Ocean Science
Ocean Science
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Articles | Volume 15, issue 2
Articles | Volume 15, issue 2
https://doi.org/10.5194/os-15-349-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-15-349-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 15, issue 2
Research article
 | 
05 Apr 2019
Research article |  | 05 Apr 2019

Hybrid improved empirical mode decomposition and BP neural network model for the prediction of sea surface temperature

Zhiyuan Wu, Changbo Jiang, Mack Conde, Bin Deng, and Jie Chen

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Short summary
Sea surface temperature (SST) is related to ocean heat content, an important topic in the debate over global warming. In this paper, we propose a novel SST-predicting method based on the hybrid improved EMD algorithms and BP neural network method. SST prediction results based on the hybrid EEMD-BPNN and CEEMD-BPNN models are compared and discussed. A case study of SST in the North Pacific shows that the proposed hybrid CEEMD-BPNN model can effectively predict the time-series SST.
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