On Variability of Mean Wave Direction During Severe Storms

2014 ◽  
Author(s):  
Valentina Laface ◽  
Felice Arena ◽  
Carlos Guedes Soares
Keyword(s):  
Time Series ◽  
Standard Deviation ◽  
Atlantic Ocean ◽  
Wave Height ◽  
North Sea ◽  
Significant Wave Height ◽  
Wave Direction ◽  
Data Set ◽  
Severe Storms ◽  
Significant Wave

The paper deals with the directional analysis of severe storms in some European locations, in the Atlantic Ocean and North Sea. The analysis is carried out by considering significant wave height and wave direction time series, from the HIPOCAS project database. At each considered location, all storms in the data set are identified. Then, for each storm, variability of direction during sea states is investigated. The results of this analysis show how direction during storms varies within well-defined sectors identified from the main directions from which the strongest storms occur plus or minus a certain angle Δϑ, and from one or more secondary sectors. The variation of direction during storms is evaluated in terms of standard deviation of direction, either by considering all sea states during storm, or only sea states during the part of the storm above a fixed threshold h of significant wave height. The results show that standard deviation of direction decreases as the threshold h increases and it is due to the fact that variability of direction near the storm peak is smaller than in the full storm.

Comparison of Bivariate Models of the Distribution of Significant Wave Height and Peak Wave Period

2007 ◽  
Author(s):  
Catarina S. Soares ◽  
C. Guedes Soares
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Bivariate Normal Distribution ◽  
Wave Period ◽  
Peak Period ◽  
Data Set ◽  
Significant Wave ◽  
The North ◽  
Bivariate Models ◽  
The North Sea

This paper presents the results of a comparison of the fit of three bivariate models to a set of 14 years of significant wave height and peak wave period data from the North Sea. One of the methods defines the joint distribution from a marginal distribution of significant wave height and a set of distributions of peak period conditional on significant wave height. Other method applies the Plackett model to the data and the third one applies the Box-Cox transformation to the data in order to make it approximately normal and then fits a bivariate normal distribution to the transformed data set. It is shown that all methods provide a good fit but each one have its own strengths and weaknesses, being the choice dependent on the data available and applications in mind.

“Three Sisters” Measured As a Triple Rogue Wave Group

2019 ◽  
Author(s):  
Anne Karin Magnusson ◽  
Karsten Trulsen ◽  
Ole Johan Aarnes ◽  
Elzbieta M. Bitner-Gregersen ◽  
Mika P. Malila
Keyword(s):  
Time Series ◽  
Wave Height ◽  
Significant Wave Height ◽  
Weather Conditions ◽  
Rogue Waves ◽  
Significant Wave ◽  
Wind Sea ◽  
Propagation Methods ◽  
Non Linear Propagation ◽  
Three Sisters

Abstract On November 30, 2018, our attention was caught when analyzing wave profile time series measured by a platform mounted wave sensor (a SAAB REX radar) at Ekofisk, central North Sea. The 20-minute time series had not only one, but three consecutive waves with individual heights that all were more than twice the significant wave height, the two last of them being almost equally high with a factor 2.35 to the significant wave height of 4m (from 4σ(η), over 20 minutes). Counting three rogue waves in one sequence seems to be very rare. In this study we analyze how the shape is evolving in space and time using linear and non-linear propagation methods developed by Mark Donelan [1,2] and Karsten Trulsen [3,4]. Weather conditions and characteristics of the sea state with the ‘Three Sisters’ (named the “Justine Three Sisters”) are presented. It is found that the Three Sisters occurred in a crossing sea condition, with wind sea and swell coming from directions 60 degrees apart, with about same frequency, but very different energy.

scholarly journals Significant Wave Height Estimation from Space-Borne Cyclone-GNSS Reflectometry

2019 ◽  
Vol 11 (5) ◽  
pp. 584 ◽  
Author(s):  
Qin Peng ◽  
Shuanggen Jin
Keyword(s):  
Standard Deviation ◽  
Correlation Coefficient ◽  
Wave Height ◽  
Significant Wave Height ◽  
Satellite System ◽  
Measurement Range ◽  
Ocean Dynamics ◽  
Global Ocean ◽  
Physical Parameters ◽  
Significant Wave

The significant wave height (SWH) of the sea is an important parameter and plays an important role in the prediction of waves and ocean dynamics. However, traditional methods, e.g., buoys or traditional remote sensing techniques such as X-band radar image have small measurement range and high cost. Recently, Global Navigation Satellite System-Reflectometry (GNSS-R) has provided a new opportunity to estimate the SWH, especially the space-borne Cyclone-GNSS (CYGNSS) launched on December 15, 2016. The GNSS-R uses the GNSS-reflected signal received by the receiver to invert ground physical parameters with all-weather, global fast coverage, high resolution, high precision, high long-term stability, rich signal sources, passive detection, and strong concealment. In this paper, the global ocean significant wave height is estimated using space-borne CYGNSS GNSS-R data for the first time though the relationship between the square root of the signal-to-noise ratio (SNR) data of CYGNSS delayed Doppler map (DDM) and the SWH. Then, the estimated significant wave height is compared with the satellite altimeter and buoy data. Compared with the AVISO SWH observation, the standard deviation value reaches 0.3080 m and the correlation coefficient reaches 0.9473 m. The correlation coefficient with the buoy SWH observation is 0.9539 m and the standard deviation is 0.2761 m. The SWH estimations from CYGNSS can provide important support in ocean shipping development, marine environmental protection, marine disaster warning and forecasting.

The Reconstruction of Significant Wave Height Time Series by Using a Neural Network Approach

2004 ◽  
Vol 126 (3) ◽  
pp. 213-219 ◽  
Author(s):  
Felice Arena ◽  
Silvia Puca
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Wave Height ◽  
Significant Wave Height ◽  
Error Function ◽  
Neural Network Approach ◽  
Significant Wave ◽  
Time Periods ◽  
Weighted Error ◽  
Storm Model

A Multivariate Neural Network (MNN) algorithm is proposed for the reconstruction of significant wave height time series, without any increase of the error of the MNN output with the number of modelled data. The algorithm uses a weighted error function during the learning phase, to improve the modelling of the higher significant wave height. The ability of the MNN to reconstruct sea storms is tested by applying the equivalent triangular storm model. Finally an application to the NOAA buoys moored off California shows a good performance of the MNN algorithm, both during sea storms and calm time periods.

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.

scholarly journals Changes of Significant Wave Height, Energy Period and Wave Power in Italy in the Period 1979–2018

2020 ◽  
Vol 2 (1) ◽  
pp. 3
Author(s):  
Tommaso Caloiero ◽  
Francesco Aristodemo ◽  
Danilo Algieri Ferraro
Keyword(s):  
Time Series ◽  
Wave Height ◽  
Significant Wave Height ◽  
Kendall Test ◽  
Wave Power ◽  
Mean Values ◽  
Significant Wave ◽  
Wave Energy Converters ◽  
Long Wave ◽  
Significance Levels

An analysis of a 40-year long wave time series was performed, along the coasts of Italy, in order to identify ongoing trends of two synthetic parameters, significant wave height (Hs) and energy period (Te), and of the wave power (P). First, wave data were deduced from the global atmospheric reanalysis ERA-INTERIM by the ECMWF and checked to verify their consistency. Then, a trend analysis was performed on mean values evaluated at annual and seasonal scales through the non-parametric Mann–Kendall test for three different significance levels equal to 90%, 95% and 99%. The obtained results could be useful for analyses linked to beach morphodynamics and on the identification of field installations of Wave Energy Converters (WECs).

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