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Global balanced wind derived from SABER temperature and pressure observations and its validations
Zonal winds in the stratosphere and mesosphere play important roles in atmospheric dynamics and aeronomy. However, the direct measurement of winds in this height range is difficult. We present a dataset of the monthly mean zonal wind in the height range of 18–100 km and at latitudes of 50∘ S–50∘ N f...
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Published in: | Earth system science data 2021-12, Vol.13 (12), p.5643-5661 |
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creator | Liu, Xiao Xu, Jiyao Yue, Jia Yu, You Batista, Paulo P Andrioli, Vania F Liu, Zhengkuan Yuan, Tao Wang, Chi Zou, Ziming Li, Guozhu Russell III, James M |
description | Zonal winds in the stratosphere and mesosphere play
important roles in atmospheric dynamics and aeronomy. However, the
direct measurement of winds in this height range is difficult. We present a
dataset of the monthly mean zonal wind in the height range of 18–100 km and
at latitudes of 50∘ S–50∘ N from 2002 to 2019,
derived by the gradient balance wind theory and the temperature and pressure
observed by the SABER instrument. The tide alias above 80 km at the Equator
is replaced by the monthly mean zonal wind measured by a meteor radar at
0.2∘ S. The dataset (named BU) is validated by comparing with
the zonal wind from MERRA2 (MerU), UARP (UraU), the HWM14 empirical model
(HwmU), meteor radar (MetU), and lidar (LidU) at seven stations from around
50∘ N to 29.7∘ S. At 18–70 km, BU and MerU have (i)
nearly identical zero wind lines and (ii) year-to-year variations of the
eastward and westward wind jets at middle and high latitudes, and (iii) the
quasi-biennial oscillation (QBO) and semi-annual oscillation (SAO)
especially the disrupted QBO in early 2016. The comparisons among BU, UraU,
and HwmU show good agreement in general below 80 km. Above 80 km, the
agreements among BU, UraU, HwmU, MetU, and LidU are good in general, except
some discrepancies at limited heights and months. The BU data are archived
as netCDF files and are available at https://doi.org/10.12176/01.99.00574 (Liu et al., 2021). The advantages
of the global BU dataset are its large vertical extent (from the
stratosphere to the lower thermosphere) and 18-year internally
consistent time series (2002–2019). The BU data is useful to study the
temporal variations with periods ranging from seasons to decades at
50∘ S–50∘ N. It can also be used as the background wind
for atmospheric wave propagation. |
doi_str_mv | 10.5194/essd-13-5643-2021 |
format | article |
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important roles in atmospheric dynamics and aeronomy. However, the
direct measurement of winds in this height range is difficult. We present a
dataset of the monthly mean zonal wind in the height range of 18–100 km and
at latitudes of 50∘ S–50∘ N from 2002 to 2019,
derived by the gradient balance wind theory and the temperature and pressure
observed by the SABER instrument. The tide alias above 80 km at the Equator
is replaced by the monthly mean zonal wind measured by a meteor radar at
0.2∘ S. The dataset (named BU) is validated by comparing with
the zonal wind from MERRA2 (MerU), UARP (UraU), the HWM14 empirical model
(HwmU), meteor radar (MetU), and lidar (LidU) at seven stations from around
50∘ N to 29.7∘ S. At 18–70 km, BU and MerU have (i)
nearly identical zero wind lines and (ii) year-to-year variations of the
eastward and westward wind jets at middle and high latitudes, and (iii) the
quasi-biennial oscillation (QBO) and semi-annual oscillation (SAO)
especially the disrupted QBO in early 2016. The comparisons among BU, UraU,
and HwmU show good agreement in general below 80 km. Above 80 km, the
agreements among BU, UraU, HwmU, MetU, and LidU are good in general, except
some discrepancies at limited heights and months. The BU data are archived
as netCDF files and are available at https://doi.org/10.12176/01.99.00574 (Liu et al., 2021). The advantages
of the global BU dataset are its large vertical extent (from the
stratosphere to the lower thermosphere) and 18-year internally
consistent time series (2002–2019). The BU data is useful to study the
temporal variations with periods ranging from seasons to decades at
50∘ S–50∘ N. It can also be used as the background wind
for atmospheric wave propagation.</description><identifier>ISSN: 1866-3516</identifier><identifier>ISSN: 1866-3508</identifier><identifier>EISSN: 1866-3516</identifier><identifier>DOI: 10.5194/essd-13-5643-2021</identifier><language>eng</language><publisher>Katlenburg-Lindau: Copernicus GmbH</publisher><subject>Aeronomy ; Agreements ; Analysis ; Annual oscillation ; Atmosphere ; Atmosphere, Upper ; Atmospheric dynamics ; Atmospheric waves ; Climate ; Datasets ; Dynamic meteorology ; Empirical models ; Equator ; Height ; Ionosphere ; Lidar ; Lower mantle ; Lower thermosphere ; Mesosphere ; Meteors ; Quasi-biennial oscillation ; Radar ; Semiannual oscillation ; Stratosphere ; Temperature ; Temporal variations ; Thermosphere ; Wave propagation ; Wind ; Wind measurement ; Winds ; Zonal winds</subject><ispartof>Earth system science data, 2021-12, Vol.13 (12), p.5643-5661</ispartof><rights>COPYRIGHT 2021 Copernicus GmbH</rights><rights>2021. This work is published under https://creativecommons.org/licenses/by/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><citedby>FETCH-LOGICAL-c549t-4773ffdfdf24aaff36bab8123bbeb506f6e1dc7402cc05d98edee35632fd78673</citedby><cites>FETCH-LOGICAL-c549t-4773ffdfdf24aaff36bab8123bbeb506f6e1dc7402cc05d98edee35632fd78673</cites><orcidid>0000-0001-6302-7516 ; 0000-0003-0577-5289 ; 0000-0002-4835-7696 ; 0000-0002-5448-5803 ; 0000-0002-7669-3590</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2607202769/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2607202769?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25753,27924,27925,37012,44590,75126</link.rule.ids></links><search><creatorcontrib>Liu, Xiao</creatorcontrib><creatorcontrib>Xu, Jiyao</creatorcontrib><creatorcontrib>Yue, Jia</creatorcontrib><creatorcontrib>Yu, You</creatorcontrib><creatorcontrib>Batista, Paulo P</creatorcontrib><creatorcontrib>Andrioli, Vania F</creatorcontrib><creatorcontrib>Liu, Zhengkuan</creatorcontrib><creatorcontrib>Yuan, Tao</creatorcontrib><creatorcontrib>Wang, Chi</creatorcontrib><creatorcontrib>Zou, Ziming</creatorcontrib><creatorcontrib>Li, Guozhu</creatorcontrib><creatorcontrib>Russell III, James M</creatorcontrib><title>Global balanced wind derived from SABER temperature and pressure observations and its validations</title><title>Earth system science data</title><description>Zonal winds in the stratosphere and mesosphere play
important roles in atmospheric dynamics and aeronomy. However, the
direct measurement of winds in this height range is difficult. We present a
dataset of the monthly mean zonal wind in the height range of 18–100 km and
at latitudes of 50∘ S–50∘ N from 2002 to 2019,
derived by the gradient balance wind theory and the temperature and pressure
observed by the SABER instrument. The tide alias above 80 km at the Equator
is replaced by the monthly mean zonal wind measured by a meteor radar at
0.2∘ S. The dataset (named BU) is validated by comparing with
the zonal wind from MERRA2 (MerU), UARP (UraU), the HWM14 empirical model
(HwmU), meteor radar (MetU), and lidar (LidU) at seven stations from around
50∘ N to 29.7∘ S. At 18–70 km, BU and MerU have (i)
nearly identical zero wind lines and (ii) year-to-year variations of the
eastward and westward wind jets at middle and high latitudes, and (iii) the
quasi-biennial oscillation (QBO) and semi-annual oscillation (SAO)
especially the disrupted QBO in early 2016. The comparisons among BU, UraU,
and HwmU show good agreement in general below 80 km. Above 80 km, the
agreements among BU, UraU, HwmU, MetU, and LidU are good in general, except
some discrepancies at limited heights and months. The BU data are archived
as netCDF files and are available at https://doi.org/10.12176/01.99.00574 (Liu et al., 2021). The advantages
of the global BU dataset are its large vertical extent (from the
stratosphere to the lower thermosphere) and 18-year internally
consistent time series (2002–2019). The BU data is useful to study the
temporal variations with periods ranging from seasons to decades at
50∘ S–50∘ N. It can also be used as the background wind
for atmospheric wave propagation.</description><subject>Aeronomy</subject><subject>Agreements</subject><subject>Analysis</subject><subject>Annual oscillation</subject><subject>Atmosphere</subject><subject>Atmosphere, Upper</subject><subject>Atmospheric dynamics</subject><subject>Atmospheric waves</subject><subject>Climate</subject><subject>Datasets</subject><subject>Dynamic meteorology</subject><subject>Empirical models</subject><subject>Equator</subject><subject>Height</subject><subject>Ionosphere</subject><subject>Lidar</subject><subject>Lower mantle</subject><subject>Lower thermosphere</subject><subject>Mesosphere</subject><subject>Meteors</subject><subject>Quasi-biennial oscillation</subject><subject>Radar</subject><subject>Semiannual oscillation</subject><subject>Stratosphere</subject><subject>Temperature</subject><subject>Temporal variations</subject><subject>Thermosphere</subject><subject>Wave propagation</subject><subject>Wind</subject><subject>Wind measurement</subject><subject>Winds</subject><subject>Zonal winds</subject><issn>1866-3516</issn><issn>1866-3508</issn><issn>1866-3516</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNptkk1r3DAQhk1poWnaH9CboacenEjWl33chjRdCBTycRZjabRosa2tpN2m_75yNrRdKEJIM3rmHUm8VfWRkgtBe36JKdmGskZIzpqWtPRVdUY7KRsmqHz9z_5t9S6lLSGSUyXOKrgZwwBjXSbMBm3908-2thj9oQQuhqm-X325vqszTjuMkPcRayjILpaWSxCGhPEA2Yc5PZ_4nOoDjN4ec--rNw7GhB9e1vPq8ev1w9W35vb7zfpqddsYwfvccKWYc7aMlgM4x-QAQ0dbNgw4CCKdRGqN4qQ1hgjbd2gRmZCsdVZ1UrHzan3UtQG2ehf9BPGXDuD1cyLEjYaYvRlRdwSNAttaRRhnrAdKnSotuTBCODcUrU9HrV0MP_aYst6GfZzL9XUriSr_q2T_l9pAEfWzCzmCmXwyeiU7obhQrC3UxX-oMixO3oQZnS_5k4LPJwWFyfiUN7BPSa_v705ZemRNDClFdH8eTolejKEXY2jK9GIMvRiD_QbPvKuE</recordid><startdate>20211207</startdate><enddate>20211207</enddate><creator>Liu, Xiao</creator><creator>Xu, Jiyao</creator><creator>Yue, Jia</creator><creator>Yu, You</creator><creator>Batista, Paulo P</creator><creator>Andrioli, Vania F</creator><creator>Liu, Zhengkuan</creator><creator>Yuan, Tao</creator><creator>Wang, Chi</creator><creator>Zou, Ziming</creator><creator>Li, Guozhu</creator><creator>Russell III, James M</creator><general>Copernicus GmbH</general><general>Copernicus 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balanced wind derived from SABER temperature and pressure observations and its validations</title><author>Liu, Xiao ; Xu, Jiyao ; Yue, Jia ; Yu, You ; Batista, Paulo P ; Andrioli, Vania F ; Liu, Zhengkuan ; Yuan, Tao ; Wang, Chi ; Zou, Ziming ; Li, Guozhu ; Russell III, James M</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c549t-4773ffdfdf24aaff36bab8123bbeb506f6e1dc7402cc05d98edee35632fd78673</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Aeronomy</topic><topic>Agreements</topic><topic>Analysis</topic><topic>Annual oscillation</topic><topic>Atmosphere</topic><topic>Atmosphere, Upper</topic><topic>Atmospheric dynamics</topic><topic>Atmospheric waves</topic><topic>Climate</topic><topic>Datasets</topic><topic>Dynamic meteorology</topic><topic>Empirical models</topic><topic>Equator</topic><topic>Height</topic><topic>Ionosphere</topic><topic>Lidar</topic><topic>Lower mantle</topic><topic>Lower thermosphere</topic><topic>Mesosphere</topic><topic>Meteors</topic><topic>Quasi-biennial oscillation</topic><topic>Radar</topic><topic>Semiannual oscillation</topic><topic>Stratosphere</topic><topic>Temperature</topic><topic>Temporal variations</topic><topic>Thermosphere</topic><topic>Wave propagation</topic><topic>Wind</topic><topic>Wind measurement</topic><topic>Winds</topic><topic>Zonal winds</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Xiao</creatorcontrib><creatorcontrib>Xu, Jiyao</creatorcontrib><creatorcontrib>Yue, Jia</creatorcontrib><creatorcontrib>Yu, You</creatorcontrib><creatorcontrib>Batista, Paulo P</creatorcontrib><creatorcontrib>Andrioli, Vania F</creatorcontrib><creatorcontrib>Liu, Zhengkuan</creatorcontrib><creatorcontrib>Yuan, Tao</creatorcontrib><creatorcontrib>Wang, Chi</creatorcontrib><creatorcontrib>Zou, Ziming</creatorcontrib><creatorcontrib>Li, Guozhu</creatorcontrib><creatorcontrib>Russell III, James M</creatorcontrib><collection>CrossRef</collection><collection>Gale in Context: Science</collection><collection>Ecology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Oceanic Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Continental Europe Database</collection><collection>Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science 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(DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering collection</collection><collection>Directory of Open Access Journals</collection><jtitle>Earth system science data</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Xiao</au><au>Xu, Jiyao</au><au>Yue, Jia</au><au>Yu, You</au><au>Batista, Paulo P</au><au>Andrioli, Vania F</au><au>Liu, Zhengkuan</au><au>Yuan, Tao</au><au>Wang, Chi</au><au>Zou, Ziming</au><au>Li, Guozhu</au><au>Russell III, James M</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Global balanced wind derived from SABER temperature and pressure observations and its validations</atitle><jtitle>Earth system science data</jtitle><date>2021-12-07</date><risdate>2021</risdate><volume>13</volume><issue>12</issue><spage>5643</spage><epage>5661</epage><pages>5643-5661</pages><issn>1866-3516</issn><issn>1866-3508</issn><eissn>1866-3516</eissn><abstract>Zonal winds in the stratosphere and mesosphere play
important roles in atmospheric dynamics and aeronomy. However, the
direct measurement of winds in this height range is difficult. We present a
dataset of the monthly mean zonal wind in the height range of 18–100 km and
at latitudes of 50∘ S–50∘ N from 2002 to 2019,
derived by the gradient balance wind theory and the temperature and pressure
observed by the SABER instrument. The tide alias above 80 km at the Equator
is replaced by the monthly mean zonal wind measured by a meteor radar at
0.2∘ S. The dataset (named BU) is validated by comparing with
the zonal wind from MERRA2 (MerU), UARP (UraU), the HWM14 empirical model
(HwmU), meteor radar (MetU), and lidar (LidU) at seven stations from around
50∘ N to 29.7∘ S. At 18–70 km, BU and MerU have (i)
nearly identical zero wind lines and (ii) year-to-year variations of the
eastward and westward wind jets at middle and high latitudes, and (iii) the
quasi-biennial oscillation (QBO) and semi-annual oscillation (SAO)
especially the disrupted QBO in early 2016. The comparisons among BU, UraU,
and HwmU show good agreement in general below 80 km. Above 80 km, the
agreements among BU, UraU, HwmU, MetU, and LidU are good in general, except
some discrepancies at limited heights and months. The BU data are archived
as netCDF files and are available at https://doi.org/10.12176/01.99.00574 (Liu et al., 2021). The advantages
of the global BU dataset are its large vertical extent (from the
stratosphere to the lower thermosphere) and 18-year internally
consistent time series (2002–2019). The BU data is useful to study the
temporal variations with periods ranging from seasons to decades at
50∘ S–50∘ N. It can also be used as the background wind
for atmospheric wave propagation.</abstract><cop>Katlenburg-Lindau</cop><pub>Copernicus GmbH</pub><doi>10.5194/essd-13-5643-2021</doi><tpages>19</tpages><orcidid>https://orcid.org/0000-0001-6302-7516</orcidid><orcidid>https://orcid.org/0000-0003-0577-5289</orcidid><orcidid>https://orcid.org/0000-0002-4835-7696</orcidid><orcidid>https://orcid.org/0000-0002-5448-5803</orcidid><orcidid>https://orcid.org/0000-0002-7669-3590</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Aeronomy Agreements Analysis Annual oscillation Atmosphere Atmosphere, Upper Atmospheric dynamics Atmospheric waves Climate Datasets Dynamic meteorology Empirical models Equator Height Ionosphere Lidar Lower mantle Lower thermosphere Mesosphere Meteors Quasi-biennial oscillation Radar Semiannual oscillation Stratosphere Temperature Temporal variations Thermosphere Wave propagation Wind Wind measurement Winds Zonal winds |
title | Global balanced wind derived from SABER temperature and pressure observations and its validations |
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