Home > Publications database > Determining Gravity Wave Sources and Propagation in the Southern Hemisphere by Ray‐Tracing AIRS Measurements > print

001     889050
005     20260122230601.0
024 7 _ |2 doi
|a 10.1029/2020GL088621
024 7 _ |2 ISSN
|a 0094-8276
024 7 _ |2 ISSN
|a 1944-8007
024 7 _ |2 Handle
|a 2128/27126
024 7 _ |2 altmetric
|a altmetric:96541599
024 7 _ |2 WOS
|a WOS:000613648800041
037 _ _ |a FZJ-2020-05418
041 _ _ |a English
082 _ _ |a 550
100 1 _ |0 0000-0002-9147-7079
|a Perrett, Jon A.
|b 0
|e Corresponding author
245 _ _ |a Determining Gravity Wave Sources and Propagation in the Southern Hemisphere by Ray‐Tracing AIRS Measurements
260 _ _ |a Hoboken, NJ
|b Wiley
|c 2021
336 7 _ |2 DRIVER
|a article
336 7 _ |2 DataCite
|a Output Types/Journal article
336 7 _ |0 PUB:(DE-HGF)16
|2 PUB:(DE-HGF)
|a Journal Article
|b journal
|m journal
|s 1641839967_21106
336 7 _ |2 BibTeX
|a ARTICLE
336 7 _ |2 ORCID
|a JOURNAL_ARTICLE
336 7 _ |0 0
|2 EndNote
|a Journal Article
520 _ _ |a Gravity waves (GWs) are key drivers of atmospheric circulation. Understanding their sources and propagation is essential to improving weather and climate models. We apply a 3D Stockwell Transform to one month of stratospheric temperature data from NASA's Atmospheric InfraRed Sounder to obtain 3D GW measurements and parameters. We use ray‐tracing methods to determine the sources and propagation characteristics of these GWs over the entire Southern Ocean. We trace 1.28 million GW measurements per day for the month of June 2010. Our analysis suggests that ground‐based sources around the Andes, Antarctic Peninsula and Kerguelen play major roles, and that the GWs generated by these and other sources travel large zonal distances. We show evidence that GWs propagate into the 60°S belt, a possible source of ‘missing momentum flux’ in GCMs at this latitude. These results emphasise the need for models to incorporate the possibility that GWs can exhibit large horizontal propagation.
536 _ _ |0 G:(DE-HGF)POF4-5111
|a 5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511)
|c POF4-511
|f POF IV
|x 0
536 _ _ |0 G:(DE-Juel-1)SDLCS
|a Simulation and Data Lab Climate Science
|c SDLCS
|x 1
588 _ _ |a Dataset connected to CrossRef
700 1 _ |0 0000-0003-2496-953X
|a Wright, Corwin J.
|b 1
700 1 _ |0 0000-0003-4377-2038
|a Hindley, Neil P.
|b 2
700 1 _ |0 P:(DE-Juel1)129125
|a Hoffmann, Lars
|b 3
700 1 _ |0 0000-0003-1149-8484
|a Mitchell, Nicholas J.
|b 4
700 1 _ |0 P:(DE-Juel1)129143
|a Preusse, Peter
|b 5
700 1 _ |0 P:(DE-Juel1)169715
|a Strube, Cornelia
|b 6
700 1 _ |0 0000-0002-8534-1909
|a Eckermann, Stephen D.
|b 7
773 _ _ |0 PERI:(DE-600)2021599-X
|a 10.1029/2020GL088621
|n 2
|p e2020GL088621
|t Geophysical research letters
|v 48
|x 1944-8007
|y 2021
856 4 _ |u https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2020GL088621
856 4 _ |u https://juser.fz-juelich.de/record/889050/files/2020GL088621.pdf
|y OpenAccess
856 4 _ |u https://juser.fz-juelich.de/record/889050/files/2nd_Corrections___Perrett_et_al_GRL.pdf
|y OpenAccess
909 C O |o oai:juser.fz-juelich.de:889050
|p openaire
|p open_access
|p driver
|p VDB:Earth_Environment
|p VDB
|p dnbdelivery
910 1 _ |0 I:(DE-588b)5008462-8
|6 P:(DE-Juel1)129125
|a Forschungszentrum Jülich
|b 3
|k FZJ
910 1 _ |0 I:(DE-588b)5008462-8
|6 P:(DE-Juel1)129143
|a Forschungszentrum Jülich
|b 5
|k FZJ
910 1 _ |0 I:(DE-588b)5008462-8
|6 P:(DE-Juel1)169715
|a Forschungszentrum Jülich
|b 6
|k FZJ
913 1 _ |0 G:(DE-HGF)POF4-511
|1 G:(DE-HGF)POF4-510
|2 G:(DE-HGF)POF4-500
|3 G:(DE-HGF)POF4
|4 G:(DE-HGF)POF
|9 G:(DE-HGF)POF4-5111
|a DE-HGF
|b Key Technologies
|l Engineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action
|v Enabling Computational- & Data-Intensive Science and Engineering
|x 0
913 0 _ |0 G:(DE-HGF)POF3-511
|1 G:(DE-HGF)POF3-510
|2 G:(DE-HGF)POF3-500
|3 G:(DE-HGF)POF3
|4 G:(DE-HGF)POF
|a DE-HGF
|b Key Technologies
|l Supercomputing & Big Data
|v Computational Science and Mathematical Methods
|x 0
913 0 _ |0 G:(DE-HGF)POF3-244
|1 G:(DE-HGF)POF3-240
|2 G:(DE-HGF)POF3-200
|3 G:(DE-HGF)POF3
|4 G:(DE-HGF)POF
|a DE-HGF
|b Erde und Umwelt
|l Atmosphäre und Klima
|v Composition and dynamics of the upper troposphere and middle atmosphere
|x 1
914 1 _ |y 2021
915 _ _ |0 StatID:(DE-HGF)0150
|2 StatID
|a DBCoverage
|b Web of Science Core Collection
|d 2020-09-04
915 _ _ |0 StatID:(DE-HGF)0300
|2 StatID
|a DBCoverage
|b Medline
|d 2020-09-04
915 _ _ |0 LIC:(DE-HGF)CCBY4
|2 HGFVOC
|a Creative Commons Attribution CC BY 4.0
915 _ _ |0 StatID:(DE-HGF)0600
|2 StatID
|a DBCoverage
|b Ebsco Academic Search
|d 2020-09-04
915 _ _ |0 StatID:(DE-HGF)1150
|2 StatID
|a DBCoverage
|b Current Contents - Physical, Chemical and Earth Sciences
|d 2020-09-04
915 _ _ |0 StatID:(DE-HGF)3001
|2 StatID
|a DEAL Wiley
|d 2020-09-04
|w ger
915 _ _ |0 StatID:(DE-HGF)0113
|2 StatID
|a WoS
|b Science Citation Index Expanded
|d 2020-09-04
915 _ _ |0 StatID:(DE-HGF)9900
|2 StatID
|a IF < 5
|d 2020-09-04
915 _ _ |0 StatID:(DE-HGF)0510
|2 StatID
|a OpenAccess
915 _ _ |0 StatID:(DE-HGF)0030
|2 StatID
|a Peer Review
|b ASC
|d 2020-09-04
915 _ _ |0 StatID:(DE-HGF)0100
|2 StatID
|a JCR
|b GEOPHYS RES LETT : 2018
|d 2020-09-04
915 _ _ |0 StatID:(DE-HGF)0160
|2 StatID
|a DBCoverage
|b Essential Science Indicators
|d 2020-09-04
915 _ _ |0 StatID:(DE-HGF)0200
|2 StatID
|a DBCoverage
|b SCOPUS
|d 2020-09-04
915 _ _ |0 StatID:(DE-HGF)0199
|2 StatID
|a DBCoverage
|b Clarivate Analytics Master Journal List
|d 2020-09-04
920 _ _ |l yes
920 1 _ |0 I:(DE-Juel1)JSC-20090406
|k JSC
|l Jülich Supercomputing Center
|x 0
920 1 _ |0 I:(DE-Juel1)IEK-7-20101013
|k IEK-7
|l Stratosphäre
|x 1
980 1 _ |a FullTexts
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-Juel1)JSC-20090406
980 _ _ |a I:(DE-Juel1)IEK-7-20101013
980 _ _ |a UNRESTRICTED
981 _ _ |a I:(DE-Juel1)ICE-4-20101013

LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21