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).

scholarly journals Wave Energy Assessment in the Bohai Sea and the Yellow Sea Based on a 40-Year Hindcast

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2087
Author(s):  
Jie Dong ◽  
Jian Shi ◽  
Jianchun Zhao ◽  
Chi Zhang ◽  
Haiyan Xu
Keyword(s):  
Wave Height ◽  
Wave Energy ◽  
Yellow Sea ◽  
Significant Wave Height ◽  
Bohai Sea ◽  
The Yellow Sea ◽  
Wave Power ◽  
Power Flux ◽  
Significant Wave ◽  
The Bohai Sea

A wave hindcast, covering the period of 1979–2018, was preformed to assess wave energy potential in the Bohai Sea and the Yellow Sea. The hindcase was carried out using the third generation wave model TOMAWAC with high spatio-temporal resolution (about 1 km and on an hourly basis). Results show that the mean values of significant wave height increase from north to south, and the maximum values are located at the south part of the Yellow Sea with amplitude within 1.6 m. The magnitudes of significant wave height values vary significantly within seasons; they are at a maximum in winter. The wave energy potential was represented by distributions of the wave power flux. The largest values appear in the southeast part of the numerical domain with wave power flux values of 8 kW/m. The wave power flux values are less than 2 kW/m in the Bohai Sea and nearshore areas of the Yellow Sea. The seasonal mean wave power flux was found up to 8 kW/m in the winter and autumn. To investigate the exploitable wave energy, a wave energy event was defined based on the significant wave height (Hs) threshold values of 0.5 m. The wave energy in south part of the Yellow Sea is more steady and intensive than in the other areas. Wave energy in winter is more suitable for harvesting wave energy. Long-term trends of wave power availability suggest that the values of wave power slightly decreased in the 1990s, whereas they have been increasing since 2006.

“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 Trend Detection of Wave Parameters along the Italian Seas

Water ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 1634
Author(s):  
Tommaso Caloiero ◽  
Francesco Aristodemo
Keyword(s):  
Kendall Test ◽  
Trend Detection ◽  
Wave Power ◽  
Mean Values ◽  
Significance Level ◽  
Weather Forecasts ◽  
Wave Energy Converters ◽  
Wave Parameters ◽  
Medium Range ◽  
The Mean

In this paper, trend detection of wave parameters such as significant wave height, energy period, and wave power along the Italian seas was carried out. To this purpose, wave time series in the period 1979–2018 taken from the global atmospheric reanalysis ERA-Interim by European Center for Medium-Range Weather Forecasts (ECMWF) were considered. Choosing a significance level equal to 90%, the use of the Mann–Kendall test allowed estimating ongoing trends on the mean values evaluated at yearly and seasonal scale. Furthermore, the assessment of the magnitude of the increase/decrease of the wave parameters was performed through the Theil–Sen estimator. The obtained results underlined that the mean values of the considered wave parameters were characterized by a high occurrence of positive trends in the different Italian seas. The findings of this study could have implications for studies of coastal flooding, shoreline variations, and port operations, and for the assessment of the performances of Wave Energy Converters.

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 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.

Advanced Altimeter Interferometry for Modelling the Wave Pattern Impacts of MH370 Flaperon

2020 ◽  
pp. 226-250
Keyword(s):  
Indian Ocean ◽  
Wave Height ◽  
Significant Wave Height ◽  
Wave Pattern ◽  
Wave Power ◽  
The Novel ◽  
M Wave ◽  
Significant Wave ◽  
Novel Approach ◽  
The Indian Ocean

Previous studies investigated the Indian Ocean's currents' impacts on the trajectory movement of MH370 debris. This chapter introduces the novel approach of investigating the wave pattern variations in the Indian Ocean on the MH370 debris. The novel approach based on the altimeter interferometry technique is utilized in this chapter. To this end, dual SIRAL instruments on-board of CryoSat-2 are applied to obtain the annual cycle of significant wave height across the Indian Ocean. In this chapter, in a one-year significant wave height cycle, the swell remains propagating from the Southwest to the Northeast from January to March 2015 with a maximum significant wave height of 5 m in the Northeast Offshore Australian Shelf and 7 m significant wave height Southwest of Australian Shelf. In this circumstance, the Pareto algorithm proves that the flaperon would submerge to a water depth less than 300 m on account of the impact of wave power of 22000 KJ/m/wave. It can be said that the flaperon would be submerged further to a water depth of 1000 m because of the wave power of 30000 KJ/m/wave.

Wave Power Statistics for Sea States

2011 ◽  
Vol 133 (4) ◽  
Author(s):  
Dag Myrhaug ◽  
Bernt J. Leira ◽  
Håvard Holm
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Wave Climate ◽  
Bivariate Distribution ◽  
Wave Power ◽  
Power Devices ◽  
Characteristic Wave ◽  
Significant Wave ◽  
Wave Power Potential

This paper provides a bivariate distribution of wave power and significant wave height, as well as a bivariate distribution of wave power and a characteristic wave period for sea states, and the statistical aspects of wave power for sea states are discussed. This is relevant for, e.g., making assessments of wave power devices and their potential for converting energy from waves. The results can be applied to compare systematically the wave power potential at different locations based on long term statistical description of the wave climate.

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