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.

Beyond significant wave height: A new approach for validating spectral wave models

2015 ◽  
Vol 100 ◽  
pp. 11-25 ◽  
Author(s):  
Edgar Peter Dabbi ◽  
Ivan D. Haigh ◽  
David Lambkin ◽  
Jamie Hernon ◽  
Jon J. Williams ◽  
...  
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
New Approach ◽  
Significant Wave ◽  
Wave Models

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 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.

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 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.

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.

scholarly journals STABILITY OF RUBBLE MOUND BREAKWATERS IN SHALLOW WATER AND SURF ZONE : AN EXPERIMENTAL STUDY

2012 ◽  
Vol 1 (33) ◽  
pp. 85
Author(s):  
Guirec Prevot ◽  
Olivier Boucher ◽  
Maryline Luck ◽  
Michel Benoit
Keyword(s):  
Shallow Water ◽  
Wave Height ◽  
Significant Wave Height ◽  
Characteristic Wave ◽  
Significant Wave ◽  
Wave Parameters ◽  
Rubble Mound ◽  
Wave Conditions ◽  
Wave Models ◽  
Rubble Mound Breakwaters

Rubble-mound breakwaters are often pre-designed with empirical formulae allowing the estimation of armour stone size or weight, taking into account the wave conditions (mainly a characteristic wave height and a characteristic period), the type and density of stone or block used, the slope of the mound, the acceptable level of damage, etc. In deep water conditions, the existing formulas are rather well established (e.g. Hudson and Van der Meer formulas among others). They use as input data wave parameters that are well defined (e.g. the significant wave height H1/3 or sometimes the height H1/10) and easily accessible, from in situ measurements or from numerical wave models. In shallow water however, and in particular in breaking wave conditions (where most of the small breakwaters are built), a number of physical processes (refraction, shoaling and breaking) significantly modify the incoming waves. They also lead to changes in the wave height distribution (which can no longer be regarded as being of Rayleightype) and in the shape of the wave spectrum. This, combined with the fact that most of the models used nowadays for nearshore wave propagation are spectral wave models (e.g. SWAN, TOMAWAC, etc.) and thus provide spectral parameters as output (typically the spectral significant wave height Hm0 and the peak period Tp or the mean energetic period Tm-1,0) has raised the question of which characteristic wave parameter should be used in stability formulas for rubble-mound breakwaters in shallow water. This has led to the consideration of more representative wave parameters such as H2% or Tm-1,0 which are sometimes less accessible from existing wave database or numerical modelling studies. The objective of the present study is to review and compare several available methods to calculate armour stone weight in shallow waters, and to provide some insight into the applicability and limitations of these methods based on a series of wave flume experiments.

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