scholarly journals Reflection and transmission of ocean wave spectra by a band of randomly distributed ice floes

2015 ◽  
Vol 56 (69) ◽  
pp. 315-322 ◽  
Author(s):  
Fabien Montiel ◽  
Vernon A. Squire ◽  
Luke G. Bennetts
Keyword(s):  
Wave Spectrum ◽  
Ocean Wave ◽  
Wave Spectra ◽  
Ensemble Averaging ◽  
Ice Dynamics ◽  
Reflection And Transmission ◽  
Directional Wave ◽  
Ice Edge ◽  
Ice Floes ◽  
Edge Band

AbstractA new ocean wave/sea-ice interaction model is proposed that simulates how a directional wave spectrum evolves as it travels through an arbitrary finite array of circular ice floes, where wave/ ice dynamics are entirely governed by wave-scattering effects. The model is applied to characterize the wave reflection and transmission properties of a strip of ice floes, such as an ice edge band. A method is devised to extract the reflected and transmitted directional wave spectra produced by the array. The method builds upon an integral mapping from polar to Cartesian coordinates of the scattered wave components. Sensitivity tests are conducted for a row of floes randomly perturbed from a regular arrangement. Results for random arrays are generated using ensemble averaging. A realistic ice edge band is then reconstructed from field experiment data. Simulations show good qualitative agreement with the data in terms of transmitted wave energy and directional spreading. In particular, it is observed that short waves become isotropic quickly after penetrating the ice field.

scholarly journals VERIFICATION OF A MODIFIED BAYESIAN METHOD FOR ESTIMATING DIRECTIONAL WAVE SPECTRA FROM HF RADAR

2011 ◽  
Vol 1 (32) ◽  
pp. 65 ◽  
Author(s):  
Lukijanto Lukijanto ◽  
Noriaki Hashimoto ◽  
Masaru Yamashiro
Keyword(s):  
Field Data ◽  
Bayesian Method ◽  
Wave Spectrum ◽  
Coastal Engineering ◽  
Hf Radar ◽  
Ocean Wave ◽  
Wave Spectra ◽  
Directional Spectrum ◽  
Radio Science ◽  
Directional Wave

A Modified Bayesian Method (MBM) for estimating directional wave spectra from Doppler spectra obtained by HF radar is examined using field data which were employed in the verification of Bayesian Method (BM). Applicability, validity and accuracy of the MBM are demonstrated compared with the directional wave spectra estimated by BM and observed by buoy acquired from the reliable field data obtained from Surface Current and Wave Variability Experiments (SCAWVEX) project. The necessary conditions of the Doppler spectral components to be used to estimate a reliable directional spectrum are correspondingly estimated by BM. The results clearly demonstrate that directional wave spectra can be estimated by MBM on the basis of Doppler spectra. In addition, though BM shows very time consuming in computations, BM is more robust against the presence of noise than MBM. References Akaike, H. (1980). Likelihood and Bayesian procedure, Bayesian statistics. In J.M. Bernardo, M.H. De Groot, D.U. Lindley, and A.F.M. Smith (Eds.), 143-166. Valencia: University Press. PMid:6252024 Barrick, D. E. (1972a). First order theory and analysis of MF/HF/VHF scatter from sea. IEEE Trans., Antennas Propagation, 20, 2-10. http://dx.doi.org/10.1109/TAP.1972.1140123 Barrick, D. E. (1977). Extraction of wave parameters from measured HF radar sea-echo Doppler spectra. Radio Science, 12(3), 415–424. http://dx.doi.org/10.1029/RS012i003p00415 Crombie, D. (1955). Doppler spectrum of sea echo at 13.56Mc/s. Nature, 175, 681-682. http://dx.doi.org/10.1038/175681a0 Hashimoto, N. and Kobune, K. (1986). Estimation of directional spectra from the maximum entropy principle. Proceedings of 5th International Offshore Mechanics and Arctic Engineering Symposium, 1, 80-85. Hashimoto, N., Kobune, K., and Kameyama, Y. (1987). Estimation of directional spectrum using the Bayesian approach, and its application to field data analysis. Report of P.H.R.I., 26(5), 57-100. Hashimoto N., and Tokuda M., (1999): A Bayesian Method Approach for Estimation of Directional Wave Spectra with HF radar, Coastal Engineering Journal, vol. 41, 137-147. http://dx.doi.org/10.1142/S0578563499000097 Hashimoto, N., Wyatt, L and Kojima, S. (2003): Verification of Bayesian Method for Estimating Directional Spectra from HF Radar Surface. Coastal Engineering Journal, 45(2), 255-274. http://dx.doi.org/10.1142/S0578563403000725 Hashimoto, N., Lukijanto, and Yamashiro, M. (2008). Development of a practical method for estimating directional spectrum from HF radar backscatter. Annual Journal of Coastal Engineering (in Japanese), 55(1), 1451-1455. http://dx.doi.org/10.2208/proce1989.55.1451 Hisaki, Y. (1996). Nonlinear inversion of the integral equation to estimate ocean wave spectra from HF radar. Radio science, 31(1), 25-39. http://dx.doi.org/10.1029/95RS02439 Howell, R., and Walsh, J. (1993). Measurement of ocean wave spectra using a ship mounted HF radar. IEEE Journal of Oceanic Engineering, 18(3), 306-310. http://dx.doi.org/10.1109/JOE.1993.236369 Lipa, B. J. and Barrick, D.E. (1982) : Analysis Methods for Narrow-Beam High-Frequency Radar Sea Echo, NOAA Technical Report ERL 420-WPL 56, 1-55. Lukijanto, Hashimoto, N., and Yamashiro, M. (2009a). Further modification practical method for estimating directional wave spectrum by HF radar. Proc. of 19 th ISOPE, 898-905. Lukijanto, Hashimoto, N., and Yamashiro, M. (2009b). An improvement of Modified Bayesian Method for estimating directional wave spectra from HF radar backscatter. Proceedings of 5 th APAC (Asian and Pacific Coasts), 105-111. Lukijanto, Hashimoto, N., and Yamashiro, M. (2009c). A comparison of analysis methods for estimating directional wave spectrum from HF ocean radar. Journal of Memoirs of the Faculty of Engineering, 69(4). Kyushu University, 163-185. Wyatt, L.R. (1990). A relaxation method for integral inversion applied to HF radar measurement of the ocean wave directional spectrum. International Journal Remote Sensing, 11(8), 1481-1494. http://dx.doi.org/10.1080/01431169008955106 Wyatt, L. R. Gurgel, K.W., Peters, H.C., Prandle, D., Krogstad, H.E., Haug, O., Gerritsen, H., Wensink, G.J. (1997b). The SCAWVEX Project. Proceedings of WAVES97, ASCE.

scholarly journals OBSERVATION OF DIRECTIONAL WAVE SPECTRA AND REFLECTION COEFFICIENT OF BREAKWATER IN A HARBOR

1988 ◽  
Vol 1 (21) ◽  
pp. 3
Author(s):  
Tetsunori Ohshimo ◽  
Kosuke Kondo ◽  
Tsunehiro Sekimoto
Keyword(s):  
Reflection Coefficient ◽  
Wave Diffraction ◽  
Maximum Likelihood Method ◽  
Wave Spectrum ◽  
Field Investigation ◽  
Likelihood Method ◽  
Electromagnetic Current ◽  
Wave Spectra ◽  
Field Investigations ◽  
Directional Wave

Field investigations were performed in order to show the effect of wave diffraction by breakwaters through directional wave spectra measurements in a harbor, and to estimate the reflection coefficient by resolving the incident and reflected wave energy in front of a composite type breakwater. Combinations of an ultrasonic wave gage (USW) and an electromagnetic current meter (EMC) were used to measure the synchronized data of the water surface elevation and two horizontal velocities. The EMLM (Extended Maximum Likelihood Method) was applied for the calculation of the directional wave spectrum, and the modified EMLM for an incident and reflection wave field was applied for the estimation of the reflection coefficient. Through the estimated directional wave spectra, the effect of wave diffraction by breakwaters were discussed and the reflection coefficient was estimated at about 0.9. As a result, the applicability of the field investigation method and the modified EMLM were verified.

On the Estimation of Directional Wave Spectrum Based on Stationary Vessels 1st Order Motions: A New Set of Experimental Results

2008 ◽  
Author(s):  
Joa˜o V. Sparano ◽  
Eduardo A. Tannuri ◽  
Alexandre N. Simos ◽  
Vini´cius L. F. Matos
Keyword(s):  
Bayesian Inference ◽  
Wave Spectrum ◽  
Small Scale ◽  
Large Set ◽  
Wave Spectra ◽  
Inference Method ◽  
Peak Period ◽  
Wave Basin ◽  
Bayesian Inference Method ◽  
Directional Wave

The practicability of estimating directional wave spectra based on a vessel 1st order response has been recently addressed by several researchers. The interest is justified since on-board estimations would only require only a simple set of accelerometers and rate-gyros connected to an ordinary PC. The on-board wave inference based on 1st order motions is therefore an uncomplicated and inexpensive choice for wave estimation if compared to wave buoys and radar systems. The latest works in the field indicate that it is indeed possible to obtain accurate estimations and a Bayesian inference model seems to be the preferable method adopted for performing this task. Nevertheless, most of the previous analysis has been based exclusively on numerical simulations. At Polytechnic School, an extensive research program supported by Petrobras has been conducted since 2000, aiming to evaluate the possibility of estimating wave spectrum on-board offshore systems, like FPSO platforms. In this context, a series of small-scale tests has been performed at the LabOceano wave basin, comprising long and short crested seas. A possible candidate for on-board wave estimation has been recently studied: a crane barge (BGL) used for launching ducts offshore Brazil. The 1:48 model has been subjected to bow and quartering seas with different wave heights and periods and also different levels of directional spreading. A Bayesian inference method was adopted for evaluating the wave spectra based on the time-series of motions and the results were directly compared to the wave spectra measured in the basin by means of an array of wave probes. Very good estimations of the statistical parameters (significant wave height, peak period and mean wave direction) were obtained and, in most cases, even the directional spreading could be properly predicted. Inversion of the mean direction (180° shift), mentioned by some authors as a possible drawback of the Bayesian inference method, was not observed in any case. Sensitivity analysis on errors in the input parameters, such as the vessel inertial characteristics, has also been performed and attested that the method is robust enough to cope well with practical uncertainties. Overall results once again indicate a good performance of the inference method, providing an important additional validation supported by a large set of model tests.

scholarly journals CONFIDENCE INTERVALS FOR OCEAN WAVE SPECTRA

1972 ◽  
Vol 1 (13) ◽  
pp. 10
Author(s):  
Leon E. Borgman
Keyword(s):  
Confidence Intervals ◽  
Wave Spectrum ◽  
Structural Response ◽  
Ocean Wave ◽  
Wave Spectra ◽  
Wave Direction ◽  
Chi Square ◽  
Simulation Procedure ◽  
Spectral Estimates ◽  
Chi Squared

The random nature of ocean wave records introduces statistical variability into the wave spectrum estimates based on these records. This may cause inaccuracy in subsequent calculations such as the prediction of the primary wave direction or the estimation of structural response. Confidence intervals on such estimates are needed to evaluate whether adequate estimate accuracy has been obtained. The chi-squared confidence interval commonly used for wave spectra is based on the assumption of a Gaussian sea surface. Its applicability for hurrican size waves has been open for question. Therefore, after a brief outline of the relevant statistical relations basic to the chi-squared procedure, wave data from Hurrican Carla is empirically analyzed and compared with the theoretical conclusions. A simulation procedure is used to proceed from the data to probability interval statements. A comparison of these with the correponding chi-squared statements shows the chi-squared relations to be fairly reasonable approximations for spectral estimates averaged over bands of at least eight values. The empirical simulation procedure can be extended to subsequent calculations based on the spectral estimates while the chi-square method encounters difficulty for such problems.

Ocean Wave Measurements From ENVISAT ASAR Data Using a Parametric Inversion Scheme

2004 ◽  
Author(s):  
J. Schulz-Stellenfleth ◽  
S. Lehner ◽  
D. Hoja ◽  
J. C. Nieto-Borge
Keyword(s):  
A Priori ◽  
Wave Spectrum ◽  
Global Scale ◽  
Wave Mode ◽  
Ocean Wave ◽  
Wave System ◽  
Wave Spectra ◽  
Data Set ◽  
Envisat Asar ◽  
Sar Imaging

A parametric algorithm is presented to estimate two-dimensional ocean wave spectra from ENVISAT ASAR wave mode data on a global scale. The retrieval scheme makes use of prior information taken from numerical wave models. The Partition Rescale and Shift algorithm (PARSA) is based on a partitioning technique, which splits an a priori wave spectrum into its wave system components. Integral parameters of these systems, such as mean direction, mean wavelength, waveheight, and directional spreading are then adjusted iteratively to improve the consistency with the SAR observation. The method takes into account the full nonlinear SAR imaging process and uses a maximum a posteriori approach, which is based on statistical model quantifying the errors of the SAR imaging model, the SAR measurement, and the prior wave spectra. The method is applied to a global data set of ENVISAT ASAR data acquired during the CAL/VAL phase. The benefit of cross spectra compared to conventional symmetric image spectra is demonstrated.

scholarly journals COMBINED REFRACTION-DIFFRACTION CALCULATIONS WITH DIRECTIONAL WAVE SPECTRA

1984 ◽  
Vol 1 (19) ◽  
pp. 71 ◽  
Author(s):  
P. Gaillard
Keyword(s):  
Water Depth ◽  
Arbitrary Shape ◽  
Wave Spectrum ◽  
Wave Spectra ◽  
Combined Effects ◽  
Random Waves ◽  
Method Of Calculation ◽  
Wave Refraction ◽  
Directional Wave

A method of calculation of the combined effects of wave refraction, diffraction and reflection in harbours of arbitrary shape and non uniform water depth, subject to periodic or random waves is presented. Examples of application are given and practical aspects on the wave spectrum discretisation are considered.

scholarly journals Research on the Algorithm Model for Measuring Ocean Waves Based on Satellite GPS Signals in China

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 541 ◽  
Author(s):  
Zhanhui Qi ◽  
Shaowu Li ◽  
Mingbing Li ◽  
Chaoqun Dang ◽  
Dongbo Sun ◽  
...  
Keyword(s):  
Wave Spectrum ◽  
Ocean Wave ◽  
Acquisition Time ◽  
Measurement Technology ◽  
Movement Velocity ◽  
Wave Parameters ◽  
Wave Measurement ◽  
Improvement Measures ◽  
Directional Wave ◽  
Gravity Acceleration

In recent years, the GPS wave buoy has been developed for in situ wave monitoring based on satellite GPS signals. Many research works have been completed on the GPS-based wave measurement technology and great progress has been achieved. The basic principle of the GPS wave buoy is to calculate the movement velocity of the buoy using the Doppler frequency shift of satellite GPS signals, and then to calculate the wave parameters from the movement velocity according to ocean wave theory. The shortage of the GPS wave buoy is the occasional occurrence of some unusual values in the movement velocity. This is mainly due to the fact that the GPS antenna is occasionally covered by sea water and cannot normally receive high-quality satellite GPS signals. The traditional solution is to remove these unusual movement velocity values from the records, which requires furthering extend the acquisition time of satellite GPS signals to ensure there is a large enough quantity of effective movement velocity values. Based on the traditional GPS wave measurement technology, this paper presents the algorithmic flow and proposes two improvement measures. On the one hand, the neural network algorithm is used to correct the unusual movement velocity data so that extending the acquisition time of satellite GPS signals is not necessary and battery power is saved. On the other hand, the Gaussian low-pass filter is used to correct the raw directional wave spectrum, which can further eliminate the influence of noise spectrum energy and improve the measurement accuracy. The on-site sea test of the SBF7-1A GPS wave buoy, developed by the National Ocean Technology Center in China, and the gravity-acceleration-type DWR-MKIII Waverider buoy are highlighted in this article. The wave data acquired by the two buoys are analyzed and processed. It can be seen from the processed results that the ocean wave parameters from the two kinds of wave buoys, such as wave height, wave period, wave direction, wave frequency spectrum, and directional wave spectrum, are in good consistency, indicating that the SBF7-1A GPS wave buoy is comparable to the traditional gravity-acceleration-type wave buoy in terms of its accuracy. Therefore, the feasibility and validity of the two improvement measures proposed in this paper are confirmed.

Estimation of Wind-Sea and Swell Components in a Bimodal Sea State

2004 ◽  
Vol 128 (4) ◽  
pp. 265-270 ◽  
Author(s):  
K. C. Ewans ◽  
E. M. Bitner-Gregersen ◽  
C. Guedes Soares
Keyword(s):  
Wave Spectrum ◽  
Low Frequency ◽  
Wave Spectra ◽  
Spectral Parameters ◽  
High Frequency Peak ◽  
Wave Measurements ◽  
Frequency Peak ◽  
Directional Wave ◽  
Wind Sea ◽  
Complete Frequency

Methods for separating the spectral components and describing bimodal wave spectra are evaluated with reference to wave spectra from directional wave measurements made at the Maui location off the west coast of New Zealand. Two methods involve partitioning bimodal wave spectra into wind-sea and swell components and then fitting a spectral function to each component, while the third assigns an average spectral shape based on the integrated spectral parameters. The partitioning methods involve separating the wave spectrum into two frequency bands: a low-frequency peak, the swell component, and a high-frequency peak, the wind-sea. One partitioning method uses only the frequency spectrum while the other analyzes the complete frequency-direction spectrum. Comparison of the spectral descriptions and derived parameters against the measured counterparts provides insight into the accuracy of the different approaches to describing actual bimodal sea states.

Extended Bayesian Estimation of Directional Wave Spectra

2004 ◽  
Author(s):  
Toshio Iseki
Keyword(s):  
Bayesian Estimation ◽  
Wave Spectrum ◽  
Time History ◽  
Ship Motions ◽  
Wave Spectra ◽  
Time Varying ◽  
Bayesian Modelling ◽  
History Data ◽  
Modelling Procedure ◽  
Directional Wave

The Bayesian modelling procedure has been extended to estimate time-varying directional wave spectra. In the proposed method, the hull of a ship is regarded as a wave sensor and the time history data of ship motions is analyzed to evaluate cross spectra. In this concept, a special attention should be paid to changes of the directional wave spectrum because the ship is moving and the location at sea is changing continuously. Therefore, the extended Bayesian estimation is based on the cross spectra evaluated at different times and the fluctuation of wave spectrum is taken into account. In order to examine the reliability of the proposed method, data of onboard experiments were analyzed. Comparisons between the results of the proposed method and visual observations show good agreements.

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