001052339 001__ 1052339
001052339 005__ 20260123203315.0
001052339 0247_ $$2doi$$a10.5194/gmd-18-8777-2025
001052339 0247_ $$2ISSN$$a1991-959X
001052339 0247_ $$2ISSN$$a1991-9603
001052339 0247_ $$2datacite_doi$$a10.34734/FZJ-2026-00942
001052339 037__ $$aFZJ-2026-00942
001052339 082__ $$a550
001052339 1001_ $$00000-0001-7437-0846$$aHickman, Sebastian H. M.$$b0
001052339 245__ $$aApplications of Machine Learning and Artificial Intelligence in Tropospheric Ozone Research
001052339 260__ $$aKatlenburg-Lindau$$bCopernicus$$c2025
001052339 3367_ $$2DRIVER$$aarticle
001052339 3367_ $$2DataCite$$aOutput Types/Journal article
001052339 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1769154827_24946
001052339 3367_ $$2BibTeX$$aARTICLE
001052339 3367_ $$2ORCID$$aJOURNAL_ARTICLE
001052339 3367_ $$00$$2EndNote$$aJournal Article
001052339 520__ $$aMachine learning (ML) is transforming atmospheric chemistry, offering powerful tools to address challenges in tropospheric ozone research, a critical area for climate resilience and public health. As in adjacent fields, ML approaches complement existing research by learning patterns from ever-increasing volumes of atmospheric and environmental data relevant to ozone. We highlight the rapid progress made in the field since Phase 1 of the Tropospheric Ozone Assessment Report (TOAR), focussing particularly on the most active areas of research, namely short-term ozone forecasting, emulation of atmospheric chemistry and the use of remote sensing for ozone estimation. This review provides a comprehensive synthesis of recent advancements, highlights critical challenges, and proposes actionable pathways to develop ML in ozone research. Further advances hinge on addressing domain-specific issues such as the dependence of ozone concentrations on several poorly observed precursor species, as well as making progress on generic ML challenges such as the definition of suitable benchmarks and developing robust, explainable models. Reaping the full potential of ML for ozone research and operational applications will require close collaborations across atmospheric chemistry, ML and computational science and vigilant pursuit of the rapid developments in adjacent fields.
001052339 536__ $$0G:(DE-HGF)POF4-5111$$a5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511)$$cPOF4-511$$fPOF IV$$x0
001052339 536__ $$0G:(DE-Juel-1)ESDE$$aEarth System Data Exploration (ESDE)$$cESDE$$x1
001052339 536__ $$0G:(EU-Grant)787576$$aIntelliAQ - Artificial Intelligence for Air Quality (787576)$$c787576$$fERC-2017-ADG$$x2
001052339 588__ $$aDataset connected to CrossRef, Journals: juser.fz-juelich.de
001052339 7001_ $$0P:(DE-HGF)0$$aKelp, Makoto M.$$b1
001052339 7001_ $$00000-0002-1089-340X$$aGriffiths, Paul T.$$b2$$eCorresponding author
001052339 7001_ $$0P:(DE-HGF)0$$aDoerksen, Kelsey$$b3
001052339 7001_ $$00000-0002-1466-4655$$aMiyazaki, Kazuyuki$$b4
001052339 7001_ $$0P:(DE-HGF)0$$aPennington, Elyse A.$$b5
001052339 7001_ $$00000-0002-2275-0713$$aKoren, Gerbrand$$b6
001052339 7001_ $$00000-0003-3403-8245$$aIglesias-Suarez, Fernando$$b7
001052339 7001_ $$0P:(DE-Juel1)6952$$aSchultz, Martin G.$$b8
001052339 7001_ $$00000-0001-5812-3183$$aChang, Kai-Lan$$b9
001052339 7001_ $$0P:(DE-HGF)0$$aCooper, Owen R.$$b10
001052339 7001_ $$0P:(DE-HGF)0$$aArchibald, Alex$$b11
001052339 7001_ $$00000-0002-2728-5814$$aSommariva, Roberto$$b12
001052339 7001_ $$00000-0003-1005-6385$$aCarlson, David$$b13
001052339 7001_ $$0P:(DE-HGF)0$$aWang, Hantao$$b14
001052339 7001_ $$00000-0001-5652-4987$$aWest, J. Jason$$b15
001052339 7001_ $$00000-0001-8326-3698$$aLiu, Zhenze$$b16
001052339 773__ $$0PERI:(DE-600)2456725-5$$a10.5194/gmd-18-8777-2025$$gVol. 18, no. 22, p. 8777 - 8800$$n22$$p8777 - 8800$$tGeoscientific model development$$v18$$x1991-959X$$y2025
001052339 8564_ $$uhttps://juser.fz-juelich.de/record/1052339/files/gmd-18-8777-2025.pdf$$yOpenAccess
001052339 909CO $$ooai:juser.fz-juelich.de:1052339$$popenaire$$popen_access$$pdriver$$pVDB$$pec_fundedresources$$pdnbdelivery
001052339 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)6952$$aForschungszentrum Jülich$$b8$$kFZJ
001052339 9131_ $$0G:(DE-HGF)POF4-511$$1G:(DE-HGF)POF4-510$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5111$$aDE-HGF$$bKey Technologies$$lEngineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action$$vEnabling Computational- & Data-Intensive Science and Engineering$$x0
001052339 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2024-12-21
001052339 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2024-12-21
001052339 915__ $$0LIC:(DE-HGF)CCBY4$$2HGFVOC$$aCreative Commons Attribution CC BY 4.0
001052339 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2024-12-21
001052339 915__ $$0StatID:(DE-HGF)1150$$2StatID$$aDBCoverage$$bCurrent Contents - Physical, Chemical and Earth Sciences$$d2024-12-21
001052339 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal$$d2022-12-20T09:29:04Z
001052339 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ$$d2022-12-20T09:29:04Z
001052339 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2024-12-21
001052339 915__ $$0StatID:(DE-HGF)0700$$2StatID$$aFees$$d2024-12-21
001052339 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2024-12-21
001052339 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
001052339 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2024-12-21
001052339 915__ $$0StatID:(DE-HGF)0561$$2StatID$$aArticle Processing Charges$$d2024-12-21
001052339 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2024-12-21
001052339 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2024-12-21
001052339 9201_ $$0I:(DE-Juel1)JSC-20090406$$kJSC$$lJülich Supercomputing Center$$x0
001052339 9801_ $$aFullTexts
001052339 980__ $$ajournal
001052339 980__ $$aVDB
001052339 980__ $$aUNRESTRICTED
001052339 980__ $$aI:(DE-Juel1)JSC-20090406