000866830 001__ 866830
000866830 005__ 20240712100953.0
000866830 0247_ $$2doi$$a10.5194/gmd-12-1725-2019
000866830 0247_ $$2ISSN$$a1991-959X
000866830 0247_ $$2ISSN$$a1991-9603
000866830 0247_ $$2Handle$$a2128/23478
000866830 0247_ $$2WOS$$aWOS:000466601200001
000866830 037__ $$aFZJ-2019-05893
000866830 082__ $$a550
000866830 1001_ $$0P:(DE-Juel1)151210$$aHuijnen, Vincent$$b0$$eCorresponding author
000866830 245__ $$aQuantifying uncertainties due to chemistry modelling – evaluation of tropospheric composition simulations in the CAMS model (cycle 43R1)
000866830 260__ $$aKatlenburg-Lindau$$bCopernicus$$c2019
000866830 3367_ $$2DRIVER$$aarticle
000866830 3367_ $$2DataCite$$aOutput Types/Journal article
000866830 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1574790477_2214
000866830 3367_ $$2BibTeX$$aARTICLE
000866830 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000866830 3367_ $$00$$2EndNote$$aJournal Article
000866830 520__ $$aWe report on an evaluation of tropospheric ozone and its precursor gases in three atmospheric chemistry versions as implemented in the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS), referred to as IFS(CB05BASCOE), IFS(MOZART) and IFS(MOCAGE). While the model versions were forced with the same overall meteorology, emissions, transport and deposition schemes, they vary largely in their parameterisations describing atmospheric chemistry, including the organics degradation, heterogeneous chemistry and photolysis, as well as chemical solver. The model results from the three chemistry versions are compared against a range of aircraft field campaigns, surface observations, ozone-sondes and satellite observations, which provides quantification of the overall model uncertainty driven by the chemistry parameterisations. We find that they produce similar patterns and magnitudes for carbon monoxide (CO) and ozone (O3), as well as a range of non-methane hydrocarbons (NMHCs), with averaged differences for O3 (CO) within 10 % (20 %) throughout the troposphere. Most of the divergence in the magnitude of CO and NMHCs can be explained by differences in OH concentrations, which can reach up to 50 %, particularly at high latitudes. There are also comparatively large discrepancies between model versions for NO2, SO2 and HNO3, which are strongly influenced by secondary chemical production and loss. Other common biases in CO and NMHCs are mainly attributed to uncertainties in their emissions. This configuration of having various chemistry versions within IFS provides a quantification of uncertainties induced by chemistry modelling in the main CAMS global trace gas products beyond those that are constrained by data assimilation.
000866830 536__ $$0G:(DE-HGF)POF3-243$$a243 - Tropospheric trace substances and their transformation processes (POF3-243)$$cPOF3-243$$fPOF III$$x0
000866830 588__ $$aDataset connected to CrossRef
000866830 7001_ $$00000-0003-2440-6104$$aPozzer, Andrea$$b1
000866830 7001_ $$0P:(DE-HGF)0$$aArteta, Joaquim$$b2
000866830 7001_ $$0P:(DE-HGF)0$$aBrasseur, Guy$$b3
000866830 7001_ $$0P:(DE-HGF)0$$aBouarar, Idir$$b4
000866830 7001_ $$00000-0003-4378-1567$$aChabrillat, Simon$$b5
000866830 7001_ $$00000-0003-3243-5036$$aChristophe, Yves$$b6
000866830 7001_ $$0P:(DE-HGF)0$$aDoumbia, Thierno$$b7
000866830 7001_ $$00000-0003-4880-5329$$aFlemming, Johannes$$b8
000866830 7001_ $$00000-0001-5768-1992$$aGuth, Jonathan$$b9
000866830 7001_ $$0P:(DE-HGF)0$$aJosse, Béatrice$$b10
000866830 7001_ $$0P:(DE-Juel1)176592$$aKarydis, Vlassis A.$$b11$$ufzj
000866830 7001_ $$0P:(DE-HGF)0$$aMarécal, Virginie$$b12
000866830 7001_ $$0P:(DE-HGF)0$$aPelletier, Sophie$$b13
000866830 773__ $$0PERI:(DE-600)2456725-5$$a10.5194/gmd-12-1725-2019$$gVol. 12, no. 4, p. 1725 - 1752$$n4$$p1725 - 1752$$tGeoscientific model development$$v12$$x1991-9603$$y2019
000866830 8564_ $$uhttps://juser.fz-juelich.de/record/866830/files/gmd-12-1725-2019.pdf$$yOpenAccess
000866830 8564_ $$uhttps://juser.fz-juelich.de/record/866830/files/gmd-12-1725-2019.pdf?subformat=pdfa$$xpdfa$$yOpenAccess
000866830 909CO $$ooai:juser.fz-juelich.de:866830$$pdnbdelivery$$pVDB$$pVDB:Earth_Environment$$pdriver$$popen_access$$popenaire
000866830 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)176592$$aForschungszentrum Jülich$$b11$$kFZJ
000866830 9131_ $$0G:(DE-HGF)POF3-243$$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$$vTropospheric trace substances and their transformation processes$$x0
000866830 9141_ $$y2019
000866830 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS
000866830 915__ $$0LIC:(DE-HGF)CCBY4$$2HGFVOC$$aCreative Commons Attribution CC BY 4.0
000866830 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search
000866830 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bGEOSCI MODEL DEV : 2017
000866830 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal
000866830 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ
000866830 915__ $$0StatID:(DE-HGF)0111$$2StatID$$aWoS$$bScience Citation Index Expanded
000866830 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection
000866830 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5
000866830 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
000866830 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC
000866830 915__ $$0StatID:(DE-HGF)1150$$2StatID$$aDBCoverage$$bCurrent Contents - Physical, Chemical and Earth Sciences
000866830 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List
000866830 9201_ $$0I:(DE-Juel1)IEK-8-20101013$$kIEK-8$$lTroposphäre$$x0
000866830 9801_ $$aFullTexts
000866830 980__ $$ajournal
000866830 980__ $$aVDB
000866830 980__ $$aUNRESTRICTED
000866830 980__ $$aI:(DE-Juel1)IEK-8-20101013
000866830 981__ $$aI:(DE-Juel1)ICE-3-20101013