scholarly journals Sea state from ocean video with singular spectrum analysis and extended Kalman filter

2021 ◽  
Author(s):  
Antonis Loizou ◽  
Jacqueline Christmas
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Wave Height ◽  
Spectrum Analysis ◽  
Significant Wave Height ◽  
Singular Spectrum Analysis ◽  
Ocean Waves ◽  
Dominant Frequency ◽  
Significant Wave ◽  
Singular Spectrum

AbstractA method for estimating key parameters of ocean waves (the dominant frequency and the significant wave height) from uncalibrated monoscopic video is proposed, based on temporal variation of the wave field, specifically time series of pixel intensities. The methodology tracks the principal component of the movement of water in the video, which we propose is associated with the dominant frequency of the ocean. To accomplish this, the singular spectrum analysis algorithm and the extended Kalman filter are used. Then, the shape of an empirical spectrum is used in order to translate the dominant frequency output into a significant wave height estimation.

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 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>

scholarly journals Evaluation of Assimilation in the MASNUM Wave Model Based on Jason-3 and CFOSAT

2021 ◽  
Vol 13 (19) ◽  
pp. 3833
Author(s):  
Meng Sun ◽  
Jianting Du ◽  
Yongzeng Yang ◽  
Xunqiang Yin
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Wave Model ◽  
Ocean Waves ◽  
Validation Data ◽  
Engineering Construction ◽  
Significant Wave ◽  
Offshore Engineering ◽  
The Indian Ocean ◽  
Dynamic Sampling

Accurate numerical simulation of ocean waves is one of the most important measures to ensure shipping safety, offshore engineering construction, etc. The use of wave observations from satellite is an efficient way to correct model results. The goal of this paper is to assess the performance of assimilation in the MASNUM wave model for the Indian Ocean. The assimilation technique is based on Ensemble Adjusted Kalman Filter, with a variable ensemble constructed by the dynamic sampling method rather than ensemble members of wave model. Observations of significant wave height from satellites Jason-3 and CFOSAT are regarded as assimilation data and independent validation data, respectively. The results indicate good performance in terms of absolute mean error for significant wave height. Model error decreases by roughly 20–40% in high-sea conditions.

Climatology, Variability and Extrema of Ocean Waves: The Web-Based KNMI/ERA-40 Wave Atlas

2006 ◽  
Author(s):  
Andreas Sterl ◽  
Sofia Caires
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Wave Model ◽  
Ocean Waves ◽  
Wave Period ◽  
Web Based ◽  
Significant Wave ◽  
Wave Parameters ◽  
Wave Heights ◽  
The Web

The European Centre for Medium Range Weather Forecasts (ECMWF) has recently finished ERA-40, a reanalysis covering the period September 1957 to August 2002. One of the products of ERA-40 consists of 6-hourly global fields of wave parameters like significant wave height and wave period. These data have been generated with the Centre’s WAM wave model. From these results the authors have derived climatologies of important wave parameters, including significant wave height, mean wave period, and extreme significant wave heights. Particular emphasis is on the variability of these parameters, both in space and time. Besides for scientists studying climate change, these results are also important for engineers who have to design maritime constructions. This paper describes the ERA-40 data and gives an overview of the results derived. The results are available on a global 1.5° × 1.5° grid. They are accessible from the web-based KNMI/ERA-40 Wave Atlas at http://www.knmi.nl/waveatlas.

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.

scholarly journals The importance of wind forcing in fjord wave modelling

2019 ◽  
Vol 70 (1) ◽  
pp. 57-75 ◽  
Author(s):  
Konstantinos Christakos ◽  
Birgitte R. Furevik ◽  
Ole Johan Aarnes ◽  
Øyvind Breivik ◽  
Laura Tuomi ◽  
...  
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Wave Model ◽  
Ocean Waves ◽  
Wind Forcing ◽  
Significant Wave ◽  
Surface Ocean ◽  
Open Sea ◽  
Mean Wave Period ◽  
Wind Input

AbstractAccurate predictions of surface ocean waves in coastal areas are important for a number of marine activities. In complex coastlines with islands and fjords, the quality of wind forcing significantly affects the results. We investigate the role of wind forcing on wave conditions in a fjord system partly exposed to open sea. For this reason, we implemented the wave model SWAN at the west coast of Norway using four different wind forcing. Wind and wave estimates were compared with observations from five measurement sites. The best results in terms of significant wave height are found at the sites exposed to offshore conditions using a wind input that is biased slightly high compared with the buoy observations. Positively biased wind input, on the other hand, leads to significant overestimation of significant wave height in more sheltered locations. The model also shows a poorer performance for mean wave period in these locations. Statistical results are supported by two case studies which also illustrate the effect of high spatial resolution in wind forcing. Detailed wind forcing is necessary in order to obtain a realistic wind field in complex fjord terrain, but wind channelling and lee effects may have unpredictable effects on the wave simulations. Pure wave propagation (no wind forcing) is not able to reproduce the highest significant wave height in any of the locations.

scholarly journals IMPLEMENTATION AND TESTING OF A POWER MATRIX-BASED WAVE ENERGY CONVERSION MODEL AND THE EFFECT SIMULATED ON THE WAVE FIELD — CASE STUDY OF LAGUNA, SC, BRAZIL

2019 ◽  
Vol 18 (1) ◽  
pp. 50
Author(s):  
P. H. Oleinik ◽  
W. C. Marques
Keyword(s):  
Energy Conversion ◽  
Wave Height ◽  
Wave Energy ◽  
Significant Wave Height ◽  
Renewable Energy Sources ◽  
Electrical Energy ◽  
Ocean Waves ◽  
Wave Energy Conversion ◽  
Significant Wave ◽  
Order Of Magnitude

Electrical energy has become an essential resource for mankind and, as the population and technological dependency grow, also does the electricity demand. This necessity boosted numerous studies which focus on clean and renewable energy sources. Ocean wave energy is one of the most environmentally friendly sources of energy since it does not emit pollutants to the atmosphere and does not produce harmful waste. Another positive point about ocean waves is that they are inexhaustible, therefore a power plant could, potentially, provide energy indefinitely. Hence the object of this study is to estimate the wave energy reduction caused by the presence of wave energy conversion (WEC) devices near the coastline of Laguna, Brazil. In order to study the coastal impact of a WEC farm, the third generation sea state model TOMAWAC was used to simulate the waves on the Southern Brazilian Shelf under two different conditions, with and without the presence of an array of WECs. The results show that the mean significant wave height in the blockaded area undergoes a slight drop, caused by the presence of the WECs, which do not appear in the other scenario. But this reduction of the significant wave height is negligible compared to the order of magnitude of the wave height itself.

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