Deep Learning Models to Predict Sea Surface Temperature in Tohoku Region

Deep Learning Models to Predict Sea Surface Temperature in Tohoku Region

The prediction of sea surface temperature (SST) is a challenging task, especially for regions with high SST variability. Such predictions are either achieved by physics-based models, which often yield poor predictions and are computationally intensive, or by using data-driven methods, which are skil...

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Bibliographic Details
Main Authors: Kalpesh R. Patil, Masaaki Iiyama
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Deep multi-layer perceptron (Deep MLP)
spatial 2-dimensional convolutional neural network (spatial 2D CNN)
long short-term memory networks (LSTM)
deep learning for SST prediction
meteorologic parameter forced SST prediction
Online Access:https://ieeexplore.ieee.org/document/9756452/

Internet

https://ieeexplore.ieee.org/document/9756452/

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