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Prediction of sea surface pCO2 in the South China Sea using Spatiotemporal Convolutional LSTM model

Shuang LI Yu GAO Jiannan GAO Yaqi ZHAO Peng HAO Jinbao SONG Chengcheng YU

海洋湖沼学报（英文版）2026，Vol.44Issue(1)：19-35,17.

海洋湖沼学报（英文版）2026，Vol.44Issue(1)：19-35,17.DOI:10.1007/s00343-025-4257-3

Prediction of sea surface pCO2 in the South China Sea using Spatiotemporal Convolutional LSTM model

Shuang LI ¹Yu GAO ¹Jiannan GAO ¹Yaqi ZHAO ¹Peng HAO ¹Jinbao SONG ¹Chengcheng YU²

作者信息

1. Ocean College,Zhejiang University,Zhoushan 316021,China
2. Marine Science and Technology College,Zhejiang Ocean University,Zhoushan 316004,China
折叠

摘要

关键词

sea surface carbon dioxide/South China Sea/Spatiotemporal Convolutional Long Short-Term Memory(ST-ConvLSTM)/deep learning

Key words

sea surface carbon dioxide/South China Sea/Spatiotemporal Convolutional Long Short-Term Memory(ST-ConvLSTM)/deep learning

引用本文复制引用

Shuang LI,Yu GAO,Jiannan GAO,Yaqi ZHAO,Peng HAO,Jinbao SONG,Chengcheng YU..Prediction of sea surface pCO2 in the South China Sea using Spatiotemporal Convolutional LSTM model[J].海洋湖沼学报（英文版）,2026,44(1):19-35,17.

基金项目

Supported by the National Key Research and Development Program of China(No.2023YFC3008202),the National Natural Science Foundation of China(No.42406019),and the Scientific Research Fund of Zhejiang Provincial Education Department(No.Y202353066) （No.2023YFC3008202）

海洋湖沼学报（英文版）

ISSN：2096-5508

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