Influence of Wave Breaking on Wave Statistics for Finite-Depth Random Wave Trains

The influence of wave breaking on wave statistics for finite-depth random wave trains is investigated experimentally. This paper is to investigate the influence of wave breaking and water depth on the wave statistics for random waves on water of finite depth. Greater attention is paid to changes in wave statistics due to wave breaking in random wave trains. The results show skewness of surface elevations is independent of wave breaking and kurtosis is suppressed by wave breaking. Finally, the exceedance probabilities for wave heights are also investigated.

Wave Energy Estimation by Using A Statistical Analysis and Wave Buoy Data near the Southern Caspian Sea

Statistical analysis was done on simultaneous wave and wind using data recorded by discus-shape wave buoy. The area is located in the southern Caspian Sea near the Anzali Port. Recorded wave data were obtained through directional spectrum wave analysis. Recorded wind direction and wind speed were obtained through the related time series as well. For 12-month measurements（May 25 2007-2008）, statistical calculations were done to specify the value of nonlinear auto-correlation of wave and wind using the probability distribution function of wave characteristics and statistical analysis in various time periods. The paper also presents and analyzes the amount of wave energy for the area mentioned on the basis of available database. Analyses showed a suitable comparison between the amounts of wave energy in different seasons. As a result, the best period for the largest amount of wave energy was known. Results showed that in the research period, the mean wave and wind auto correlation were about three hours. Among the probability distribution functions, i.e Weibull, Normal, Lognormal and Rayleigh, ＂Weibull＂ had the best consistency with experimental distribution function shown in different diagrams for each season. Results also showed that the mean wave energy in the research period was about 49.88 k W/m and the maximum density of wave energy was found in February and March, 2010.

Global Statistical Study of Ionospheric Waves Based on COSMIC GPS Radio Occultation Data

Extracting and parameterizing ionospheric waves globally and statistically is a longstanding problem. Based on the multichannel maximum entropy method（MMEM） used for studying ionospheric waves by previous work, we calculate the parameters of ionospheric waves by applying the MMEM to numerously temporally approximate and spatially close global-positioning-system radio occultation total electron content profile triples provided by the unique clustered satellites flight between years 2006 and 2007 right after the constellation observing system for meteorology, ionosphere, and climate（COSMIC） mission launch. The results show that the amplitude of ionospheric waves increases at the low and high latitudes（~0.15 TECU） and decreases in the mid-latitudes（~0.05 TECU）. The vertical wavelength of the ionospheric waves increases in the mid-latitudes（e.g., ~50 km at altitudes of 200–250 km） and decreases at the low and high latitudes（e.g., ~35 km at altitudes of 200–250 km）.The horizontal wavelength shows a similar result（e.g., ~1400 km in the mid-latitudes and ~800 km at the low and high latitudes）.

The difference between the joint probability distributions of apparent wave heights and periods and individual wave heights and periods

The joint distribution of wave heights and periods of individual waves is usually approximated by the joint distribution of apparent wave heights and periods. However there is difference between them. This difference is addressed and the theoretical joint distributions of apparent wave heights and periods due to Longuet-Higgins and Sun are modified to give more reasonable representations of the joint distribution of wave heights and periods of individual waves. The modification has overcome an inherent drawback of these joint PDFs that the mean wave period is infinite. A comparison is made between the modified formulae and the field data of Goda, which shows that the new formulae consist with the measurement better than their original counterparts.

Probabilistic Models for the Probability of Wave Breaking and Whitecap Coverage Based on Kinematic Breaking Criterion

More and more researches show that neither the critical downward acceleration nor the critical slope of water waves is a universal constant. On the contrary, they vary with particular wave conditions. This fact renders the models either for the probability of wave breaking B or for the whitecap coverage W based on these criteria difficult to apply. In this paper and the one which follows we seek to develop models for the prediction of both B and W based on the kinematical criterion. First, several joint probabilistic distribution functions (PDFs) of wave characteristics are derived, based on which the breaking properties B and W are estimated. The estimation is made on the assumption that a wave breaks if the horizontal velocity of water particles at its crest exceeds the local wave celerity, and whitecapping occurs in regions of fluid where water particles travel faster than the waves. The consequent B and W depend on wave spectral moments of orders 0 to 4. Then the JONSWAP spectrum is used to represent the fetch limited sea waves in deep water, so as to relate the probability of wave breaking and the whitecap coverage with wind parameters. To this end, the time averaging technique proposed by Glazman (1986) is applied to the estimation of the spectral moments involved, and furthermore, the theoretical models are compared with available observations collected from published literature. From the comparison, the averaging time scale is determined. The final models show that the probability of wave breaking as well as the whitecap coverage depends on the dimensionless fetch. The agreement between these models and the database is reasonable.

Wind Wave Characteristics and Engineering Environment of the South China Sea

Wave simulation was conducted for the period 1976 to 2005 in the South China Sea （SCS） using the wave model, WAVEWATCH-III. Wave characteristics and engineering environment were studied in the region. The wind input data are from the objective reanalysis wind datasets, which assimilate meteorological data from several sources. Comparisons of significant wave heights between simulation and TOPEX/Poseidon altimeter and buoy data show a good agreement in general. By statistical analysis, the wave characteristics, such as significant wave heights, dominant wave directions, and their seasonal variations, were discussed. The largest significant wave heights are found in winter and the smallest in spring. The annual mean dominant wave direction is northeast （NE） along the southwest （SW）-NE axis, east northeast in the northwest （NW） part of SCS, and north northeast in the southeast （SE） part of SCS. The joint distributions of wave heights and wave periods （directions） were studied. The results show a single peak pattern for joint significant wave heights and periods, and a double peak pattern for joint significant wave heights and mean directions. Furthermore, the main wave extreme parameters and directional extreme values, particularly for the 100-year return period, were also investigated. The main extreme values of significant wave heights are larger in the northern part of SCS than in the south- ern part, with the maximum value occurring to the southeast of Hainan Island. The direction of large directional extreme Hs values is focus in E in the northem and middle sea areas of SCS, while the direction of those is focus in N in the southeast sea areas of SCS.

The improved model of estimating global whitecap coverage based on satellite data

The pro and con of whitecap parameterizations and a statistical wave breaking model are discussed. An improved model is derived by combining satellite-based parameterization and the wave breaking model. The appropriate constants for the general wave state are obtained by considering the breaking condition of the wave slope and fitting with the satellite-based parameterization. The result is close to the constants based on the whitecap data from Monahan. Comparing with satellite-based data and the original model＇s results, the improved model＇s results are consistent with satellite-based data and previous studies. The global seasonal distributions of the whitecap coverage averaged from 1998 to 2008 are presented. Spatial and seasonal features of the whitecap coverage are analyzed.

Study on the double transmission of ultrasonic waves through statistic rough surfaces

A model evaluating the signal loss of the double transmitted acoustic beams through random rough surfaces was established based on the Fresnel approximation and phase- screen approximation. A simple analytical solution was achieved using the exponential substi- tution approach to remove the nonlinear integral terms. The factors that affect the signal of double transmissions from random rough surfaces were analyzed. The research results demon- strated that the signal loss is not only related to the root-mean-squire height of the roughness, but also to the distance of wave traveling in the materials. The model can be very helpful for improving the reliability of NDT (Non-Destructive Testing).

Asymptotic Calculation of Wave Period Statistics in Non-Gaussian Mixed Sea

This article concerns the calculation of the wave period probability densities in non-Gaussiau mixed sea states. The calculations are carried out by incorporating a second order nonlinear wave model into an asymptotic analysis method which is a novel approach to the calculation of wave period probability densities. Since all of the calculations are performed in the probability domain, the approach avoids long time-domain sinmlations. The accuracy and efficiency of the asymptotic analysis method for calculating the wave period probability densities are validated by comparing the results predicted using the method with those predicted by using the Monte-Carlo simulation （MCS） method.