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.

Evaluation on the Capability of Revealing Ocean Swells from Sentinel-1A Wave Spectra Measurements

2020 ◽  
Vol 37 (7) ◽  
pp. 1289-1304
Author(s):  
Xuan Wang ◽  
Romain Husson ◽  
Haoyu Jiang ◽  
Ge Chen ◽  
Guoping Gao
Keyword(s):  
Wave Energy ◽  
Wave Spectrum ◽  
Wave Mode ◽  
Wave Frequency ◽  
Wave Parameter ◽  
Wave System ◽  
Wave Spectra ◽  
Wave Measurements ◽  
The Difference ◽  
Level 2

AbstractWave measurements retrieved by Sentinel-1A level-2 ocean (OCN) products are sensitive to swells other than wind seas, and are considered to provide a finer resolution of ocean swells. To assess the capability of swell retrieval globally, OCN products are validated against WAVEWATCH III (WW3) wave spectra for two available incidence angles [“wave mode” (WV); WV1: 23°; WV2: 36°], focused on the integral wave parameters and most energetic wave system of Sentinel-1A. The wave parameter difference between Sentinel-1A and WW3 along antenna look angles for WV1 demonstrates the obvious impact of the nonlinearity influence in the azimuth direction, resulting in an unrealistically high wave height at the low wave frequency, and the spurious split of wave systems in the range direction, due to the vanishing of velocity bunching modulation. WV2 is less pronounced in these two aspects, but tends to shift wave energy to a higher wave frequency in the range direction. The inside discrepancy of wave energy has two noticeable features: the difference in peak wavelengths in the wave spectrum is positively clustered in the azimuth direction and negatively clustered in the range direction; some of the most energetic partitions derived from Sentinel-1A are difficult to assign to any wave systems in WW3. This phenomenon could be related to wind-wave coupling as the azimuth cutoff/WW3 peak wavelength is confined to a ratio below 0.5 for the negative difference between Sentinel-1A and WW3 peak wavelengths and the spectral distance of most energetic wave system in Sentinel-1A highly resembles “swell pools.”

scholarly journals Ocean Wave Integral Parameter Measurements Using Envisat ASAR Wave Mode Data

2011 ◽  
Vol 49 (1) ◽  
pp. 155-174 ◽  
Author(s):  
Xiao-Ming Li ◽  
Susanne Lehner ◽  
Thomas Bruns
Keyword(s):  
Wave Mode ◽  
Ocean Wave ◽  
Integral Parameter ◽  
Envisat Asar

Sea State Statistics and Extreme Waves Observed by Satellite

2008 ◽  
Author(s):  
S. Lehner ◽  
J. Schulz-Stellenfleth ◽  
Thomas Ko¨nig ◽  
X. Li
Keyword(s):  
Extreme Events ◽  
Wave Spectrum ◽  
Ocean Waves ◽  
Wave Mode ◽  
Extreme Value Statistics ◽  
Altimeter Data ◽  
Sea State ◽  
Data Set ◽  
Wave Properties ◽  
D Wave

For the design of ships as well as for the investigation of ship accidents it is important to have knowledge about both the two dimensional spectral wave properties as well as extreme value statistics of ocean waves. Although numerical wave models have reached a high level of accuracy, they still have weaknesses with respect to the details of the 2-D wave spectrum. Furthermore standard models like WAM provide estimates of the 2-D wave spectrum, i.e., second order sea state statistics and therefore lack information on individual wave properties and the occurrence of extreme events. In this study the potential of global Synthetic Aperture Radar (SAR) wave mode data acquired by the European satellites ERS-2 and ENVISAT to investigate ship accidents is discussed and compared to altimeter data and ECMWF model results. These data are acquired independent of light and weather conditions on a global scale. A historic data set of ERS-2 wave mode data acquired between 1998 and 2000 is co-located with accidents which occurred during that time. ENVISAT ASAR wave mode data acquired since 2002 are considered, too. Different ocean wave parameters like significant wave height and wave periods are derived from the SAR data. The potential role of the respective wave conditions for some recent accident is discussed in detail. This includes in particular the analysis of cross sea conditions, groupiness and extreme events.

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.

scholarly journals A fully coupled Atmosphere–Ocean Wave modeling system (WEW) for the Mediterranean Sea: interactions and sensitivity to the resolved scales and mechanisms

2015 ◽  
Vol 8 (5) ◽  
pp. 4075-4112
Author(s):  
P. Katsafados ◽  
A. Papadopoulos ◽  
G. Korres ◽  
G. Varlas
Keyword(s):  
Data Exchange ◽  
Wind Wave ◽  
Aerodynamic Drag ◽  
Wave Spectrum ◽  
Ocean Wave ◽  
Wave System ◽  
Sea State ◽  
Scientific Performance ◽  
Research Activities ◽  
Fully Coupled

Abstract. It is commonly accepted that there is an urgent need for a better understanding of the factors that contribute to the air–sea interaction processes and their feedbacks. In this sense it is absolutely important to develop advanced numerical prediction systems that treat the atmosphere and the ocean as a unified system. The realistic description and understanding of the exchange processes near the ocean surface, requires the exact knowledge of the sea state and its evolution. This can be achieved by considering the sea surface and the atmosphere as a continuously cross talking dynamic system. Therefore, this study aims to present the effort towards developing a new, high-resolution, two-way fully coupled atmosphere–ocean wave model in order to support operational and research activities. A specific issue that it is emphasized here is the determination and parameterization of the air–sea momentum fluxes under conditions of extremely high and time-varying winds. Software considerations, data exchange as well as computational and scientific performance of the coupled system, so-called WEW, are also discussed throughout this study. In a case study of high-impact weather and sea state event, the wind–wave parameterization scheme reduces the resulted wind speed and the significant wave height as a response to the increased aerodynamic drag over rough sea surfaces. Overall, WEW offers a more realistic representation of the momentum exchanges in the ocean wind–wave system and includes the effects of the resolved wave spectrum on the drag coefficient and its feedback on the momentum flux.

Spectral Analysis of Ship-Generated Waves in Finite-Depth Water

2002 ◽  
Author(s):  
Carl A. Scragg
Keyword(s):  
Deep Water ◽  
Wave Spectrum ◽  
Finite Depth ◽  
Far Field ◽  
Wave Spectra ◽  
Data Set ◽  
Free Wave ◽  
Common Reference ◽  
Depth Water ◽  
Wave Elevations

Recent efforts to compare the waves generated by different vessels traveling in finite-depth water have struggled with difficulties presented by various data sets of wave elevations (either measurements or predictions) corresponding to different lateral distances from the ship. Some of the attempts to shift the data to a common reference location have relied upon crude and potentially misleading approximations. The use of free-wave spectral-methods not only overcomes such difficulties, but it also provides us the means to accurately extend CFD results into the far field. As in the deep-water case, one can define a free-wave spectrum that is valid for all lateral positions and distances astern of the vessel. The free-wave spectrum contains a complete description of the Kelvin wake, and wave elevations at any far-field position can be readily calculated once the spectrum is known. For the case of infinitely deep water, Eggers, Sharma, and Ward [1967] presented a method by which free-wave spectra can be determined from appropriate measurements of the far-field wave elevations. The current paper discusses the use of free-wave spectra for finite-depth problems and presents a method for the determination of free-wave spectra based upon fitting predicted wave elevations to a corresponding data set. The predicted wave elevations can be calculated from an unknown distribution of finite-depth Havelock singularities. The unknown singularities are determined by minimizing the mean-square-difference between predicted and measured wave fields. The method appears to be quite general and can be used to calculate either finite or infinite-depth free-wave spectra from experimental data or from local CFD predictions.

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.

Spectral Representation of Ship-Generated Waves in Finite-Depth Water

2003 ◽  
Vol 125 (1) ◽  
pp. 65-71 ◽  
Author(s):  
Carl A. Scragg
Keyword(s):  
Deep Water ◽  
Wave Spectrum ◽  
Finite Depth ◽  
Far Field ◽  
Wave Spectra ◽  
Data Set ◽  
Free Wave ◽  
Common Reference ◽  
Depth Water ◽  
Wave Elevations

Recent efforts to compare the waves generated by different vessels traveling in finite-depth water have struggled with difficulties presented by various data sets of wave elevations (either measurements or predictions) corresponding to different lateral distances from the ship. Some of the attempts to shift the data to a common reference location have relied upon crude and potentially misleading approximations. The use of free-wave spectral-methods not only overcomes such difficulties, but is also provides us the means to accurately extend CFD results into the far field. As in the deep-water case, one can define a free-wave spectrum that is valid for all lateral positions and distances astern of the vessel. The free-wave spectrum contains a complete description of the Kelvin wake, and wave elevations at any far-field position can be readily calculated once the spectrum is known. For the case of infinitely deep water, Eggers, Sharma, and Ward [1] presented a method by which free-wave spectra can be determined from appropriate measurements of the far-field wave elevations. The current paper discusses the use of free-wave spectra for finite-depth problems and presents a method for the determination of free-wave spectra based upon fitting predicted wave elevations to a corresponding data set. The predicted wave elevations can be calculated from an unknown distribution of finite-depth Havelock singularities. The unknown singularities are determined by minimizing the mean-square-difference between predicted and measured wave fields. The method appears to be quite general and can be used to calculate either finite or infinite-depth free-wave spectra from experimental data or from local CFD predictions.

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.

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