The recently advanced approach of wavelet transform is applied to the analysis of wave data measured in the nearshore areas of the Great Lakes. The conventional spectrum analysis of wave time series in the frequency domain can be readily generalized to the frequency and time domain using the wavelet
Wave grouping characteristics in nearshore Great Lakes II
โ Scribed by Paul C. Liu; Nathan Hawley
- Book ID
- 104158924
- Publisher
- Elsevier Science
- Year
- 2002
- Tongue
- English
- Weight
- 927 KB
- Volume
- 29
- Category
- Article
- ISSN
- 0029-8018
No coin nor oath required. For personal study only.
โฆ Synopsis
This is a sequel with extensive new data to Liu's (Liu, 2000a. Wave grouping characteristics in nearshore Great Lakes. Ocean Engineering 27, 1221-1230) exploratory study on wave grouping characteristics in the nearshore Great Lakes. We analyze recent GLERL time-series measurements recorded by pressure sensors deployed at four nearshore stations in southern Lake Michigan during 1998-1999. With the advantage of continued application of time-frequency wavelet spectrum analysis, the extensive new measurements substantially confirmed the effectiveness of the empirical characterization of wave grouping parameters defined in Liu. We show that a wave group is really the basic element for a detailed understanding of wave processes, in contrast to the conventional approach of using a frequency spectrum as the basic element, which depends on the recording length and requires the data to be stationary. While studying wave time-series alone does not really alleviate the vast intricacies of the wind wave processes, the embodiment of wave grouping as the predominant feature in the wind wave processes clearly represents a significant step forward toward sound conceptual advancement.
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