scholarly journals EXTREMAL PREDICTION OF SIGNIFICANT WAVE HEIGHT

1978 ◽  
Vol 1 (16) ◽  
pp. 14 ◽  
Author(s):  
Enrique Copeiro
Keyword(s):  
Distribution Function ◽  
Wave Height ◽  
Significant Wave Height ◽  
Goodness Of Fit ◽  
Theoretical Foundation ◽  
Extreme Values ◽  
Point Of View ◽  
Significant Wave ◽  
Wide Range ◽  
Empirical Point

The most generally used procedure for estimating the extremal distribution of ge_o physical variates consists in obtaining a sample of extreme values (for instance a number of annual maxima) and fitting to them a distribution function. One of the main problems - involved in this procedure is the choice of the type of distribution adequate in each case. No general agreement exists, to date, for any geophysical variate. This means a serio us trouble because of the wide range of extrapolations which can usually be obtained by - using different functions. Some of the authors who have tackled this problem have adopted a strictly empirical point of view, going as far in it as to advise to make a choice for each particular case, according to the goodness-of-fit obtained when several types of dis tribution functions are fitted to the sample. Others have instead tried to base the choices on some theoretical foundation, placing less emphasis in the goodness of the fits and generally suggesting the use of one or other of the three well known Asymptotic Extremal Distributions.

scholarly journals The land–sea coastal border: a quantitative definition by considering the wind and wave conditions in a wave-dominated, micro-tidal environment

Ocean Science ◽  
2019 ◽  
Vol 15 (1) ◽  
pp. 113-126 ◽  
Author(s):  
Agustín Sánchez-Arcilla ◽  
Jue Lin-Ye ◽  
Manuel García-León ◽  
Vicente Gràcia ◽  
Elena Pallarès
Keyword(s):  
Distribution Function ◽  
Wind Velocity ◽  
Wave Height ◽  
Significant Wave Height ◽  
Gaussian Copula ◽  
Logistic Distribution ◽  
Normal Distribution Function ◽  
Significant Wave ◽  
Fringe Width ◽  
Quantitative Definition

Abstract. A quantitative definition for the land–sea (coastal) transitional area is proposed here for wave-driven areas, based on the variability and isotropy of met-ocean processes. Wind velocity and significant wave height fields are examined for geostatistical anisotropy along four cross-shore transects on the Catalan coast (north-western Mediterranean), illustrating a case of significant changes along the shelf. The variation in the geostatistical anisotropy as a function of distance from the coast and water depth has been analysed through heat maps and scatter plots. The results show how the anisotropy of wind velocity and significant wave height decrease towards the offshore region, suggesting an objective definition for the coastal fringe width. The more viable estimator turns out to be the distance at which the significant wave height anisotropy is equal to the 90th percentile of variance in the anisotropies within a 100 km distance from the coast. Such a definition, when applied to the Spanish Mediterranean coast, determines a fringe width of 2–4 km. Regarding the probabilistic characterization, the inverse of wind velocity anisotropy can be fitted to a log-normal distribution function, while the significant wave height anisotropy can be fitted to a log-logistic distribution function. The joint probability structure of the two anisotropies can be best described by a Gaussian copula, where the dependence parameter denotes a mild to moderate dependence between both anisotropies, reflecting a certain decoupling between wind velocity and significant wave height near the coast. This wind–wave dependence remains stronger in the central bay-like part of the study area, where the wave field is being more actively generated by the overlaying wind. Such a pattern controls the spatial variation in the coastal fringe width.

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 SAMPLING BIAS IN THE ESTIMATION OF SIGNIFICANT WAVE HEIGHT EXTREME VALUES

2017 ◽  
pp. 33
Author(s):  
Fabio Dentale ◽  
Ferdinando Reale ◽  
Felice D'Alessandro ◽  
Leonardo Damiani ◽  
Angela Di Leo ◽  
...  
Keyword(s):  
Wave Height ◽  
Time Resolution ◽  
Significant Wave Height ◽  
Extreme Values ◽  
Sampling Bias ◽  
Threshold Value ◽  
Return Time ◽  
Sampling Interval ◽  
Significant Wave ◽  
Wave Models

It has been shown before, and it is intuitively evident, that in a Significant Wave Height (SWH) time series, the longer the sampling interval, the lower is the number of events which are above a given threshold value. As a consequence, the use of data with a low time resolution (such as a 3 h sampling, for instance) causes a considerable undervaluation of the extreme SWH values for a given return time RT. In this paper an example of such a bias is provided, and a method is suggested to estimate it on a regional basis. Results may help to improve the use of historical wave meters data which were often collected with a low time resolution, and may also provide a tool to improve the application of Numerical Meteo-Wave models to the evaluation of extremes.

scholarly journals Projection and Analysis of Extreme Wave Climate

2006 ◽  
Vol 19 (21) ◽  
pp. 5581-5605 ◽  
Author(s):  
Sofia Caires ◽  
Val R. Swail ◽  
Xiaolan L. Wang
Keyword(s):  
Poisson Process ◽  
Sea Level ◽  
Wave Height ◽  
Significant Wave Height ◽  
Climate Model ◽  
Extreme Values ◽  
Nonhomogeneous Poisson Process ◽  
Sea Level Pressure ◽  
Significant Wave ◽  
Level Pressure

Abstract The nonhomogeneous Poisson process is used to model extreme values of the 40-yr ECMWF Re-Analysis (ERA-40) significant wave height. The parameters of the model are expressed as functions of the seasonal mean sea level pressure anomaly and seasonal squared sea level pressure gradient index. Using projections of the sea level pressure under three different forcing scenarios by the Canadian coupled climate model, projections of the parameters of the nonhomogeneous Poisson process are made, trends in these projections are determined, return-value estimates of significant wave height up to the end of the twenty-first century are projected, and their uncertainties are assessed. The uncertainty of estimates associated with the nonhomogeneous Poisson process estimates is studied and compared with the homologous estimates obtained using a nonstationary generalized extreme value model.

scholarly journals Study of Directional Declustering for Estimating Extreme Wave Heights in the Yellow Sea

2020 ◽  
Vol 8 (4) ◽  
pp. 236 ◽  
Author(s):  
Huijun Gao ◽  
Zhuxiao Shao ◽  
Guoxiang Wu ◽  
Ping Li
Keyword(s):  
Wave Height ◽  
Yellow Sea ◽  
Significant Wave Height ◽  
Extreme Values ◽  
The Yellow Sea ◽  
Distribution Model ◽  
Significant Wave ◽  
Window Method ◽  
Wave Heights ◽  
Significant Wave Heights

The study of extreme waves is important for the protection of coastal and ocean structures. In this work, a 22-year (1990–2011) wave hindcast in the Yellow Sea is employed to perform the assessment of extreme significant wave heights in this area. To extract the independent sample from this database, the fixed window method is used, which takes the peak significant wave height within five d. With the selected samples, directional declustering is studied to extract the homogenous sample. The results show that most of the independent samples (especially large samples) are observed in the North. In this direction, the peak over threshold (POT) method is used to extract the extreme sample from the homogenous sample, and then the generalized Pareto distribution model is used to extrapolate the extreme significant wave height. In addition to this combination, the annual maxima method with the Gumbel model is also used for estimating extreme values. The comparisons show that the return significant wave heights of the first combination are reliable, resulting from a flexible sampling window in the POT method. With this conclusion, the extreme significant wave height is extrapolated from the Yellow Sea, which can be used to protect the structure in the main directional bin.

100-Year Return Value Estimates for Ocean Wind Speed and Significant Wave Height from the ERA-40 Data

2005 ◽  
Vol 18 (7) ◽  
pp. 1032-1048 ◽  
Author(s):  
S. Caires ◽  
A. Sterl
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
Significant Wave Height ◽  
Extreme Values ◽  
Domain Of Attraction ◽  
Altimeter Data ◽  
Time Variability ◽  
Threshold Method ◽  
Significant Wave ◽  
Ocean Wind

Abstract In this article global estimates of 100-yr return values of wind speed and significant wave height are presented. These estimates are based on the ECMWF 40-yr Re-Analysis (ERA-40) data and are linearly corrected using estimates based on buoy data. This correction is supported by global Topographic Ocean Experiment (TOPEX) altimeter data estimates. The calculation of return values is based on the peaks-over-threshold method. The large amount of data used in this study provides evidence that the distributions of significant wave height and wind speed data belong to the domain of attraction of the exponential. Further, the effect of the space and time variability of significant wave height and wind speed on the prediction of their extreme values is assessed. This is done by performing detailed global extreme value analyses using different decadal subperiods of the 45-yr-long ERA-40 dataset.

scholarly journals Global Estimates of Extreme Wind Speed and Wave Height

2011 ◽  
Vol 24 (6) ◽  
pp. 1647-1665 ◽  
Author(s):  
J. Vinoth ◽  
I. R. Young
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
Return Period ◽  
Significant Wave Height ◽  
Extreme Values ◽  
Significant Wave ◽  
Extreme Wind ◽  
Extreme Wind Speed ◽  
Global Estimates ◽  
Buoy Measurements

Abstract A long-term dataset of satellite altimeter measurements of significant wave height and wind speed, spanning 23 years, is analyzed to determine extreme values corresponding to a 100-yr return period. The analysis considers the suitability of both the initial distribution method (IDM) and peaks-over-threshold (POT) approaches and concludes that for wave height both IDM and POT methods can yield reliable results. For the first time, the global POT results for wave height show spatial consistency, a feature afforded by the larger dataset. The analyses also show that the POT approach is sensitive to spatial resolution. Since wind speed has greater spatial and temporal variability than wave height, the POT approach yields unreliable results for wind speed as a result of undersampling of peak events. The IDM approach does, however, generate extreme wind speed values in reasonable agreement with buoy estimates. The results show that the altimeter database can estimate 100-yr return period significant wave height to within 5% of buoy measurements and the 100-yr wind speed to within 10% of buoy measurements when using the IDM approach. Owing to the long dataset and global coverage, global estimates of extreme values can be developed on a 1° × 1° grid when using the IDM and a coarser 2° × 2° for the POT approach. The high-resolution 1° × 1° grid together with the long duration of the dataset means that finescale features not previously identified using altimeter data are clearly apparent in the IDM results. Goodness-of-fit tests show that the observed data conform to a Fisher–Tippett Type 1 (FT-1) distribution. Even in regions such as the Gulf of Mexico where extreme forcing is produced by small-scale hurricanes, the altimeter results are consistent with buoy data.

scholarly journals Comparing the Currents Measured by CARTHE, CODE and SVP Drifters as a Function of Wind and Wave Conditions in the Southwestern Mediterranean Sea

Sensors ◽  
2022 ◽  
Vol 22 (1) ◽  
pp. 353
Author(s):  
Pierre-Marie Poulain ◽  
Luca Centurioni ◽  
Tamay Özgökmen
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
Significant Wave Height ◽  
Stokes Drift ◽  
Large Scatter ◽  
Sea State ◽  
Near Surface ◽  
Significant Wave ◽  
Surface Ocean ◽  
Wide Range

Instruments drifting at the ocean surface are quasi-Lagrangian, that is, they do not follow exactly the near-surface ocean currents. The currents measured by three commonly-used drifters (CARTHE, CODE and SVP) are compared in a wide range of sea state conditions (winds up to 17 m/s and significant wave height up to 3 m). Nearly collocated and simultaneous drifter measurements in the southwestern Mediterranean reveal that the CARTHE and CODE drifters measure the currents in the first meter below the surface in approximately the same way. When compared to SVP drogued at 15 m nominal depth, the CODE and CARTHE currents are essentially downwind (and down-wave), with a typical speed of 0.5–1% of the wind speed. However, there is a large scatter in velocity differences between CODE/CARTHE and SVP for all wind and sea state conditions encountered, principally due to vertical and horizontal shears not related to the wind. For the CODE drifter with wind speed larger than 10 m/s and significant wave height larger than 1 m, about 30–40% of this difference can be explained by Stokes drift.

Evolution of the Extreme Wave Region in the North Atlantic Using a 23 Year Hindcast

2015 ◽  
Author(s):  
Sonia Ponce de León ◽  
João H. Bettencourt ◽  
Joseph Brennan ◽  
Frederic Dias
Keyword(s):  
Wave Height ◽  
North Atlantic ◽  
Significant Wave Height ◽  
Extreme Values ◽  
Extreme Wave ◽  
North Atlantic Region ◽  
Atlantic Region ◽  
Significant Wave ◽  
The North ◽  
The North Atlantic

The IOWAGA data base for the North Atlantic region was used to identify the region where extreme values of significant wave height are more likely to occur. The IOWAGA database [1] was obtained from the WAVEWATCH III model [2] hindcast using the CFSR (Climate Forecast System Reanalysis) from NOAA [3,4]. The period of the study covers 1990 up to 2012 (23 years). The variability of the significant wave height was assessed by computing return periods for sea storms where the significant wave height exceeds a given threshold. The return periods of sea storms where the Hs exceeds extreme values for the north Atlantic region were computed allowing for the identification of the extreme wave regions which show that extreme waves are more likely to occur in the storm track regions of the tropical and extratropical north Atlantic cyclones.

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