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Noise Reduction for Solar-Induced Fluorescence Retrievals Using Machine Learning and Principal Component Analysis: Simulations and Applications to GOME-2 Satellite Retrievals

dc.contributor.authorJoiner, Joanna
dc.contributor.authorYoshida, Yasuko
dc.contributor.authorGuanter, Luis
dc.contributor.authorLamsal, Lok
dc.contributor.authorLi, Can
dc.contributor.authorFasnacht, Zachary
dc.contributor.authorKöhler, Philipp
dc.contributor.authorFrankenberg, Christian
dc.contributor.authorSun, Ying
dc.contributor.authorParazoo, Nicholas
dc.date.accessioned2024-12-24T13:45:23Z
dc.date.available2024-12-24T13:45:23Z
dc.date.copyright01 Jul. 2024
dc.date.issued2024
dc.identifier.otheraies-AIES-D-23-0085.1.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4299557
dc.languageEnglish
dc.publisherAmerican Meteorological Society
dc.titleNoise Reduction for Solar-Induced Fluorescence Retrievals Using Machine Learning and Principal Component Analysis: Simulations and Applications to GOME-2 Satellite Retrievals
dc.typeJournal Paper
dc.journal.volume3
dc.journal.issue3
dc.journal.titleArtificial Intelligence for the Earth Systems
dc.identifier.doi10.1175/AIES-D-23-0085.1
dc.journal.lastpagee230085
dc.treeArtificial Intelligence for the Earth Systems:;2024:;volume( 003 ):;issue: 003
dc.contenttypeFulltext


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