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Ocean Science An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/os-2018-116
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-2018-116
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 01 Nov 2018

Research article | 01 Nov 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Ocean Science (OS).

A simple predictive model for the eddy propagation trajectory in the South China Sea

Jiaxun Li1,2, Guihua Wang1, Huijie Xue3,4, and Huizan Wang5 Jiaxun Li et al.
  • 1Department of Atmospheric and Oceanic Sciences, Institute of Atmospheric Science, Fudan University, Shanghai, China
  • 2Naval Institute of Hydrographic Surveying and Charting, Tianjin, China
  • 3State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China
  • 4School of Marine Sciences, University of Maine, Orono, Maine, USA
  • 5Institute of Meteorology and Oceanography, National University of Defense Technology, Nanjing, China

Abstract. A novel predictive model is built for eddy propagation trajectory using the multiple linear regression method. This simple model has related various oceanic parameters to eddy propagation position changes in the South China Sea (SCS). These oceanic parameters mainly represent the effects of planetary β and mean flow advection on the eddy propagation. The performance of the proposed model is examined in the SCS based on twenty years of satellite altimeter data, and demonstrates its significant forecast skills over a 4-week forecast window comparing to the traditional persistence method. It is also found that the model forecast accuracy is sensitive to eddy polarity and forecast season.

Jiaxun Li et al.
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Short summary
A novel predictive model is built for eddy propagation trajectory using the multiple linear regression method. This simple model has related various oceanic parameters to eddy propagation position changes in the South China Sea (SCS). The performance of the proposed model is examined in the SCS based on twenty years of satellite altimeter data, and demonstrates its significant forecast skills over a 4-week forecast window comparing to the traditional persistence method.
A novel predictive model is built for eddy propagation trajectory using the multiple linear...
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