Measuring Global Ocean Wave Skewness by Retracking RA-2 Envisat Waveforms

2007 ◽  
Vol 24 (6) ◽  
pp. 1102-1116 ◽  
Author(s):  
J. Gómez-Enri ◽  
C. P. Gommenginger ◽  
M. A. Srokosz ◽  
P. G. Challenor ◽  
J. Benveniste
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Likelihood Estimation ◽  
Ocean Waves ◽  
Ocean Wave ◽  
Global Ocean ◽  
Radar Altimeter ◽  
Significant Wave ◽  
Linear And Nonlinear ◽  
The Impact

For early satellite altimeters, the retrieval of geophysical information (e.g., range, significant wave height) from altimeter ocean waveforms was performed on board the satellite, but this was restricted by computational constraints that limited how much processing could be performed. Today, ground-based retracking of averaged waveforms transmitted to the earth is less restrictive, especially with respect to assumptions about the statistics of ocean waves. In this paper, a theoretical maximum likelihood estimation (MLE) ocean waveform retracker is applied tothe Envisat Radar Altimeter system (RA-2) 18-Hz averaged waveforms under both linear (Gaussian) and nonlinear ocean wave statistics assumptions, to determine whether ocean wave skewness can be sensibly retrieved from Envisat RA-2 waveforms. Results from the MLE retracker used in nonlinear mode provide the first estimates of global ocean wave skewness based on RA-2 Envisat averaged waveforms. These results show for the first time geographically coherent skewness fields and confirm the notion that large values of skewness occur primarily in regions of large significant wave height. Results from the MLE retracker run in linear and nonlinear modes are compared with each other and with the RA-2 Level 2 Sensor Geophysical Data Records (SGDR) products to evaluate the impact of retrieving skewness on other geophysical parameters. Good agreement is obtained between the linear and nonlinear MLE results for both significant wave height and epoch (range), except in areas of high-wave-height conditions.

Modelling Long-Term Trends in Significant Wave Height and its Potential Impacts on Ship Structural Loads

2013 ◽  
Author(s):  
Erik Vanem ◽  
Elzbieta M. Bitner-Gregersen
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Wave Climate ◽  
Ocean Wave ◽  
Future Trends ◽  
Significant Wave ◽  
Long Term Trends ◽  
Ocean Wave Climate ◽  
The Impact

This paper presents the results from a statistical model for significant wave height in space and time. In particular, various model alternatives were applied to extract long-term temporal trends towards the year 2100. Future projections of the North Atlantic ocean wave climate based on two of these alternatives are presented, i.e. an extrapolated linear trend and trends based on regression on atmospheric levels of CO2 and assuming future emission scenarios proposed by IPCC. It is further explored how such future trends can be related to the structural load calculations of ships. It will be demonstrated how the estimated future trends can be incorporated in joint environmental models to yield updated environmental contour lines that take possible changes in the ocean wave climate into account. In this way, the impact of climate change on the wave climate can be accounted for in stress and loads calculations and hence in the structural dimensioning of ships and offshore installations. The proposed approach is illustrated by an example showing the potential impact of the estimated long-term trends in the wave climate on the wave-induced structural loads of an oil tanker. Results indicate that the impact may be far from negligible, and that this may need to be considered in the future when performing loads calculations.

scholarly journals Estimation of Significant Wave Heights from ASCAT Scatterometer Data via Deep Learning Network

2021 ◽  
Vol 13 (2) ◽  
pp. 195
Author(s):  
He Wang ◽  
Jingsong Yang ◽  
Jianhua Zhu ◽  
Lin Ren ◽  
Yahao Liu ◽  
...  
Keyword(s):  
Deep Learning ◽  
Wave Height ◽  
Significant Wave Height ◽  
Incidence Angle ◽  
Ocean Waves ◽  
Global Scale ◽  
Learning Technology ◽  
Sea State ◽  
Significant Wave ◽  
Wave Heights

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.

Sea State Estimation Based on Ship Motions Measurements and Data Fusion

2013 ◽  
Author(s):  
Céline Drouet ◽  
Nicolas Cellier ◽  
Jérémie Raymond ◽  
Denis Martigny
Keyword(s):  
Data Fusion ◽  
State Estimation ◽  
Wave Height ◽  
Significant Wave Height ◽  
Wave Spectrum ◽  
Ocean Waves ◽  
Ship Motions ◽  
Sea State ◽  
Significant Wave ◽  
X Band

In-service monitoring can help to increase safety of ships especially regarding the fatigue assessment. For this purpose, it is compulsory to know the environmental conditions encountered: wind, but also the full directional wave spectrum. During the EU TULCS project, a full scale measurements campaign has been conducted onboard the CMA-CGM 13200 TEU container ship Rigoletto. She has been instrumented to measure deformation of the ship as well as the sea state encountered during its trip. This paper will focus on the sea state estimation. Three systems have been installed to estimate the sea state encountered by the Rigoletto: An X-band radar from Ocean Waves with WAMOS® system and two altimetric wave radars from RADAC®. Nevertheless, the measured significant wave height can be disturbed by several external elements like bow waves, sprays, sea surface ripples, etc… Furthermore, ship motions are also measured and can provide another estimation of the significant wave height using a specific algorithm developed by DCNS Research for the TULCS project. As all those estimations are inherently different, it is necessary to make a fusion of those data to provide a single estimation (“best estimate”) of the significant wave height. This paper will present the data fusion process developed for TULCS and show some first validation results.

Inferring significant wave height from seismic data: A comparison between methods.

2021 ◽  
Author(s):  
Francisco Bolrão ◽  
Co Tran ◽  
Miguel Lima ◽  
Sheroze Sheriffdeen ◽  
Diogo Rodrigues ◽  
...  
Keyword(s):  
Real Time ◽  
Wave Height ◽  
Seismic Data ◽  
Significant Wave Height ◽  
Transfer Functions ◽  
Seismic Station ◽  
Meteorological Data ◽  
Ocean Waves ◽  
The United States ◽  
Significant Wave

<p>The most pervasive seismic signal recorded on our planet – microseismic ambient noise -results from the coupling of energy between atmosphere, oceans and solid Earth. Because it carries information on ocean waves (source), the microseismic wavefield can be advantageously used to image ocean storms. This imaging is of interest both to climate studies – by extending the record of oceanic activity back into the early instrumental seismic record – and to real-time monitoring – where real-time seismic data can potentially be used to complement the spatially dense but temporally sparse satellite meteorological data.<br>In our work, we develop empirical transfer functions between seismic observations and ocean activity observations, in particular, significant wave height. We employ three different approaches: 1) The approach of Ferretti et al (2013), who compute a seismic significant wave height and invert only for the empirical conversion parameters between oceanic and seismic significant wave heights; 2) The classical approach of Bromirski et al (1999), who computed an empirical transfer function between ground-motion recorded at a coastal seismic station and significant wave height measured at a nearby ocean buoy; and 3) A novel recurrent neural-network (RNN) approach to infer significant wave height from seismic data. <br>We apply the three approaches to seismic and ocean buoy data recorded in the east coast of the United States. All three approaches are able to successfully predict ocean significant wave height from the seismic data. We compare the three approaches in terms of accuracy, computational effort and robustness. In addition, we investigate the regimes where each approach works best.  The results show that the RNN approach is able to predict well the significant wave height recorded at the buoy. The prediction is improved if several nearby seismic stations are used rather than just one. <br>This work is supported by FCT through projects UIDB/50019/2020 – IDL and UTAP-EXPL/EAC/0056/2017 - STORM.</p>

scholarly journals Significant Wave Height Estimation from Space-Borne Cyclone-GNSS Reflectometry

2019 ◽  
Vol 11 (5) ◽  
pp. 584 ◽  
Author(s):  
Qin Peng ◽  
Shuanggen Jin
Keyword(s):  
Standard Deviation ◽  
Correlation Coefficient ◽  
Wave Height ◽  
Significant Wave Height ◽  
Satellite System ◽  
Measurement Range ◽  
Ocean Dynamics ◽  
Global Ocean ◽  
Physical Parameters ◽  
Significant Wave

The significant wave height (SWH) of the sea is an important parameter and plays an important role in the prediction of waves and ocean dynamics. However, traditional methods, e.g., buoys or traditional remote sensing techniques such as X-band radar image have small measurement range and high cost. Recently, Global Navigation Satellite System-Reflectometry (GNSS-R) has provided a new opportunity to estimate the SWH, especially the space-borne Cyclone-GNSS (CYGNSS) launched on December 15, 2016. The GNSS-R uses the GNSS-reflected signal received by the receiver to invert ground physical parameters with all-weather, global fast coverage, high resolution, high precision, high long-term stability, rich signal sources, passive detection, and strong concealment. In this paper, the global ocean significant wave height is estimated using space-borne CYGNSS GNSS-R data for the first time though the relationship between the square root of the signal-to-noise ratio (SNR) data of CYGNSS delayed Doppler map (DDM) and the SWH. Then, the estimated significant wave height is compared with the satellite altimeter and buoy data. Compared with the AVISO SWH observation, the standard deviation value reaches 0.3080 m and the correlation coefficient reaches 0.9473 m. The correlation coefficient with the buoy SWH observation is 0.9539 m and the standard deviation is 0.2761 m. The SWH estimations from CYGNSS can provide important support in ocean shipping development, marine environmental protection, marine disaster warning and forecasting.

The corrections for significant wave height and attitude effects in the TOPEX radar altimeter

1994 ◽  
Vol 99 (C12) ◽  
pp. 24941 ◽  
Author(s):  
G. S. Hayne ◽  
D. W. Hancock ◽  
C. L. Purdy ◽  
P. S. Callahan
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Radar Altimeter ◽  
Significant Wave

Uncertainty of Ocean Wave Hindcasts Due to Wind Modeling

1995 ◽  
Vol 117 (4) ◽  
pp. 294-297 ◽  
Author(s):  
J. C. Teixeira ◽  
M. P. Abreu ◽  
C. Guedes Soares
Keyword(s):  
Wind Speed ◽  
Relative Error ◽  
Wave Height ◽  
Significant Wave Height ◽  
Second Generation ◽  
Wave Model ◽  
Ocean Wave ◽  
Wind Fields ◽  
Significant Wave ◽  
Wind Input

Two wind models were developed and their results were compared with data gathered during the Wangara experiment, so as to characterize their uncertainty. One of the models was adopted to generate the wind fields used as input to a second generation wave model. The relative error in the wind speed was considered in order to assess the uncertainties of the predictions or the significant wave height. Different time steps for the wind input were also used to determine their effect on the predicted significant wave height.

Monthly Variations of Global Wave Climate due to Global Warming

2015 ◽  
Vol 74 (5) ◽  
Author(s):  
Muhammad Zikra ◽  
Noriaki Hashimoto ◽  
Kodama Mitsuyasu ◽  
Kriyo Sambodho
Keyword(s):  
Global Warming ◽  
Wave Height ◽  
Significant Wave Height ◽  
Wave Climate ◽  
Ocean Wave ◽  
Climate Data ◽  
Significant Wave ◽  
Wide Range ◽  
Wind Climate ◽  
Ocean Wave Climate

Over recent years, ocean wave climate change due to global warming has attracted a lot of attention not only coastal and offshore engineer but also stakeholders in the marine industry. There is a wide range of application in ocean environment that require information on ocean wave climate data, such as ships design, design of offshore platforms and coastal structures or naval industry. In this research, monthly variation in significant wave height is studied using MRI-AGCM3.2 wind climate data for 25 year period from 1979-2003. The 25 year significant wave height simulation derived from JMA/MRI-AGCM wind climate data. The JMA/MRI-AGCM climate data were input into WAM model. The results showed that the monthly variability of significant wave height in the Northern Hemisphere is greater than in the Southern Hemisphere. Meanwhile, most of the equatorial regions are in calm condition all year. 

scholarly journals Kajian Energi Gelombang Laut Di Daerah Abrasi Serangai, Bengkulu Utara Melalui Pengamatan Tinggi Gelombang Laut

2021 ◽  
Vol 11 (2) ◽  
pp. 143
Author(s):  
Ashar Muda Lubis ◽  
Yosi Apriani Putri ◽  
Rio Saputra ◽  
Juhendi Sinaga ◽  
M Hasanudin ◽  
...  
Keyword(s):  
Wave Height ◽  
Wave Energy ◽  
Seasonal Variations ◽  
Coastal Area ◽  
Significant Wave Height ◽  
Ocean Waves ◽  
Wave Period ◽  
Maximum Wave Height ◽  
Significant Wave ◽  
Sea Wave

<p class="AbstractText"><span lang="EN-AU">The Serangai area, Batik Nau District, North Bengkulu has the highest average abrasion speed of 20 m/year. The abrasion could cause the coastal area to erode the coastline till several tens of meters. The purpose of this study was to determine the height of the ocean waves and to determine the energy of the ocean waves that has the potential to accelerate the abrasion process in the Serangai area. The research was carried out on November 5-7, 2018 in the Serangai beach area at a depth of 5 m using SBE 26 Plus Seagauge Wave equipment. The results showed that the observed wave height was between 0.8-1.6 m with a significant wave height (Hs) of 1.38 m. In addition, the wave period ranges from 5-11 s with a significant wave period (Ts) of 8.2 s. The result also shows that the maximum wave height of 1.6 m occurred on November 7, 2018 with maximum wave energy of 1800 J/m<sup>2</sup>. This result can perhaps accelerate the abrasion process in the Serangai area. It can also be seen that the wave height in the Serangai region is higher than in several other areas in Indonesia. However, it is necessary to continue observing the wave height to see the seasonal variations in sea wave height in Serangai area.</span></p>

Sign in / Sign up

Export Citation Format

Share Document