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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-2016-94
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/os-2016-94
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Submitted as: research article 03 Feb 2017

Submitted as: research article | 03 Feb 2017

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This discussion paper is a preprint. It has been under review for the journal Ocean Science (OS). The revised manuscript was not accepted.

Multivariate analysis of extreme storm surges in a semi-enclosed bay

Yao Luo1, Hui Shi2, and Dongxiao Wang1 Yao Luo et al.
  • 1State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China
  • 2China Water Resources Pearl River Planning Surveying & Designing Co., Ltd., China

Abstract. The prediction of extreme storm surges is a critical task for coastal area protection. This study examines extreme storm surges in Beibu Bay, a semi-enclosed bay in the South China Sea, and their joint probabilities. A method for the advanced prediction of the extreme storm surges is proposed using a multivariate extreme statistical method. We further present practical guidelines of the proposed multivariate analysis method, including guidelines for simulation. The simulation can be extended to multidimensional data to simplify computation, so the proposed approach can be extended to use more points' data from the semi-enclosed bay for predicting extreme storm surges probabilities. A practical case study illustrates the application of the proposed techniques for extreme storm surges prediction. A comparison of the conditional probabilities obtained from observations and simulation data show that the proposed method is effective.

Yao Luo et al.
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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Interactive discussion
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Yao Luo et al.
Yao Luo et al.
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Short summary
South China Sea is a hardest-hit area of typhoon, and there are server typhoons in Beibu Bay. Satellite data and ocean model are effective method now. But this will need lots of social resources. Our method is a feasible and economical method. Now lots of hydrological stations have long surge data in china. According to these history data, we can get an extreme surge relationship between two or more stations. Combining front stations data and the relationship, we can make advanced prediction.
South China Sea is a hardest-hit area of typhoon, and there are server typhoons in Beibu Bay....
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