Deep learning to infer eddy heat fluxes from sea surface height patterns of mesoscale turbulence

Eddy heat fluxes crucially affect large-scale oceanic currents but are challenging to monitor on a global scale. Here the authors develop a Deep Learning model to predict the eddy heat fluxes from sea surface height data only, bypassing the need for simultaneous observations of the deep ocean.

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Auteurs principaux: Tom M. George, Georgy E. Manucharyan, Andrew F. Thompson
Format: article
Langue:EN
Publié: Nature Portfolio 2021
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Accès en ligne:https://doaj.org/article/c7651d6337f64a0bb9c40bf8010fa9bc
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