000884800 001__ 884800
000884800 005__ 20240712100859.0
000884800 0247_ $$2doi$$a10.5194/amt-13-4927-2020
000884800 0247_ $$2ISSN$$a1867-1381
000884800 0247_ $$2ISSN$$a1867-8548
000884800 0247_ $$2Handle$$a2128/25779
000884800 0247_ $$2altmetric$$aaltmetric:90543637
000884800 0247_ $$2WOS$$aWOS:000574778900002
000884800 037__ $$aFZJ-2020-03262
000884800 082__ $$a550
000884800 1001_ $$0P:(DE-Juel1)169715$$aStrube, Cornelia$$b0$$eCorresponding author$$ufzj
000884800 245__ $$aRemoving spurious inertial instability signals from gravity wave temperature perturbations using spectral filtering methods
000884800 260__ $$aKatlenburg-Lindau$$bCopernicus$$c2020
000884800 3367_ $$2DRIVER$$aarticle
000884800 3367_ $$2DataCite$$aOutput Types/Journal article
000884800 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1601376927_13975
000884800 3367_ $$2BibTeX$$aARTICLE
000884800 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000884800 3367_ $$00$$2EndNote$$aJournal Article
000884800 520__ $$aGravity waves are important drivers of dynamic processes in particular in the middle atmosphere. To analyse atmospheric data for gravity wave signals, it is essential to separate gravity wave perturbations from atmospheric variability due to other dynamic processes. Common methods to separate small-scale gravity wave signals from a large-scale background are separation methods depending on filters in either the horizontal or vertical wavelength domain. However, gravity waves are not the only process that could lead to small-scale perturbations in the atmosphere. Recently, concerns have been raised that vertical wavelength filtering can lead to misinterpretation of other wave-like perturbations, such as inertial instability effects, as gravity wave perturbations.In this paper we assess the ability of different spectral background removal approaches to separate gravity waves and inertial instabilities using artificial inertial instability perturbations, global model data and satellite observations. We investigate a horizontal background removal (which applies a zonal wavenumber filter with additional smoothing of the spectral components in meridional and vertical direction), a sophisticated filter based on 2D time–longitude spectral analysis (see Ern et al., 2011) and a vertical wavelength Butterworth filter.Critical thresholds for the vertical wavelength and zonal wavenumber are analysed. Vertical filtering has to cut deep into the gravity wave spectrum in order to remove inertial instability remnants from the perturbations (down to 6 km cutoff wavelength). Horizontal filtering, however, removes inertial instability remnants in global model data at wavenumbers far lower than the typical gravity wave scales for the case we investigated. Specifically, a cutoff zonal wavenumber of 6 in the stratosphere is sufficient to eliminate inertial instability structures. Furthermore, we show that for infrared limb-sounding satellite profiles it is possible as well to effectively separate perturbations of inertial instabilities from those of gravity waves using a cutoff zonal wavenumber of 6. We generalize the findings of our case study by examining a 1-year time series of SABER (Sounding of the Atmosphere using Broadband Emission Radiometry) data.
000884800 536__ $$0G:(DE-HGF)POF3-244$$a244 - Composition and dynamics of the upper troposphere and middle atmosphere (POF3-244)$$cPOF3-244$$fPOF III$$x0
000884800 588__ $$aDataset connected to CrossRef
000884800 7001_ $$0P:(DE-Juel1)129117$$aErn, Manfred$$b1
000884800 7001_ $$0P:(DE-Juel1)129143$$aPreusse, Peter$$b2
000884800 7001_ $$0P:(DE-Juel1)129145$$aRiese, Martin$$b3
000884800 773__ $$0PERI:(DE-600)2505596-3$$a10.5194/amt-13-4927-2020$$gVol. 13, no. 9, p. 4927 - 4945$$n9$$p4927 - 4945$$tAtmospheric measurement techniques$$v13$$x1867-8548$$y2020
000884800 8564_ $$uhttps://juser.fz-juelich.de/record/884800/files/amt-13-4927-2020.pdf$$yOpenAccess
000884800 8564_ $$uhttps://juser.fz-juelich.de/record/884800/files/amt-13-4927-2020.pdf?subformat=pdfa$$xpdfa$$yOpenAccess
000884800 8767_ $$8Helmholtz-PUC-2020-89$$92020-10-01$$d2020-10-15$$eAPC$$jZahlung erfolgt$$pamt-2020-29$$zBelegnr. 1200158044
000884800 909CO $$ooai:juser.fz-juelich.de:884800$$pdnbdelivery$$popenCost$$pVDB$$pVDB:Earth_Environment$$pdriver$$pOpenAPC$$popen_access$$popenaire
000884800 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)169715$$aForschungszentrum Jülich$$b0$$kFZJ
000884800 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)129117$$aForschungszentrum Jülich$$b1$$kFZJ
000884800 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)129143$$aForschungszentrum Jülich$$b2$$kFZJ
000884800 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)129145$$aForschungszentrum Jülich$$b3$$kFZJ
000884800 9131_ $$0G:(DE-HGF)POF3-244$$1G:(DE-HGF)POF3-240$$2G:(DE-HGF)POF3-200$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bErde und Umwelt$$lAtmosphäre und Klima$$vComposition and dynamics of the upper troposphere and middle atmosphere$$x0
000884800 9141_ $$y2020
000884800 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2020-01-18
000884800 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2020-01-18
000884800 915__ $$0LIC:(DE-HGF)CCBY4$$2HGFVOC$$aCreative Commons Attribution CC BY 4.0
000884800 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2020-01-18
000884800 915__ $$0StatID:(DE-HGF)1150$$2StatID$$aDBCoverage$$bCurrent Contents - Physical, Chemical and Earth Sciences$$d2020-01-18
000884800 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal$$d2020-01-18
000884800 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ$$d2020-01-18
000884800 915__ $$0StatID:(DE-HGF)0111$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2020-01-18
000884800 915__ $$0StatID:(DE-HGF)0700$$2StatID$$aFees$$d2020-01-18
000884800 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2020-01-18
000884800 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5$$d2020-01-18
000884800 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
000884800 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2020-01-18
000884800 915__ $$0StatID:(DE-HGF)0561$$2StatID$$aArticle Processing Charges$$f2020-01-18
000884800 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bATMOS MEAS TECH : 2018$$d2020-01-18
000884800 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2020-01-18
000884800 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2020-01-18
000884800 920__ $$lyes
000884800 9201_ $$0I:(DE-Juel1)IEK-7-20101013$$kIEK-7$$lStratosphäre$$x0
000884800 9801_ $$aFullTexts
000884800 980__ $$ajournal
000884800 980__ $$aVDB
000884800 980__ $$aUNRESTRICTED
000884800 980__ $$aI:(DE-Juel1)IEK-7-20101013
000884800 980__ $$aAPC
000884800 981__ $$aI:(DE-Juel1)ICE-4-20101013