Improving ocean reanalyses of observationally sparse regions with transfer learning

Abstract Oceanic subsurface observations are sparse and lead to large uncertainties in any model-based estimate. We investigate the applicability of transfer learning based neural networks to reconstruct North Atlantic temperatures in times with sparse observations. Our network is trained on a time...

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Bibliographic Details
Main Authors: Simon Lentz, Sebastian Brune, Christopher Kadow, Johanna Baehr
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
Online Access:https://doi.org/10.1038/s41598-025-86374-4
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