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The relationship between significant wave height ( H 1 / 3 ) and period ( T 1 / 3 ) was obtained using wave data from the East and Yellow coasts of the Korean Peninsula to facilitate the calculations of the wave parameters. In addition, the JONSWAP spectral parameters were estimated and analyzed for all wave height ranges. The relational expression between the two wave variables ( H 1 / 3 ~ T 1 / 3 ) obtained from this study showed a significant difference from the previously proposed relational expressions, most of which tended to follow the lower limit of the data. Meanwhile, the suggested peak enhancement factor (PEF,   γ ) is 1–7; however, for this study, a peak control factor (PCF,   γ c ) with a range of 0–10 was introduced. As a result of the analysis, the PCF was determined to be 1.13–1.42, which is approximately 40% smaller than the previously proposed γ   =   3.3 . The probability density distribution of the appropriate PCF was then calculated, and the gamma and log-normal distributions for the East and Yellow coasts of the Korean Peninsula were found, respectively. This study covered waves of all range heights, and the analysis results can be used as important data to explain the characteristics of the sea area. [ABSTRACT FROM AUTHOR]

Thirty two-year observations (1990–2022) of water level from a total of 14 high-quality acoustic tide stations around the coast of Australia deployed for the Australian Baseline Sea Level Monitoring Project were analyzed. The following three approaches were used: Fourier Transform (FT), Empirical Mode Decomposition (EMD), and Singular Spectrum Analysis (SSA). The water level anomaly was observed to have predominant annual variations with a period of about 12 months based on the Fourier transform. The intrinsic components of stations were extracted in the EMD analysis and the mean period of each of the components was calculated using the zero down crossing method. A regular association was observed between the order of modes and the mean period such that the periods increase by a factor of two on successive modes. The third method used for anomaly analysis was SSA. The number of the obtained components in this method was less than in the EMD. Moreover, the order observed for the components' period in the EMD was not seen in this method. Spectral analysis of Autocorrelation function (ACF) has demonstrated that peak frequencies are almost the same with anomaly spectra so the dominant modes in anomalies are also present in the ACF. • More than 30-year sea level data around the Australian coast have been analyzed. • Fourier Transform, Empirical Mode Decomposition, and Singular Spectrum Analysis have been used. • A predominant annual variation with a period of about 12 months was observed based on the Fourier transform. ACF analysis showed that: ✓ The periodic and regular signals have larger ACF with low rate decreasing amplitude. ✓ Irregular signal has a smaller ACF and its amplitude decreases more sever. ✓ In general, the more regular the time series, the more symmetrical its ACF. ✓ Spectral analysis of anomalies and ACF has demonstrated that peak frequencies are almost the same in both spectra. [ABSTRACT FROM AUTHOR]