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Li, Qin, Xu, Yan, Verma, Meetu, Denker, Carsten, Zhao, Junwei, Wang, Haimin (2023) Study of Global Photospheric and Chromospheric Flows Using Local Correlation Tracking and Machine Learning Methods I: Methodology and Uncertainty Estimates. Solar Physics, 298 (5) doi:10.1007/s11207-023-02158-x

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Reference TypeJournal (article/letter/editorial)
TitleStudy of Global Photospheric and Chromospheric Flows Using Local Correlation Tracking and Machine Learning Methods I: Methodology and Uncertainty Estimates
JournalSolar Physics
AuthorsLi, QinAuthor
Xu, YanAuthor
Verma, MeetuAuthor
Denker, CarstenAuthor
Zhao, JunweiAuthor
Wang, HaiminAuthor
Year2023 (May)Volume298
Issue5
PublisherSpringer Science and Business Media LLC
DOIdoi:10.1007/s11207-023-02158-xSearch in ResearchGate
Generate Citation Formats
Mindat Ref. ID15838892Long-form Identifiermindat:1:5:15838892:4
GUID0
Full ReferenceLi, Qin, Xu, Yan, Verma, Meetu, Denker, Carsten, Zhao, Junwei, Wang, Haimin (2023) Study of Global Photospheric and Chromospheric Flows Using Local Correlation Tracking and Machine Learning Methods I: Methodology and Uncertainty Estimates. Solar Physics, 298 (5) doi:10.1007/s11207-023-02158-x
Plain TextLi, Qin, Xu, Yan, Verma, Meetu, Denker, Carsten, Zhao, Junwei, Wang, Haimin (2023) Study of Global Photospheric and Chromospheric Flows Using Local Correlation Tracking and Machine Learning Methods I: Methodology and Uncertainty Estimates. Solar Physics, 298 (5) doi:10.1007/s11207-023-02158-x
In(2023, May) Solar Physics Vol. 298 (5) Springer Science and Business Media LLC

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