Microwave scatter and sea state estimation: Two-scale ocean wave models

1978 ◽  
Vol 13 (1-4) ◽  
pp. 107-118 ◽  
Author(s):  
Robert O. Harger ◽  
David M. Levine
Keyword(s):  
State Estimation ◽  
Ocean Wave ◽  
Sea State ◽  
Wave Models

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 Characterization of Extreme Wave Conditions for Wave Energy Converter Design and Project Risk Assessment

2020 ◽  
Vol 8 (4) ◽  
pp. 289 ◽  
Author(s):  
Vincent S. Neary ◽  
Seongho Ahn ◽  
Bibiana E. Seng ◽  
Mohammad Nabi Allahdadi ◽  
Taiping Wang ◽  
...  
Keyword(s):  
Return Period ◽  
Wave Energy ◽  
Wave Energy Converter ◽  
Extreme Value Analysis ◽  
Extreme Wave ◽  
Energy Converter ◽  
Sea State ◽  
Value Analysis ◽  
Wave Conditions ◽  
Wave Models

Best practices and international standards for determining n-year return period extreme wave (sea states) conditions allow wave energy converter designers and project developers the option to apply simple univariate or more complex bivariate extreme value analysis methods. The present study compares extreme sea state estimates derived from univariate and bivariate methods and investigates the performance of spectral wave models for predicting extreme sea states at buoy locations within several regional wave climates along the US East and West Coasts. Two common third-generation spectral wave models are evaluated, a WAVEWATCH III® model with a grid resolution of 4 arc-minutes (6–7 km), and a Simulating WAves Nearshore model, with a coastal resolution of 200–300 m. Both models are used to generate multi-year hindcasts, from which extreme sea state statistics used for wave conditions characterization can be derived and compared to those based on in-situ observations at National Data Buoy Center stations. Comparison of results using different univariate and bivariate methods from the same data source indicates reasonable agreement on average. Discrepancies are predominantly random. Large discrepancies are common and increase with return period. There is a systematic underbias for extreme significant wave heights derived from model hindcasts compared to those derived from buoy measurements. This underbias is dependent on model spatial resolution. However, simple linear corrections can effectively compensate for this bias. A similar approach is not possible for correcting model-derived environmental contours, but other methods, e.g., machine learning, should be explored.

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>

scholarly journals A fully coupled Atmosphere–Ocean Wave modeling system (WEW) for the Mediterranean Sea: interactions and sensitivity to the resolved scales and mechanisms

2015 ◽  
Vol 8 (5) ◽  
pp. 4075-4112
Author(s):  
P. Katsafados ◽  
A. Papadopoulos ◽  
G. Korres ◽  
G. Varlas
Keyword(s):  
Data Exchange ◽  
Wind Wave ◽  
Aerodynamic Drag ◽  
Wave Spectrum ◽  
Ocean Wave ◽  
Wave System ◽  
Sea State ◽  
Scientific Performance ◽  
Research Activities ◽  
Fully Coupled

Abstract. It is commonly accepted that there is an urgent need for a better understanding of the factors that contribute to the air–sea interaction processes and their feedbacks. In this sense it is absolutely important to develop advanced numerical prediction systems that treat the atmosphere and the ocean as a unified system. The realistic description and understanding of the exchange processes near the ocean surface, requires the exact knowledge of the sea state and its evolution. This can be achieved by considering the sea surface and the atmosphere as a continuously cross talking dynamic system. Therefore, this study aims to present the effort towards developing a new, high-resolution, two-way fully coupled atmosphere–ocean wave model in order to support operational and research activities. A specific issue that it is emphasized here is the determination and parameterization of the air–sea momentum fluxes under conditions of extremely high and time-varying winds. Software considerations, data exchange as well as computational and scientific performance of the coupled system, so-called WEW, are also discussed throughout this study. In a case study of high-impact weather and sea state event, the wind–wave parameterization scheme reduces the resulted wind speed and the significant wave height as a response to the increased aerodynamic drag over rough sea surfaces. Overall, WEW offers a more realistic representation of the momentum exchanges in the ocean wind–wave system and includes the effects of the resolved wave spectrum on the drag coefficient and its feedback on the momentum flux.

scholarly journals The Contribution of High-Frequency Wind-Generated Surface Waves to the Stokes Drift

2020 ◽  
Vol 50 (12) ◽  
pp. 3455-3465
Author(s):  
Luc Lenain ◽  
Nick Pizzo
Keyword(s):  
Surface Waves ◽  
Wave Spectrum ◽  
Ocean Dynamics ◽  
Stokes Drift ◽  
Upper Ocean ◽  
Sea State ◽  
Instrument Measurement ◽  
Wave Models ◽  
Surface Wave Field

AbstractThe effects of nonbreaking surface waves on upper-ocean dynamics enter the wave-averaged primitive equations through the Stokes drift. Through the resulting upper-ocean dynamics, Stokes drift is a catalyst for the fluxes of heat and trace gases between the atmosphere and ocean. However, estimates of the Stokes drift rely crucially on properly resolving the wave spectrum. In this paper, using state-of-the-art spatial measurements (in situ and airborne remote sensing) from a number of different field campaigns, with environmental conditions ranging from 2 to 13 m s−1 wind speed and significant wave height of up to 4 m, we characterize the properties of the surface wave field across the equilibrium and saturation ranges and provide a simple parameterization of the transition between the two regimes that can easily be implemented in numerical wave models. We quantify the error associated with instrument measurement limitations, or incomplete numerical parameterizations, and propose forms for the continuation of these spectra to properly estimate the Stokes drift. Depending on the instrument and the sea state, predictions of surface Stokes drift may be underestimated by more than 50%.

Data-Driven Modeling for Transferable Sea State Estimation Between Marine Systems

2021 ◽  
pp. 1-11
Author(s):  
Xu Cheng ◽  
Guoyuan Li ◽  
Peihua Han ◽  
Robert Skulstad ◽  
Shengyong Chen ◽  
...  
Keyword(s):  
State Estimation ◽  
Data Driven ◽  
Sea State ◽  
Marine Systems ◽  
Data Driven Modeling
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