Systematic multi-scale decomposition of ocean variability using machine learning | Zendy

Christian Franzke | Zendy; Federica Gugole | Zendy; Stephan Juricke | Zendy

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Systematic multi-scale decomposition of ocean variability using machine learning

Author(s) -

Christian Franzke,

Federica Gugole,

Stephan Juricke

Publication year - 2022

Publication title -

chaos an interdisciplinary journal of nonlinear science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.971

H-Index - 113

eISSN - 1089-7682

pISSN - 1054-1500

DOI - 10.1063/5.0090064

Subject(s) - empirical orthogonal functions , hilbert–huang transform , sea surface temperature , oscillation (cell signaling) , sea surface height , scale (ratio) , mode (computer interface) , ocean dynamics , dynamical systems theory , transient (computer programming) , position (finance) , decomposition , meteorology , ocean current , computer science , climatology , physics , geology , mathematics , statistics , finance , white noise , quantum mechanics , biology , economics , genetics , operating system , ecology

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