A new method for the validation of altimeter-derived sea state parameters with results from wind and wave models

1992 ◽  
Vol 97 (C6) ◽  
pp. 9705 ◽  
Author(s):  
Anne Guillaume ◽  
Nelly M. Mognard
Keyword(s):  
New Method ◽  
Sea State ◽  
Wave Models

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 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%.

scholarly journals Round Robin Assessment of Radar Altimeter Low Resolution Mode and Delay-Doppler Retracking Algorithms for Significant Wave Height

2020 ◽  
Vol 12 (8) ◽  
pp. 1254 ◽  
Author(s):  
Florian Schlembach ◽  
Marcello Passaro ◽  
Graham D. Quartly ◽  
Andrey Kurekin ◽  
Francesco Nencioli ◽  
...  
Keyword(s):  
Climate Change ◽  
Wave Height ◽  
Significant Wave Height ◽  
Low Resolution ◽  
Spectral Variability ◽  
Sea State ◽  
Significant Wave ◽  
In Situ Data ◽  
Wave Models

Radar altimeters have been measuring ocean significant wave height for more than three decades, with their data used to record the severity of storms, the mixing of surface waters and the potential threats to offshore structures and low-lying land, and to improve operational wave forecasting. Understanding climate change and long-term planning for enhanced storm and flooding hazards are imposing more stringent requirements on the robustness, precision, and accuracy of the estimates than have hitherto been needed. Taking advantage of novel retracking algorithms, particularly developed for the coastal zone, the present work aims at establishing an objective baseline processing chain for wave height retrieval that can be adapted to all satellite missions. In order to determine the best performing retracking algorithm for both Low Resolution Mode and Delay-Doppler altimetry, an objective assessment is conducted in the framework of the European Space Agency Sea State Climate Change Initiative project. All algorithms process the same Level-1 input dataset covering a time-period of up to two years. As a reference for validation, an ERA5-based hindcast wave model as well as an in-situ buoy dataset from the Copernicus Marine Environment Monitoring Service In Situ Thematic Centre database are used. Five different metrics are evaluated: percentage and types of outliers, level of measurement noise, wave spectral variability, comparison against wave models, and comparison against in-situ data. The metrics are evaluated as a function of the distance to the nearest coast and the sea state. The results of the assessment show that all novel retracking algorithms perform better in the majority of the metrics than the baseline algorithms currently used for operational generation of the products. Nevertheless, the performance of the retrackers strongly differ depending on the coastal proximity and the sea state. Some retrackers show high correlations with the wave models and in-situ data but significantly under- or overestimate large-scale spectral variability. We propose a weighting scheme to select the most suitable retrackers for the Sea State Climate Change Initiative programme.

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

Verification of 2D Wave Spectra Produced by Wave Models

2004 ◽  
Author(s):  
Jose´ Caˆndido ◽  
Henrique Oliveira Pires ◽  
M. Teresa Pontes
Keyword(s):  
Frequency Band ◽  
Wind Wave ◽  
Wave Spectra ◽  
Sea State ◽  
Directional Wave ◽  
Wave Models ◽  
Different Origins ◽  
Buoy Data

In this paper a methodology for assessing the accuracy of full directional wave spectra produced by wind-wave models is presented and tested. This methodology includes graphical and parametric comparisons of model directional spectra against data obtained from directional buoys. Results of the verification of 3rd generation wind-wave models using directional buoy data show that in general the accuracy of model directional results is good. In addition it was found that this methodology is well suited to identify the occurrence of different wave systems in the same sea state, namely swells within the same frequency band but with different origins.

A Simple and Robust Method for Calculating Return Periods of Ocean Waves

2018 ◽  
Author(s):  
Edward B. L. Mackay ◽  
Lars Johanning
Keyword(s):  
Ocean Waves ◽  
New Method ◽  
Threshold Analysis ◽  
Return Periods ◽  
Peaks Over Threshold ◽  
Short Term ◽  
Sea State ◽  
Individual Wave ◽  
Buoy Measurements

A new method is introduced for combining the long-term distribution of sea states with the short-term distribution of individual wave or crest heights, conditional on sea state. The method uses a Monte Carlo approach to simulate random realisations of the maximum wave or crest height in each sea state. A peaks-over-threshold analysis is conducted on the random maxima in each sea state in order to estimate the long-term distribution of individual wave or crest heights. The new method is significantly simpler than existing methods such as the equivalent storm approach, requires fewer assumptions and has similar computational times. The new method is applied to a 35 year dataset of wave buoy measurements and is shown to produce almost identical estimates of return values of individual crest heights to the equivalent storm method.

Selective Sampling and Orientation of Non-Homogeneous Tissues

1968 ◽  
Vol 26 ◽  
pp. 98-99
Author(s):  
C. C. Clawson ◽  
L. W. Anderson ◽  
R. A. Good
Keyword(s):  
Electron Microscopy ◽  
Electron Microscope ◽  
Light Microscopy ◽  
Random Sampling ◽  
New Method ◽  
Microscope Examination ◽  
Small Areas ◽  
Selective Sampling ◽  
Large Numbers ◽  
Specific Orientation

Investigations which require electron microscope examination of a few specific areas of non-homogeneous tissues make random sampling of small blocks an inefficient and unrewarding procedure. Therefore, several investigators have devised methods which allow obtaining sample blocks for electron microscopy from region of tissue previously identified by light microscopy of present here techniques which make possible: 1) sampling tissue for electron microscopy from selected areas previously identified by light microscopy of relatively large pieces of tissue; 2) dehydration and embedding large numbers of individually identified blocks while keeping each one separate; 3) a new method of maintaining specific orientation of blocks during embedding; 4) special light microscopic staining or fluorescent procedures and electron microscopy on immediately adjacent small areas of tissue.

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