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

Author(s):  
Danièle Hauser ◽  
Eva Le Merle ◽  
Lotfi Aouf ◽  
Charles Peureux

<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>

Author(s):  
Danie`le Hauser ◽  
Ce´line Tison ◽  
Jean-Michel Lefe`vre ◽  
Juliette Lambin ◽  
Amiot Thierry ◽  
...  

The Chinese and French Space Agencies are jointly preparing a satellite mission devoted to the monitoring of the ocean surface and related science and applications. This is the so-called “China France Oceanography SATellite” (CFOSAT), to be launched around 2013. This mission will provide simultaneous and collocated observations of wind at the ocean surface and spectral properties of surface ocean waves using two scatterometers, both in Ku-Band: SWIM for measurements of directional wave spectra and SCAT for wind vector measurements. The SWIM instrument will use a real aperture observation technique so as to avoid limitations encountered with SAR systems. This paper describes the main objectives and characteristics of the mission with a focus on the SWIM instrument designed and developed under French responsibility to measure directional spectra of ocean waves.


2021 ◽  
Vol 13 (2) ◽  
pp. 195
Author(s):  
He Wang ◽  
Jingsong Yang ◽  
Jianhua Zhu ◽  
Lin Ren ◽  
Yahao Liu ◽  
...  

Sea state estimation from wide-swath and frequent-revisit scatterometers, which are providing ocean winds in the routine, is an attractive challenge. In this study, state-of-the-art deep learning technology is successfully adopted to develop an algorithm for deriving significant wave height from Advanced Scatterometer (ASCAT) aboard MetOp-A. By collocating three years (2016–2018) of ASCAT measurements and WaveWatch III sea state hindcasts at a global scale, huge amount data points (>8 million) were employed to train the multi-hidden-layer deep learning model, which has been established to map the inputs of thirteen sea state related ASCAT observables into the wave heights. The ASCAT significant wave height estimates were validated against hindcast dataset independent on training, showing good consistency in terms of root mean square error of 0.5 m under moderate sea condition (1.0–5.0 m). Additionally, reasonable agreement is also found between ASCAT derived wave heights and buoy observations from National Data Buoy Center for the proposed algorithm. Results are further discussed with respect to sea state maturity, radar incidence angle along with the limitations of the model. Our work demonstrates the capability of scatterometers for monitoring sea state, thus would advance the use of scatterometers, which were originally designed for winds, in studies of ocean waves.


2020 ◽  
Author(s):  
Alvise Benetazzo ◽  
Francesco Barbariol ◽  
Paolo Pezzutto ◽  
Luciana Bertotti ◽  
Luigi Cavaleri ◽  
...  

<p>Reliable prediction of oceanic waves during severe marine storms has always been foremost for offshore platform design, coastal activities, and navigation safety. Indeed, many damaging accidents and casualties during storms were ascribed to the impact with abnormal and unexpected waves. However, predicting extreme wave occurrence is a challenging task, at first, because of their inherent randomness, and because the observation of large ocean waves, of primary importance to assess theoretical and numerical models, is limited by the costs and risks of deployment during severe open-ocean sea-state conditions.</p><p>In the context of the EU-based Copernicus Marine Environment Monitoring Service (CMEMS) evolution, the LATEMAR project (https://www.mercator-ocean.fr/en/portfolio/latemar/) aimed at improving the modelling of large wave events during marine storms. Indeed, at present, operational systems only provide average and peak wave parameters, with no information on individual waves whatsoever. However, developments of the state-of-the-art third-generation wave models demonstrated that using the directional wave spectrum moments into theoretical statistical models for wave extremes, forecasters are able to accurately infer the expected shape and likelihood of the maximum waves during storms.</p><p>The main purpose of the activity is therefore to provide the wave models WAM and WAVEWATCH III with common procedures to explicitly estimate the maximum wave heights for each sea state. LATEMAR achieved this goal by: performing an extensive assessment of the model maximum waves using field observations collected from an oceanographic tower; comparing WAM and WAVEWATCH III maximum wave estimates in the Mediterranean Sea; investigating the sensitivity of the maximum waves on the main sea state parameters. All model developments and evaluations resulting from this research project will be directly applicable to the wave model forecasting systems to expand their catalogue.</p>


Author(s):  
J. Schulz-Stellenfleth ◽  
S. Lehner ◽  
D. Hoja ◽  
J. C. Nieto-Borge

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.


2014 ◽  
Vol 31 (11) ◽  
pp. 2556-2564 ◽  
Author(s):  
James Foster ◽  
Ning Li ◽  
Kwok Fai Cheung

AbstractOcean waves have a profound impact on navigation, offshore operations, recreation, safety, and the economic vitality of a nation’s maritime and coastal communities. This study demonstrates that ships equipped with geodetic GPS and a radar gauge can provide accurate estimates of sea state. The Research Vessel (R/V) Kilo Moana recorded 1-Hz data for the entire period of a 10-day cruise around the Hawaiian Islands. Solving for precise kinematic positions for the ship and combining these solutions with the ranges from the ship to the sea surface provided by the radar gauge, it was possible to retrieve 1-Hz estimates of the sea surface elevation along the cruise track. Converting these into estimates of significant wave height, strong agreement was found with wave buoy measurements and hindcast wave data. Comparison with buoy data indicates the estimates have errors on the order of 0.22 m, or less than 11% of the wave height. Using wave model predictions of the dominant directions, the data were processed further to correct for the Doppler shift and to estimate the dominant wave period. Although relatively noisy in locations where the predicted wave directions are expected to be poor, in general these estimates also show a good agreement with the wave buoy observations and hindcast wave estimates. A segment of the cruise that formed a circuit allowed for testing the consistency of the ship-based estimates and for determining a dominant wave direction, which was found to agree closely with model predictions.


2011 ◽  
Vol 480-481 ◽  
pp. 1452-1456
Author(s):  
Li Bo ◽  
Zhong Yi Li ◽  
Yue Jin Zhang

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.


2021 ◽  
Vol 12 (1) ◽  
pp. 51
Author(s):  
Safdar Rasool ◽  
Kashem M. Muttaqi ◽  
Danny Sutanto

Ocean wave energy is an abundant and clean source of energy; however, its potential is largely untapped. Although the concept of energy harvesting from ocean waves is antiquated, the advances in wave energy conversion technologies are embryonic. In many major studies related to wave-to-wire technologies, ocean waves are considered to be regular waves with a fixed amplitude and frequency. However, the actual ocean waves are the sum of multiple frequencies that exhibit a particular sea state with a significant wave height and peak period. Therefore, in this paper, detailed modelling of the ocean waves is presented and different wave spectra are analyzed. The wave spectra will eventually be used for the generation of wave elevation time series. Those time series can be used for the wave-to-wire model-based studies for improved investigations into wave energy conversion mechanisms, mimicking the real ocean conditions.


Author(s):  
E. Le Merle ◽  
D. Hauser ◽  
C. Peureux ◽  
L. Aouf ◽  
P. Schippers ◽  
...  

Eos ◽  
2016 ◽  
Author(s):  
Sarah Stanley

The seasonality of fine-scale, near-surface ocean dynamics raises important considerations for an upcoming satellite mission to measure global sea surface height.


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