Surface Turbulent Fluxes From the MOSAiC Campaign Predicted by Machine Learning

Cummins, D.P. orcid.org/0000-0003-3600-5367, Guemas, V., Cox, C.J. et al. (2 more authors) (2023) Surface Turbulent Fluxes From the MOSAiC Campaign Predicted by Machine Learning. Geophysical Research Letters, 50 (23). e2023GL105698. ISSN 0094-8276

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Item Type: Article
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© 2023. The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Keywords: artificial neural networks; machine learning; Monin-Obukhov similarity theory; surface layer; sea ice; Arctic
Dates:
  • Published: 16 December 2023
  • Published (online): 6 December 2023
  • Accepted: 26 October 2023
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Inst for Climate & Atmos Science (ICAS) (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 12 Jul 2024 10:45
Last Modified: 12 Jul 2024 10:45
Status: Published
Publisher: American Geophysical Union (AGU)
Identification Number: 10.1029/2023gl105698
Sustainable Development Goals:
  • Sustainable Development Goals: Goal 13: Climate Action
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