Spatiotemporal wave forecast with transformer-based network: A case study for the northwestern Pacific Ocean-Reference-Cited by-同舟云学术

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Spatiotemporal wave forecast with transformer-based network: A case study for the northwestern Pacific Ocean

Published:2024-04 Issue: Volume:188 Page:102323
ISSN:1463-5003
Container-title:Ocean Modelling
language:en
Short-container-title:Ocean Modelling

Author:

Liu Yong,Lu Wenfang,Wang Dong,Lai Zhigang,Ying Chao,Li Xinwen,Han Ying,Wang Zhifeng,Dong Changming

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Basic Public Welfare Research Program of Zhejiang Province

Southern Marine Science and Engineering Guangdong Laboratory

Publisher

Elsevier BV

Reference61 articles.

1. Ocean waves in large-scale air-sea weather and climate systems;Babanin;J. Geophys. Res.: Oceans,2023

2. Ocean wave energy forecasting using optimised deep learning neural networks;Bento;Ocean Eng.,2021

3. Accurate medium-range global weather forecasting with 3D neural networks;Bi;Nature,2023

4. Detection of marine oil-like features in Sentinel-1 SAR images by supplementary use of deep learning and empirical methods: performance assessment for the Great Barrier Reef marine park;Blondeau-Patissier;Mar. Pollut. Bull.,2023

5. Applications of deep learning to ocean data inference and subgrid parameterization;Bolton;J. Adv. Model. Earth Syst.,2019

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2. Comment on papers using machine learning for significant wave height time series prediction: Complex models do not outperform auto-regression;Ocean Modelling;2024-06

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