scholarly journals Sea State Determination from Ship-Based Geodetic GPS

2014 ◽  
Vol 31 (11) ◽  
pp. 2556-2564 ◽  
Author(s):  
James Foster ◽  
Ning Li ◽  
Kwok Fai Cheung
Keyword(s):  
Wave Height ◽  
Wave Model ◽  
Ocean Waves ◽  
Sea Surface ◽  
Wave Direction ◽  
Sea State ◽  
Dominant Wave ◽  
Model Predictions ◽  
Economic Vitality ◽  
Buoy Data

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.

scholarly journals Global ship accidents and ocean swell-related sea states

2017 ◽  
Vol 17 (11) ◽  
pp. 2041-2051 ◽  
Author(s):  
Zhiwei Zhang ◽  
Xiao-Ming Li
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Environmental Issues ◽  
Wave Model ◽  
Economic Losses ◽  
Wave Direction ◽  
Sea State ◽  
Mean Wave Period ◽  
Numerical Wave ◽  
Wind Sea

Abstract. With the increased frequency of shipping activities, navigation safety has become a major concern, especially when economic losses, human casualties and environmental issues are considered. As a contributing factor, the sea state plays a significant role in shipping safety. However, the types of dangerous sea states that trigger serious shipping accidents are not well understood. To address this issue, we analyzed the sea state characteristics during ship accidents that occurred in poor weather or heavy seas based on a 10-year ship accident dataset. Sea state parameters of a numerical wave model, i.e., significant wave height, mean wave period and mean wave direction, were analyzed for the selected ship accident cases. The results indicated that complex sea states with the co-occurrence of wind sea and swell conditions represent threats to sailing vessels, especially when these conditions include similar wave periods and oblique wave directions.

On the space-time maximum oceanic waves and related sea-state parameters during the tropical storm Kong-rey (2018)

2021 ◽  
Author(s):  
Alvise Benetazzo ◽  
Francesco Barbariol ◽  
Filippo Bergamasco ◽  
Luciana Bertotti ◽  
Luigi Cavaleri ◽  
...  
Keyword(s):  
Wave Height ◽  
Wave Model ◽  
Space Time ◽  
Tropical Storm ◽  
Sea Surface ◽  
Surface Elevation ◽  
Extreme Value Statistics ◽  
Northwestern Pacific ◽  
Sea State ◽  
Temporal Domain

<div> <p><span>The characteristics of the space-time extreme value statistics of maximum oceanic waves under the tropical storm Kong-rey (2018) is investigated in the Northwestern Pacific Ocean (Yellow Sea and East China Sea). We base our composite analysis upon space-time 3D measurements of the sea surface elevation field and wave model frequency/direction spectra. We focus on the highest individual waves that may develop at short-term/range under the cyclonic winds and we consider the spatial distribution around the storm centre of two main variables of interest, namely the maximum sea surface elevation (crest height) and the maximum wave height. Their expectations are linked to characteristic parameters of the sea state, such as the significant wave height, the mean steepness, the directional spreading, the bandwidth, of which we extend the meaning in the temporal domain in order to include the 3D geometry of the wave field. Our results evidence the sea regions where the highest individual waves may be expected and highlights, via scale analysis, the main mechanisms responsible for the generation of space-time extreme conditions. </span></p> </div>

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.

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.

Towards a unified framework for maximum wave computation from numerical models: outcomes from the LATEMAR project.

2020 ◽  
Author(s):  
Alvise Benetazzo ◽  
Francesco Barbariol ◽  
Paolo Pezzutto ◽  
Luciana Bertotti ◽  
Luigi Cavaleri ◽  
...  
Keyword(s):  
Numerical Models ◽  
Wave Spectrum ◽  
Wave Model ◽  
Ocean Waves ◽  
Unified Framework ◽  
Sea State ◽  
Large Wave ◽  
Wavewatch Iii ◽  
Wave Models ◽  
The Impact

<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>

Using Remote Sensed Data for Wave Energy Resource Assessment

2008 ◽  
Author(s):  
M. T. Pontes ◽  
M. Bruck
Keyword(s):  
Wave Height ◽  
Wave Energy ◽  
Wind Waves ◽  
Energy Resource ◽  
Ocean Waves ◽  
Resource Assessment ◽  
Altimeter Data ◽  
Zero Crossing ◽  
Frequency Wave ◽  
Buoy Data

The conversion of the energy contained in ocean waves into an useful form of energy namely electrical energy requires the knowledge at least of wave height and period parameters. Since 1992 at least one altimeter has been accurately measuring significant wave height Hs. To derive wave period parameters namely zero-crossing period Tz from the altimeter backscatter coefficient various models have been proposed. Another space-borne sensor that measures ocean waves is SAR (or the advanced ASAR) from which directional spectra are obtained. In this paper various models proposed to compute Tz from altimeter data are presented and verified against a collocated set of Jason altimeter and NDBC buoy data. A good fitting of altimeter estimates to buoy data was found. Directional spectra obtained from ENVISAT ASAR measurements were compared against NDBC buoy data. It was concluded that for the buoys that are more sensitive to long low-frequency wave components the fitting of wave parameters and spectral form is good for short spatial distances. However, since the cut-off ASAR frequency is low (reliable information is provided only for long waves) their use for wave energy resource assessment in areas where wind-waves are important is limited.

scholarly journals Wave intensities and slopes in Lagrangian seas

2007 ◽  
Vol 39 (04) ◽  
pp. 1020-1035 ◽  
Author(s):  
Sofia Åberg
Keyword(s):  
Gaussian Random Field ◽  
Gaussian Model ◽  
Wave Model ◽  
Ocean Waves ◽  
Offshore Structures ◽  
Sea Surface ◽  
Lagrangian Model ◽  
Level Crossing ◽  
Wave Slamming ◽  
Wave Slope

In many applications, such as remote sensing or wave slamming on ships and offshore structures, it is important to have a good model for wave slope. Today, most models are based on the assumption that the sea surface is well described by a Gaussian random field. However, since the Gaussian model does not capture several important features of real ocean waves, e.g. the asymmetry of crests and troughs, it may lead to unconservative safety estimates. An alternative is to use a stochastic Lagrangian wave model. Few studies have been carried out on the Lagrangian model; in particular, very little is known about its probabilistic properties. Therefore, in this paper we derive expressions for the level-crossing intensity of the Lagrangian sea surface, which has the interpretation of wave intensity, as well as the distribution of the wave slope at an arbitrary crossing. These results are then compared to the corresponding intensity and distribution of slope for the Gaussian model.

scholarly journals Operational numerical wind-wave model for the Black Sea

2000 ◽  
Vol 1 (1) ◽  
pp. 65
Author(s):  
A. KORTCHEVA ◽  
G. KORTCHEV ◽  
J. M. LEFEVRE
Keyword(s):  
Shallow Water ◽  
Real Time ◽  
Wave Height ◽  
Black Sea ◽  
Water Wave ◽  
Wind Wave ◽  
Wave Model ◽  
The Black Sea ◽  
Sea State ◽  
Height Data

In this paper the discrete spectral shallow water wave model named VAGBUHL1 is presented. This model is used for real-time Black Sea state forecasting. The model was verified against satellite ERS-2 altimeter wave height data.

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.

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