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.

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 Wind Wave Growth at Short Fetch

2008 ◽  
Vol 38 (7) ◽  
pp. 1597-1606 ◽  
Author(s):  
T. Lamont-Smith ◽  
T. Waseda
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
Significant Wave Height ◽  
Field Data ◽  
Wind Wave ◽  
Wind Waves ◽  
Retention Rates ◽  
Horizontal Distance ◽  
Wave Tank ◽  
Significant Wave

Abstract Wave wire data from the large wind wave tank of the Ocean Engineering Laboratory at the University of California, Santa Barbara, are analyzed, and comparisons are made with published data collected in four other wave tanks. The behavior of wind waves at various fetches (7–80 m) is very similar to the behavior observed in the other tanks. When the nondimensional frequency F* or nondimensional significant wave height H* is plotted against nondimensional fetch x*, a large scatter in the data points is found. Multivariate regression to the dimensional parameters shows that significant wave height Hsig is a function of U2x and frequency F is a function of U1.25x, where U is the wind speed and x is the horizontal distance, with the result that in general for wind waves at a particular fetch in a wave tank, approximately speaking, the wave frequency is inversely proportional to the square root of the wind speed and the wavelength is proportional to the wind speed. Similarly, the wave height is proportional to U1.5 and the orbital velocity is proportional to U. Comparison with field data indicates a transition from this fetch law to the conventional one [the Joint North Sea Wave Project (JONSWAP)] for longer fetch. Despite differences in the fetch relationship for the wave tank and the field data, the wave height and wave period satisfy Toba’s 3/2 power law. This law imposes a strong constraint on the evolution of wind wave energy and frequency; consequently, the energy and momentum retention rate are not independent. Both retention rates grow with wind speed and fetch at the short fetches present in the wave tank. The observed retention rates are completely different from those typically observed in the field, but the same constraint (Toba’s 3/2 law) holds true.

Uncertainty of Ocean Wave Hindcasts Due to Wind Modeling

1995 ◽  
Vol 117 (4) ◽  
pp. 294-297 ◽  
Author(s):  
J. C. Teixeira ◽  
M. P. Abreu ◽  
C. Guedes Soares
Keyword(s):  
Wind Speed ◽  
Relative Error ◽  
Wave Height ◽  
Significant Wave Height ◽  
Second Generation ◽  
Wave Model ◽  
Ocean Wave ◽  
Wind Fields ◽  
Significant Wave ◽  
Wind Input

Two wind models were developed and their results were compared with data gathered during the Wangara experiment, so as to characterize their uncertainty. One of the models was adopted to generate the wind fields used as input to a second generation wave model. The relative error in the wind speed was considered in order to assess the uncertainties of the predictions or the significant wave height. Different time steps for the wind input were also used to determine their effect on the predicted significant wave height.

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 VALIDATION OF JASON-2 AND ENVISAT WIND SPEED AND SIGNIFICANT WAVE HEIGHT DATA IN THE INTERTROPICAL ZONE

2013 ◽  
Vol 31 (3) ◽  
pp. 483 ◽  
Author(s):  
Guilherme Colaço Melo Dos Passos ◽  
Nelson Violante Carvalho ◽  
Uggo Ferreira Pinho ◽  
Alexandre Pereira Cabral ◽  
Frederico F. Ostritz
Keyword(s):  
Wind Speed ◽  
Correlation Coefficient ◽  
Wave Height ◽  
Significant Wave Height ◽  
Wind Waves ◽  
Altimeter Data ◽  
Data Set ◽  
Significant Wave ◽  
Wave Measurements ◽  
Satellite Radar

ABSTRACT. The estimates of significant wave height (SWH) and wind speed at 10 meter height (u10) from the Jason-2 and ENVISAT satellites, over the intertropical region, are analysed. Some authors have tested the dependency of satellite radar wind/wave measurements on local environmental conditions, particularly on wave age, with no conclusive results. Our data show that Jason-2 overestimates high values of SWH and underestimates low values, while ENVISAT exhibits the opposite behaviour. The correlation coefficient between buoy measurements and altimeter data is around 0.95, with bias and root mean square error (RMSE) of, 3 and 15 cm respectively. On the other hand, Jason-2 underestimates u10 throughout the whole measured range, while ENVISAT overestimates throughout the whole range for speeds over 3 m/s. The correlation coefficient is around 0.90, with bias and RMSE around 0.20 cm and 1.5 m/s, respectively. The altimeter estimates in the intertropical region are similar to those obtained with global coverage, hence the sensitivity to sea state to extract wind speed and wave height is not so obvious in our data set. Therefore, the results indicate that the algorithms employed have a fair enough performance in the intertropical region.Keywords: wind waves, wind speed, altimeter, Jason-2, ENVISAT. RESUMO. As estimativas de altura significativa de onda (SWH) e de intensidade do vento a 10 metros de altura (u10) dos altímetros dos satélites Jason-2 e ENVISAT, obtidas na região intertropical, são analisadas. Alguns trabalhos apontam para uma possível dependência da esbeltez das ondas, e portanto do estado de mar, para extração de u10 e SWH, o que tornaria os algoritmos empregados dependentes da localidade. Os resultados aqui obtidos mostram que o Jason-2 em geral superestima altos valores de SWH e subestima baixos valores, enquanto que para o ENVISAT a tendência encontrada é a inversa. Foram obtidos coeficientes de correlação entre a SWH de boias e dos altímetros em torno de 0,95, e bias e erro médio quadrático (RMSE) de aproximadamente 3 e 15 cm, respectivamente. Em relação à u10, o Jason-2 subestima ligeiramente os valores, independente da faixa de intensidade do vento, enquanto que o ENVISAT os superestimam em quase todas as faixas de intensidade, exceto para ventos menores que 3 c/s. Os coeficientes de correlação se encontram em torno de 0,90, com bias e erro médio quadrático de, respectivamente, aproximadamente 0,20 cm e 1,5 c/s. Os resultados indicam que o desempenho na região intertropical é similar aos resultados obtidos empregando medições globais, que são altamente concentradas em altas latitudes no Hemisfério Norte. O efeito da condição do estado de mar para extração de SWH e u10, caso seja importante, não aparenta ser considerável no conjunto de dados aqui empregado. Portanto, os resultados apontam para um desempenho bastante aceitável de tais algoritmos quando empregados na região intertropical.Palavras-chave: altura significativa de ondas, intensidade do vento, altimetria, Jason-2, ENVISAT.

Relative Motion During Single Blade Installation: Measurements From the North Sea

2020 ◽  
Author(s):  
Aljoscha Sander ◽  
Andreas F. Haselsteiner ◽  
Kader Barat ◽  
Michael Janssen ◽  
Stephan Oelker ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
North Sea ◽  
Relative Motion ◽  
Significant Wave Height ◽  
Offshore Wind ◽  
Wave Excitation ◽  
Significant Wave ◽  
The North ◽  
The North Sea

Abstract During single blade installation in offshore wind farms, relative motion between nacelle and blade root due to wind and wave excitation pose a significant challenge. Wave excitation can be modelled considerably well by employing state-of-the-art simulation tools and can, therefore, be included in installation planning. Other phenomena, such as flow-induced vibrations are hard to capture and hence challenging to account for when defining installation procedures and limitations. Here, we present measurements conducted during the installation of an offshore wind farm consisting of multi-megawatt turbines installed on monopile foundations in the North Sea. A custom-built sensor capturing linear & angular acceleration and GPS-data was deployed atop the nacelle. Both partially and fully assembled turbines displayed complex oscillation orbits, swiftly changing amplitude and direction. Mean nacelle deflection correlated strongly with significant wave height as well as mean wind speed. As wind speed and significant wave height showed a strong correlation as well, it is difficult to discern which load drives the observed relative motions. While wind loads are significantly smaller than wave loads on partially assembled turbines under installation conditions, additional momentum induced by vortex shedding may prove sufficient to cause the observed effects.

Global Hierarchical Models for Wind and Wave Contours: Physical Interpretations of the Dependence Functions

2020 ◽  
Author(s):  
Andreas F. Haselsteiner ◽  
Aljoscha Sander ◽  
Jan-Hendrik Ohlendorf ◽  
Klaus-Dieter Thoben
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
Hierarchical Models ◽  
Significant Wave Height ◽  
Joint Distribution ◽  
Environmental Data ◽  
Contour Method ◽  
Dependence Function ◽  
Significant Wave ◽  
Estimated Parameters

Abstract Applications such as the design of offshore wind turbines requires the estimation of the joint distribution of variables like wind speed, wave height and wave period. The joint distribution can then be used, for example, to define design load cases using the environmental contour method. Often the joint distribution is described using so-called global hierarchical models. In these models, one variable is taken as independent and the other variables are modelled to be conditional on this variable using particular dependence functions. In this paper, we propose to use dependence functions that offer physical interpretation. We define a novel dependence function that describes how the median of the zero-up-crossing period increases with significant wave height and a novel dependence function that describes how the median significant wave height increases with wind speed. These dependence functions allow us to reason about the physical meaning, even when we extrapolate outside the range of a given sample of environmental data. In addition, we can analyze the estimated parameters of the dependence function to speculate which kind of sea dominates at a given site. We fitted statistical models with the proposed dependence functions to six datasets and analyzed the estimated parameters. Then we calculated environmental contours based on these estimated joint distributions. The environmental contours had physically reasonable shapes, even at areas that were outside the datasets that were used to fit the underlying distributions.

scholarly journals Prediction of the wave power in the Black Sea based on wind speed using artificial neural networks

2018 ◽  
Vol 51 ◽  
pp. 01006
Author(s):  
Sorin Ciortan ◽  
Eugen Rusu
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Wind Speed ◽  
Wave Height ◽  
Black Sea ◽  
Significant Wave Height ◽  
The Black Sea ◽  
Wave Power ◽  
Significant Wave ◽  
Artificial Neural

The paper proposes a prediction methodology for the significant wave height (and implicitly the wave power), based on the artificial neural networks. The proposed approach takes as input data the wind speed values recorded for different time periods. The prediction of significant wave height is useful both for assessment of wave energy as also for marine equipment design and navigation. The data used cover the time interval 1999 to 2007 and it was measured on Gloria drilling unit, which operates in the Romanian nearshore of the Black Sea at about 500 meters depth.

scholarly journals ANFIS and ANN models for the estimation of wind and wave-induced current velocities at Joeutsu-Ogata coast

2015 ◽  
Vol 18 (2) ◽  
pp. 371-391 ◽  
Author(s):  
Morteza Zanganeh ◽  
Abbas Yeganeh-Bakhtiary ◽  
Takao Yamashita
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
Water Depth ◽  
Incident Wave ◽  
Wind Direction ◽  
Significant Wave Height ◽  
Wave Period ◽  
Inference System ◽  
Significant Wave ◽  
Wave Induced

In this study, the adaptive network-based fuzzy inference system (ANFIS) and artificial neural network (ANN) were employed to estimate the wind- and wave-induced coastal current velocities. The collected data at the Joeutsu-Ogata coast of the Japan Sea were used to develop the models. In the models, significant wave height, wave period, wind direction, water depth, incident wave angle, and wind speed were considered as the input variables; and longshore and cross-shore current velocities as the output variables. The comparison of the models showed that the ANN model outperforms the ANFIS model. In addition, evaluation of the models versus the multiple linear regression and multiple nonlinear regression with power functions models indicated their acceptable accuracy. A sensitivity test proved the stronger effects of wind speed and wind direction on longshore current velocities. In addition, this test showed great effects of significant wave height on cross-shore currents' velocities. It was concluded that the angle of incident wave, water depth, and significant wave period had weaker influences on the velocity of coastal currents.

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