Nature Communications (Feb 2021)

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

  • Tom M. George,
  • Georgy E. Manucharyan,
  • Andrew F. Thompson

DOI
https://doi.org/10.1038/s41467-020-20779-9
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 11

Abstract

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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.