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sciCUN: A deep learning model for daily sea surface current fields inference—A case study of the Gulf of Riga | Synapse
March 3, 2026
sciCUN: A deep learning model for daily sea surface current fields inference—A case study of the Gulf of Riga
AB
Amirhossein Barzandeh
Tallinn University of Technology
IM
Ilja Maljutenko
Tallinn University of Technology
SR
Sander Rikka
Tallinn University of Technology
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Key Points
Enhanced inference of daily sea surface current fields was observed in the Gulf of Riga, providing better accuracy in current predictions.
The model demonstrates a significant improvement in sea surface current inference, achieving a 20% increase in accuracy compared to previous methods.
Deep learning algorithms were employed to analyze and model the daily variations in sea surface currents using extensive datasets.
These findings support advancements in marine navigation and climate studies through improved current modeling methods.
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Barzandeh et al. (Fri,) studied this question.
synapsesocial.com/papers/69a75e8fc6e9836116a29482
https://doi.org/https://doi.org/10.1016/j.ocemod.2026.102693