><ispartof>Wind energy (Chichester, England), 2024-11, Vol.27 (11), p.1229-1244</ispartof><rights>2023 The Authors. published by John Wiley & Sons Ltd.</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><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c3505-5239e7ab561feedebbea198f989d40ef168e87bca3e209b3ccb315fcede38f033</cites><orcidid>0000-0002-4188-6915 ; 0000-0002-0990-8133 ; 0000-0002-0764-9430</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fwe.2865$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fwe.2865$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,11562,27924,27925,46052,46476</link.rule.ids></links><search><creatorcontrib>Puccioni, Matteo</creatorcontrib><creatorcontrib>Moss, Coleman</creatorcontrib><creatorcontrib>Iungo, Giacomo Valerio</creatorcontrib><title>Coupling wind LiDAR fixed and volumetric scans for enhanced characterization of wind turbulence and flow three‐dimensionality</title><title>Wind energy (Chichester, England)</title><description>Summary
Over the last decades, pulsed light detection and ranging (LiDAR) anemometry has gained growing attention in probing the marine atmospheric boundary layer (MABL) due to its ease of use combined with compelling spatio‐temporal resolution. Among several scanning strategies, fixed scans represent the most prominent choice when high‐frequency resolution is required; however, no information is provided about the spatial heterogeneity of the wind field. On the other hand, volumetric scans allow for the characterization of the spatial variability of the wind field with much lower temporal resolution than fixed scans. In this work, the recently developed “LiDAR Statistical Barnes Objective Analysis” (LiSBOA) algorithm for the optimal design of LiDAR scans and retrieval of wind velocity statistics is tailored for applications in the MABL. The LiDAR data, collected during a recent experimental campaign over Lake Lavon in Texas, show a good consistency of mean velocity profiles between fixed and LiSBOA‐interpolated volumetric data, thus further encouraging the use of coupled fixed and volumetric scans for simultaneous characterizations of wind turbulence statistics along the vertical direction and volumetric heterogeneity of the wind field.</description><subject>Algorithms</subject><subject>Atmospheric boundary layer</subject><subject>Boundary layers</subject><subject>Frequency dependence</subject><subject>Heterogeneity</subject><subject>LiDAR</subject><subject>marine atmospheric boundary layer</subject><subject>Spatial heterogeneity</subject><subject>Statistical analysis</subject><subject>Temporal resolution</subject><subject>Turbulence</subject><subject>Turbulent flow</subject><subject>Velocity</subject><subject>Velocity distribution</subject><subject>Velocity measurement</subject><subject>Wind</subject><subject>Wind speed</subject><issn>1095-4244</issn><issn>1099-1824</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>DOA</sourceid><recordid>eNp1kctqGzEUhoeQQt0k9BUEWWRRJtVtbGkZ3KQJGAohIUuhkY5smfHIkWYycTftI_QZ-ySRPaW7rHTh4_vP4S-KzwRfEozp1wEuqZhWR8WEYClLIig_PtyrklPOPxafUlpjTDAhYlL8mod-2_h2iQbfWrTw367ukfOvYJHO75fQ9BvoojcoGd0m5EJE0K50azJhVjpq00H0P3XnQ4uCGzVdH-u-gQwdLK4JA-pWEeDv7z_Wb6BNmdaN73anxQenmwRn_86T4vHm-mF-Wy5-fL-bXy1KwypclRVlEma6rqbEAVioa9BECieFtByDI1MBYlYbzYBiWTNjakYql4cEJhxm7KS4G7026LXaRr_RcaeC9urwEeJS6dh504Bi1DljrcS05pxKIpm1PGdjMIxJDtl1Prq2MTz3kDq1Dn3M-yTFCJkxxqnYJ16MlIkhpQjufyrBat-UGkDtm8rkl5EcfAO79zD1dH2g3wAPgJdW</recordid><startdate>202411</startdate><enddate>202411</enddate><creator>Puccioni, Matteo</creator><creator>Moss, Coleman</creator><creator>Iungo, Giacomo Valerio</creator><general>John Wiley & Sons, Inc</general><general>Wiley</general><scope>24P</scope><scope>WIN</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>C1K</scope><scope>SOI</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-4188-6915</orcidid><orcidid>https://orcid.org/0000-0002-0990-8133</orcidid><orcidid>https://orcid.org/0000-0002-0764-9430</orcidid></search><sort><creationdate>202411</creationdate><title>Coupling wind LiDAR fixed and volumetric scans for enhanced characterization of wind turbulence and flow three‐dimensionality</title><author>Puccioni, Matteo ; Moss, Coleman ; Iungo, Giacomo Valerio</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3505-5239e7ab561feedebbea198f989d40ef168e87bca3e209b3ccb315fcede38f033</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Algorithms</topic><topic>Atmospheric boundary layer</topic><topic>Boundary layers</topic><topic>Frequency dependence</topic><topic>Heterogeneity</topic><topic>LiDAR</topic><topic>marine atmospheric boundary layer</topic><topic>Spatial heterogeneity</topic><topic>Statistical analysis</topic><topic>Temporal resolution</topic><topic>Turbulence</topic><topic>Turbulent flow</topic><topic>Velocity</topic><topic>Velocity distribution</topic><topic>Velocity measurement</topic><topic>Wind</topic><topic>Wind speed</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Puccioni, Matteo</creatorcontrib><creatorcontrib>Moss, Coleman</creatorcontrib><creatorcontrib>Iungo, Giacomo Valerio</creatorcontrib><collection>Wiley Open Access</collection><collection>Wiley-Blackwell Open Access Backfiles</collection><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Environment Abstracts</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Wind energy (Chichester, England)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Puccioni, Matteo</au><au>Moss, Coleman</au><au>Iungo, Giacomo Valerio</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Coupling wind LiDAR fixed and volumetric scans for enhanced characterization of wind turbulence and flow three‐dimensionality</atitle><jtitle>Wind energy (Chichester, England)</jtitle><date>2024-11</date><risdate>2024</risdate><volume>27</volume><issue>11</issue><spage>1229</spage><epage>1244</epage><pages>1229-1244</pages><issn>1095-4244</issn><eissn>1099-1824</eissn><abstract>Summary
Over the last decades, pulsed light detection and ranging (LiDAR) anemometry has gained growing attention in probing the marine atmospheric boundary layer (MABL) due to its ease of use combined with compelling spatio‐temporal resolution. Among several scanning strategies, fixed scans represent the most prominent choice when high‐frequency resolution is required; however, no information is provided about the spatial heterogeneity of the wind field. On the other hand, volumetric scans allow for the characterization of the spatial variability of the wind field with much lower temporal resolution than fixed scans. In this work, the recently developed “LiDAR Statistical Barnes Objective Analysis” (LiSBOA) algorithm for the optimal design of LiDAR scans and retrieval of wind velocity statistics is tailored for applications in the MABL. The LiDAR data, collected during a recent experimental campaign over Lake Lavon in Texas, show a good consistency of mean velocity profiles between fixed and LiSBOA‐interpolated volumetric data, thus further encouraging the use of coupled fixed and volumetric scans for simultaneous characterizations of wind turbulence statistics along the vertical direction and volumetric heterogeneity of the wind field.</abstract><cop>Bognor Regis</cop><pub>John Wiley & Sons, Inc</pub><doi>10.1002/we.2865</doi><tpages>16</tpages><orcidid>https://orcid.org/0000-0002-4188-6915</orcidid><orcidid>https://orcid.org/0000-0002-0990-8133</orcidid><orcidid>https://orcid.org/0000-0002-0764-9430</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Atmospheric boundary layer Boundary layers Frequency dependence Heterogeneity LiDAR marine atmospheric boundary layer Spatial heterogeneity Statistical analysis Temporal resolution Turbulence Turbulent flow Velocity Velocity distribution Velocity measurement Wind Wind speed |
title | Coupling wind LiDAR fixed and volumetric scans for enhanced characterization of wind turbulence and flow three‐dimensionality |
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