WIT Press


Detrended Fluctuation Analysis Of Significant Wave Height Time Series

Price

Free (open access)

Paper DOI

10.2495/CP110281

Volume

149

Pages

9

Page Range

333 - 341

Published

2011

Size

324 kb

Author(s)

L. Cabrera & G. Rodríguez

Abstract

Mean daily significant wave height time series are analysed by means of the detrended fluctuation analysis (DFA) method to examine the existence of longrange correlations, or long memory. The results indicate that the scaling behavior of significant wave height fluctuations is not constant over the considered time scales but there is a decrease of the scaling exponent with increasing time scale. Two crossover times have been identified, indicating three different scaling behaviors. Fluctuations associated to time scales between 10 and 100 days, approximately, show long-range correlation while fluctuations above and below this range present white and Brownian noise-like behavior, respectively. 1 Introduction The knowledge of sea state conditions is critical not only for studying many oceanic and atmospheric processes but also for many offshore and nearshore operations. The evolution of sea state conditions is also of utmost importance in coastal erosion, several questions concerning safety, reliability and feasibility of offshore activities, as well as in maritime transport. It has been highlighted by many researchers [1, 2] that the design and construction of marine structures and the coastal and offshore development activities require a relatively accurate knowledge of wave conditions to be expected during those activities and the expected lifetime of the structures. However, acquiring accurate knowledge of wave conditions evolution proves to be a difficult task. Ocean wind waves are generated in the interface connecting the turbulent boundary layers of air and water. The coupling of these two different viscous fluids is strong and nonlinear. Waves are inherently forced by the wind, break intermittently and interact strongly with surrounding turbulence. Moreover, in

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