Wave height statistical characteristic analysis -- Journal of Oceanology and Limnology,2019,37(2):448-460

	Cite this paper:
	LIU Guilin, CHEN Baiyu, WANG Liping, ZHANG Shuaifang, ZHANG Kuangyuan, LEI Xi. Wave height statistical characteristic analysis[J]. Journal of Oceanology and Limnology, 2019, 37(2): 448-460

Wave height statistical characteristic analysis

LIU Guilin¹, CHEN Baiyu², WANG Liping³, ZHANG Shuaifang⁴, ZHANG Kuangyuan⁵, LEI Xi³

1 College of Engineering, Ocean University of China, Qingdao 266100, China;
2 College of Engineering, University of California Berkeley, CA 94720, USA;
3 College of Mathematical Science, Ocean University of China, Qingdao 266100, China;
4 Department of Mechanical Engineering, University of Florida, Gainesville, USA;
5 Department of Economics, Penn State University, State College, USA

Abstract:

When exploring the temporal and spatial change law of ocean environment, the most common method used is using smaller-scale observed data to derive the change law for a larger-scale system. For instance, using 30-year observation data to derive 100-year return period design wave height. Therefore, the study of inherent self-similarity in ocean hydrological elements becomes increasingly important to the study of multi-year return period design wave height derivation. In this paper, we introduced multifractal to analyze the statistical characteristics of wave height series data observed from oceanic hydrological station. An improvement is made to address the existing problems of the multifractal detrended fluctuation analysis (MF-DFA) method, where trend function showed a discontinuity between intervals. The improved MFDFA method is based on signal mode decomposition, replacing piecewise polynomial fitting used in the original method. We applied the proposed method to the wave height data collected at Chaolian Island, Shandong, China, from 1963 to 1989 and was able to conclude the wave height sequence presented weak multi-fractality. This result provided strong support to the past research on the derivation of multi-year return period design wave height with observed data. Moreover, the new method proposed in this paper also provides a new perspective to explore the intrinsic characteristic of data.

Key words: wave height|partition function|multifractal spectrum|multifractal detrended fluctuation analysis (MF-DFA)|signal mode decomposition

Received: 2018-01-07 Revised: 2018-03-13

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Articles by LIU Guilin

Articles by CHEN Baiyu

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Articles by LEI Xi

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