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dc.contributor.authorAwasthi, Amit
dc.contributor.authorPattnayak, Kanhu Charan
dc.contributor.authorTiwari, Pushp Raj
dc.date.accessioned2025-01-20T11:15:01Z
dc.date.available2025-01-20T11:15:01Z
dc.date.issued2025-01-03
dc.identifier.citationAwasthi , A , Pattnayak , K C & Tiwari , P R 2025 , ' Editorial: Application of artificial intelligence-supported process-based climate models to understand the atmosphere/weather patterns and their prediction ' , Frontiers in Environmental Science , vol. 12 , pp. 1-3 . https://doi.org/10.3389/fenvs.2024.1543951
dc.identifier.issn2296-665X
dc.identifier.otherJisc: 2598812
dc.identifier.otherpublisher-id: 1543951
dc.identifier.urihttp://hdl.handle.net/2299/28714
dc.description© 2025 The Author(s). This is an open access Editorial distributed under the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/
dc.format.extent3
dc.format.extent521758
dc.language.isoeng
dc.relation.ispartofFrontiers in Environmental Science
dc.subjectweather pattern
dc.subjectclimate change
dc.subjectclimate model
dc.subjectweather prediction
dc.subjectartificial intelligence (AI)
dc.titleEditorial: Application of artificial intelligence-supported process-based climate models to understand the atmosphere/weather patterns and their predictionen
dc.contributor.institutionCentre for Atmospheric and Climate Physics Research
dc.contributor.institutionCentre for Future Societies Research
dc.contributor.institutionCentre for Climate Change Research (C3R)
dc.contributor.institutionDepartment of Physics, Astronomy and Mathematics
dc.contributor.institutionSchool of Physics, Engineering & Computer Science
dc.description.statusPeer reviewed
rioxxterms.versionofrecord10.3389/fenvs.2024.1543951
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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