Prediction of long lead monthly three-dimensional ocean temperature using time series gridded Argo data and a deep learning method

Prediction of long lead monthly three-dimensional ocean temperature using time series gridded Argo data and a deep learning method

Ocean temperature is a vital physical variable of the oceans. Accurately predicting the long lead dynamics of the three-dimensional ocean temperature (3D-OT) can help us identify in advance potential extreme events (e.g., droughts and floods) that may be caused by the changes of the 3D-OT, which how...

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Bibliographic Details
Main Authors: Changjiang Xiao, Xiaohua Tong, Dandan Li, Xiaojian Chen, Qiquan Yang, Xiong Xv, Hui Lin, Min Huang
Format: Article
Language:English
Published: Elsevier 2022-08-01
Series:International Journal of Applied Earth Observations and Geoinformation
Subjects:
One-dimensional convolution (Conv1D)
Long short-term memory (LSTM)
Time series gridded Argo data
Three-dimensional ocean temperature (3D-OT) prediction
Online Access:http://www.sciencedirect.com/science/article/pii/S1569843222001649

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http://www.sciencedirect.com/science/article/pii/S1569843222001649

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