The introduction of students to methods of time-series analysis is a pedagogical challenge, since the availability of easily manipulated computer software presents an attractive alternative to an understanding of the computations, as well as their assumptions and limitations. A two-part pedagogical tutorial exercise is offered as a hands-on laboratory to complement classroom discussions or as a reference for students involved in independent research projects. The exercises are focused on the analysis of ocean waves, specifically wind-generated surface gravity waves. The exercises are cross-disciplinary in nature and can be extended to any other field dealing with random signal analysis. The first exercise introduces the manual arithmetic steps of a finite Fourier analysis of a wave record, develops a spectrum, and compares these results to the results obtained using a fast Fourier transform (FFT). The second part of the exercise, described in the subsequent article, takes a longer wave record and addresses the theoretical and observed wave probability distributions of wave heights and sea surface elevations. These results are then compared to a FFT, thus linking the two pedagogical laboratory exercise parts for a more complete understanding of both exercises.

A series of tests has been conducted to investigate the increased ice-water drag exhibited by ice floes in two-layer, salinity-stratified water. Scaled model tests are used to quantify the additional drag due to internal wave creation at the fresh water-salt water interface. This additional drag is shown to have a peak value five times the drag in similar unstratified conditions and to have a strong dependence on a few well-defined nondimensional parameters describing the ice and wate r characteristics.

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This paper describes the second of a two-part series of pedagogical exercises to introduce students to methods of time-series analysis. While these exercises are focused on the analysis of wind generated surface gravity waves, they are cross-disciplinary in nature and can be applied to other fields dealing with random signal analysis. Two computer laboratory exercises are presented which enable students to understand many of the facets of random signal analysis with less difficulty and more understanding than standard classroom instruction alone. The first pedagogical exercise, described in the previous article, uses mathematical software on which the students execute the manual arithmetic operations of a finite Fourier analysis on a complex wave record. The results are then compared to those obtained by a fast Fourier transform. This article, the second of this two-part pedagogical series, addresses analysis of a complex sea using observed and theoretical wave height and water surface elevation probability distributions and wave spectra. These results are compared to a fast Fourier transform analysis, thus providing a link back to the first exercise.

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