scholarly journals Amplitude Malformation in the IFFT Ocean Wave Rendering under the Influence of the Fourier Coefficient

2014 ◽  
Vol 18 (2) ◽  
pp. 89
Author(s):  
Lining Chen ◽  
Yicheng Jin ◽  
Yong Yin
Keyword(s):  
Fourier Coefficient ◽  
Integral Domain ◽  
Wave Model ◽  
Ocean Waves ◽  
Ocean Wave ◽  
Wave Number ◽  
Not Given ◽  
Source Codes ◽  
Wave Potential ◽  
Wavenumber Spectrum

Although Tessendorf’s IFFT Gerstner wave model hasbeen widely used, the value of A, a constant of the Fouriercoefficient, is not given. A will strongly influence the shape of therendered ocean wave and even cause amplitude malformation.We study the algorithm of the IFFT Gerstner wave, and give themethod of A calculating. The method of the paper can guaranteethere is no amplitude malformation in rendered ocean waves. Theexpression of the IFFT Gerstner wave with the amplitude of thecosine wave is derived again. The definite integral of the wavenumber spectrum is discretized. Further, another expression ofthe IFFT Gerstner wave is gotten. The Fourier coefficient of theexpression contains the wave number spectrum and the area ofthe discrete integral domain. The method makes the shape of thegenerated wave stable. Comparing Tessdendorf’s method with themethod of the paper, we find that the expression of A shouldcontain the area of the discrete integral domain and the spectralconstant of the wave number spectrum. If A contains only thespectral constant, the amplitude malformation may occur. Byreading some well known open source codes, we find that the codeauthors adopted some factitious methods to suppress themalformed amplitude Obviously, the code authors have alreadynoticed the phenomenon of the malformation, but not probed thecause. The rendering results of the codes are close to that of themethod of the paper. Furthermore, the wave potential iscomputed using the Gerstner wave model directly, the author findit is quite close to that of the paper. The experimental results andcomparisons show that the method of the paper correctlycomputes the wave potential and effectively solves the problem ofamplitude malformation.

Ocean Surface Modeling in Vary Wind Field

2011 ◽  
Vol 480-481 ◽  
pp. 1452-1456
Author(s):  
Li Bo ◽  
Zhong Yi Li ◽  
Yue Jin Zhang
Keyword(s):  
Wind Field ◽  
Wave Spectrum ◽  
Wave Model ◽  
Ocean Surface ◽  
Ocean Waves ◽  
Surface Modeling ◽  
Ocean Wave ◽  
Statistical Characteristics ◽  
Linear Wave ◽  
Wave Models

In ocean surface modeling a popular method of wave modeling is making use of ocean wave spectrum, which is a physical wave model and based on linear wave theories. The ocean waves produced in this way can reflect the statistical characteristics of the real ocean well. However, few investigations of ocean simulation have been focused on turbulent fluid under vary wind field in this way, while all ocean wave models are built with the same wind parameters. In order to resolve the problem of traditional method, we proposed a new method of dividing the ocean surface into regular grids and generating wave models with different parameters of wind in different location of view scope. The method not only preserves the fidelity of statistical characteristics, but also can be accelerated with the processing of GPU and widely used in VR applications.

scholarly journals Investigation of the Anisotropic Patterns in the Altimeter Backscatter Measurements Over Ocean Wave Surfaces

2021 ◽  
Vol 9 ◽  
Author(s):  
Xi-Yu Xu ◽  
Ke Xu ◽  
Maofei Jiang ◽  
Bingxu Geng ◽  
Lingwei Shi
Keyword(s):  
Wave Model ◽  
Ocean Surface ◽  
Ocean Waves ◽  
Ocean Wave ◽  
Altimeter Data ◽  
Wave Surface ◽  
Wave Direction ◽  
Backscatter Coefficient ◽  
Wave Surfaces ◽  
Operational Modes

This article attempts to analyze the influence of the anisotropic effects of the ocean wave surface on SAR altimetry backscatter coefficient (Sigma-0) measurements, which has not been intensively addressed in publications. Data of Sentinel-3A, Cryosat-2, and Jason-3 altimeters allocated by the WW3 numeric wave model were analyzed, and the patterns of Sigma-0 with respect to the wave direction were acquired under ∼2 m significant wave height. The ocean waves were classified into six categories, among which the moderate swell and short win-wave cases were analyzed intensively. Swell-dominated ocean surface shows less randomness than the wind-wave-dominated ocean surface. Clear and significant sinusoid trends are found in the Sigma-0 and SSB patterns of both operational modes (SAR mode and PLRM mode) of the Sentinel-3A altimeter for the moderate swell case, indicating the sensitivity of Sigma-0 and SSB measurements to the anisotropic features of the altimeter measurements. The anisotropic pattern in the Sentinel-3A PLRM Sigma-0 is somewhat counterintuitive, but the analysis of Jason-3 altimeter data would show similar results. Additionally, by comparing the anisotropic patterns of two orthogonally polarized SAR altimeters (Sentinel-3A and Cryosat-2), we could draw the conclusion that the Sigma-0 measurements are not sensitive to the polarization mode. As for the SSHA patterns, no clear sinusoid could be identified for the moderate swell. A possible explanation is that the SSB pattern may be overwhelmed in the complicated factors that can influence the SSHA pattern.

Seasonal fluctuations in the secondary microseism wavefield recorded offshore Ireland

2020 ◽  
Author(s):  
Florian Le Pape ◽  
Christopher J. Bean
Keyword(s):  
Wave Model ◽  
Ocean Waves ◽  
Ocean Wave ◽  
Ocean Bottom ◽  
Ocean Bottom Seismometer ◽  
Storm Activity ◽  
Directional Spectrum ◽  
Sea Bottom ◽  
Ocean Wave Model ◽  
Obs Data

<p><span>Generated in the ocean, secondary microseisms result from the interaction of opposing ocean wave fronts and represent the strongest ambient seismic noise level measured on land. The recorded noise energy will vary with seasons due to changes in storm activity and associated secondary microseism source locations. Here, ocean bottom seismometer (OBS) data collected offshore Ireland in 2016 have been processed to look into the seasonal variations of the ambient noise wavefield recorded at the seafloor. Daily cross-correlations of OBS pairs located on top of thick sediments in deep water highlight seasonal changes between Rayleigh waves fundamental mode and first overtone for winter and summer months. Comparisons with ocean wave directional spectrum data derived from ocean wave model hindcasts suggest those variations are correlated with changing patterns in ocean waves interactions and therefore microseism source locations. In order to understand those observations in detail, we use 3D numerical simulations to show how the water column but also the subsurface structure below the sea bottom will affect the recorded wavefield at the seafloor for different stations and sources locations. Compared to land stations, the secondary microseism wavefield observed in the ocean and in particular changes in the excitation of Rayleigh modes due to site effects can help characterize the microseism source locations that fluctuate through the seasons.</span></p>

Directional and frequency spread of surface ocean waves from CFOSAT/SWIM satelllite measurements

2021 ◽  
Author(s):  
Danièle Hauser ◽  
Eva Le Merle ◽  
Lotfi Aouf ◽  
Charles Peureux
Keyword(s):  
Wave Model ◽  
Ocean Waves ◽  
Global Scale ◽  
Ocean Wave ◽  
Wave Spectra ◽  
Physical Processes ◽  
Satellite Mission ◽  
Sea State ◽  
Surface Ocean ◽  
Frequency Spread

<p>The CFOSAT (China France Oceanography Satellite) mission launched in 2018 now routinely provides at the global scale, directional spectra of ocean waves. The principle is based on the analysis of the normalized radar cross-section measured by the instrument SWIM (Surface Waves Investigation and Monitoring), a near-nadir pointing Ku-Band real-aperture scanning radar. From the ocean wave spectra derived from SWIM, the principal parameters of ocean wave spectra as significant wave height, peak wavelength, and peak direction are now available to better characterize the sea-state. However, it is known that these principal parameters are not sufficient not fully characterize the distribution of wave energy and understand or validate the physical processes impacting its evolution during growth order decay. Here we show that the parameters characterizing the shape of the wave spectra (e.g directional and frequency spread) can be estimated at the global scale from the SWIM measurements. We also show that they can provide consistent values of the Benjamin-Feir index, an index proposed to estimate the probability of extreme waves. Similarities of differences with the shape parameters of the MFWAM numerical wave model are also discussed.</p>

scholarly journals Impact of wave physics on ocean–wave coupling in CMEMS-IBI Part B: Validation study

2019 ◽  
Author(s):  
Romain Rainaud ◽  
Lotfi Aouf ◽  
Alice Dalphinet ◽  
Marcos Garcia Sotillo ◽  
Enrique Alvarez-Fanjul ◽  
...  
Keyword(s):  
Positive Impact ◽  
Wave Model ◽  
Ocean Waves ◽  
Ocean Model ◽  
Ocean Wave ◽  
Wave Coupling ◽  
In Situ Observations ◽  
The Waves ◽  
Horizontal Grid

Abstract. This work aims to evaluate the ocean/waves coupling based on input from the wave modelMFWAM. 1-year coupled runs including seasonal variability has been performed for the IberianBiscay and Ireland domain. We investigated the consequences of improvement in wave physics onthe mixed layer of the ocean with a fine horizontal grid size of 1/36°. The ocean model NEMO andthe wave model MFWAM have been used for this study to prepare the use of coupling operationallyin the IBI Copernicus Marine Service and Monitoring Evironment (CMEMS). Two wave physicsversions have been discussed in this study. The validation of sea surface temperature, surfacecurrents have been implemented in comparison with satellite and in-situ observations. The resultsshow a positive impact of the waves forcing on surface key parameters. For storm cases it has beendemonstrated a good skill of the ocean/wave coupling to capture the peak of surge event such as theone observed for Petra storm.

scholarly journals Long and Short-Term Simulations of Seto Inland Sea by Coupled Ocean-Wave Model

2013 ◽  
Vol 69 (2) ◽  
pp. I_511-I_515
Author(s):  
Yusuke TANAKA ◽  
Nobuhito MORI ◽  
Junichi NINOMIYA ◽  
Koichi SUGIMATSU ◽  
Hiroshi YAGI ◽  
...  
Keyword(s):  
Wave Model ◽  
Ocean Wave ◽  
Seto Inland Sea ◽  
Short Term ◽  
Ocean Wave Model

New directional wave observations from CFOSAT : impact on ocean/wave coupling in the Southern Ocean

2021 ◽  
Author(s):  
Lotfi Aouf ◽  
Daniele Hauser ◽  
Stephane Law-Chune ◽  
Bertrand chapron ◽  
Alice Dalphinet ◽  
...  
Keyword(s):  
Southern Ocean ◽  
Surface Wind ◽  
Bias Reduction ◽  
Ocean Wave ◽  
Wave Number ◽  
Geophysical Research ◽  
Wave Coupling ◽  
Ocean Region ◽  
Directional Wave ◽  
The Impact

<p>The Southern ocean is a complex ocean region with uncertainties related to surface wind forcing and fluxes exchanges at the air/sea interface. The improvement of wind wave generation in this ocean region is crucial for climate studies. With CFOSAT satellite mission, the SWIM instrument provides directional wave spectra for wavelengths from 70 to 500 m, which shed light on the role of correcting the wave direction and peak wave number of dominant wave trains in the wind-waves growth phase. This consequently induced a better energy transfer between waves and a significant bias reduction of wave height in the Southern Ocean (Aouf et al. 2020). The objective of this work is to extend the analysis of the impact of the assimilation of wave number components from SWIM wave partitions on the ocean/wave coupling. To this end, coupled simulations of the wave model MFWAM and the ocean model NEMO are performed during the southern winter period of 2019 (May-July). We have examined the MFWAM/NEMO coupling with and without the assimilation of the SWIM mean wave number components. Several coupling processes related to Stokes drift, momentum flux stress and wave breaking inducing turbulence in the ocean mixing layer have been analyzed. We also compared the coupled runs with a control run without wave forcing in order to evaluate the impact of the assimilation. The results of coupled simulations have been validated with satellite Sea Surface Temperature and available surface currents data over the southern ocean. We also investigated the impact of the assimilation during severe storms with unlimited fetch conditions.</p><p>Further discussions and conclusions will be commented in the final paper.</p><p>Aouf L., New directional wave satellite observations : Towards improved wave forecasting and climate description in Southern Ocean, Geophysical Research Letters, DOI: 10.1029/2020GL091187 (in production).</p><p> </p><div> <div> <div></div> <div>What do you want to do ?</div> New mail</div> </div><div><img></div>

scholarly journals Evaluating skill of BMKG wave model forecast (Wavewatch-3) with observation data in Indian Ocean (5 – 31 December 2017).

2021 ◽  
Vol 893 (1) ◽  
pp. 012058
Author(s):  
R Kurniawan ◽  
H Harsa ◽  
A Ramdhani ◽  
W Fitria ◽  
D Rahmawati ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Wave Height ◽  
Model Performance ◽  
Forecast Accuracy ◽  
Wave Model ◽  
Ocean Waves ◽  
Observation Data ◽  
Operating Characteristics ◽  
Wave Forecast ◽  
Good For

Abstract Providing Maritime meteorological forecasts (including ocean wave information) is one of BMKG duties. Currently, BMKG employs Wavewatch-3 (WW3) model to forecast ocean waves in Indonesia. Evaluating the wave forecasts is very important to improve the forecasts skill. This paper presents the evaluation of 7-days ahead BMKG’s wave forecast. The evaluation was performed by comparing wave data observation and BMKG wave forecast. The observation data were obtained from RV Mirai 1708 cruise on December 5th to 31st 2017 at the Indian Ocean around 04°14'S and 101°31'E. Some statistical properties and Relative Operating Characteristics (ROC) curve were utilized to assess the model performance. The evaluation processes were carried out on model’s parameters: Significant Wave Height (Hs) and Wind surface for each 7-days forecast started from 00 UTC. The comparation results show that, in average, WW3 forecasts are over-estimate the wave height than that of the observation. The forecast skills determined from the correlation and ROC curves are good for the first- and second-day forecast, while the third until seventh day decrease to fair. This phenomenon is suspected to be caused by the wind data characteristics provided by the Global Forecasts System (GFS) as the input of the model. Nevertheless, although statistical correlation is good for up to 2 days forecast, the average value of Root Mean Square Error (RMSE), absolute bias, and relative error are high. In general, this verifies the overestimate results of the model output and should be taken into consideration to improve BMKG’s wave model performance and forecast accuracy.

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