Ocean wave modes in the South Atlantic by a short-scale
                        simulation

Parise, Cláudia Klose; Farina, Leandro

doi:10.3402/tellusa.v64i0.17362

Cited by 12 publications

(6 citation statements)

References 23 publications

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“…Several studies in recent decades have focused on the historical trends of wind and wave climate over the global oceans (Cox & Swail, 2001;Gulev & Grigorieva, 2004;Stopa et al, 2013;Young, 1999;Young et al, 2011). At the regional scale, particularly in the North Atlantic and North Pacific (NP), the ocean wind and wave climate has also been investigated extensively (Allan & Komar, 2000;Appendini et al, 2014;Carter & Draper, 1988;Parise & Farina, 2012;Vanem & Walker, 2013;Wang et al, 2009;Wang & Swail, 2001;Wang & Swail, 2006). In the Indian Ocean (IO), wave statistics for visually reported data were examined by Sundar (1986) for the southeast coast of India over a 10-year period, and for ship-reported wave data by Chandramohan et al (1991) around the Indian coast for a 19-year period.…”

Section: Introductionmentioning

confidence: 99%

Influence of Natural Climate Variability on the Extreme Ocean Surface Wave Heights Over the Indian Ocean

et al. 2019

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Extreme ocean waves are part of the climate system but responsible for significant impacts on coastal and offshore environments, structures, and populations. In the Indian Ocean (IO), the wind and wave climate can be significantly influenced by natural climate variability, such as the El Niño–Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and Southern Annular Mode (SAM), yet our understanding on their regional influence is limited, particularly for seasonal extremes. Here, seasonal extreme significant wave heights (SWHs) and winds in the IO are examined over the period 1957–2010 utilizing ERA‐20C reanalysis data and the nonstationary generalized extreme value distribution to understand climatic extremes, by considering climate indices as covariates. ENSO influence on extreme SWHs include increases in the Bay of Bengal, southwest tropical IO (TIO), southern IO (SIO; a broad extension south of Australia), and South China and Philippine (SCP) Seas, and decreases in the Arabian Sea in boreal summer during El Niño. Extreme SWH responses to the IOD include increases in the eastern TIO, southwest TIO, and SIO in boreal autumn during its positive phase. Lastly, Southern Annular Mode not only significantly affects the SIO year round but has a weak influence in the northern and tropical IO. Composite analysis of ENSO and IOD events further highlight in phase combinations display less significant influence than out of phase combinations during summer, but not autumn. Mean and extreme wind responses are consistent with SWH responses to natural climate variability, and climate mode teleconnection patterns help explain the seasonal variations.

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Section: Introductionmentioning

confidence: 99%

Influence of Natural Climate Variability on the Extreme Ocean Surface Wave Heights Over the Indian Ocean

et al. 2019

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“…Many regional studies have been conducted on the change in wave climate, especially in the North Pacific and North Atlantic regions (Carter and Draper 1988;Allan and Komar 2000;Caires and Swail 2004;Gulev and Grigorieva 2004;Parise and Farina 2012;Vanem and Walker 2013). Simmonds and Keay (2002) observed that the increase in wave height in the North Atlantic and North Pacific is due to the increase in cyclone numbers and the corresponding increase in the mean rate of mechanical energy input into the oceans.…”

Section: Introductionmentioning

confidence: 99%

Surface Wave Climatology and Its Variability in the North Indian Ocean Based on ERA-Interim Reanalysis

Anoop

Kumar

Shanas

et al. 2015

Journal of Atmospheric and Oceanic Technology

104

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The climate over the north Indian Ocean (NIO) is one of the most dynamic in the world because of seasonally reversing monsoon winds. In this study, the climate of the NIO and the variability of its surface waves using the European Centre for Medium-Range Weather Forecasts (ECMWF) global atmospheric reanalysis product (ERA-Interim) for the period 1979–2012 are analyzed. Annual average significant wave height (SWH) of the NIO ranges from 1.5 to 2.5 m and the seasonal average is highest (3–3.5 m) during the monsoon period [June–September (JJAS)]. Swells propagating from the Southern Hemisphere are present in the NIO during the premonsoon [February–May (FMAM)] and postmonsoon [October–January (ONDJ)] periods. The waves are separated into wind seas and swells based on the wave energy statistical method. The results show that the NIO is swell dominated and that wind sea heights are lower compared to the swell heights. Higher wind sea and swell heights are observed during the monsoon in the western NIO because of strong cross-equatorial winds of the Somali (Findlater) jet. In the postmonsoon period, the eastern NIO shows a higher swell height than the western NIO shows. SWH shows an annual increasing trend in the western NIO. On a seasonal scale, the trends are increasing significantly in the monsoon compared to the postmonsoon period in a major part of the NIO, whereas the premonsoon period shows a decline in SWH. In the NIO, the monsoon is the dominant mode of variability and it covers 92% of the total variability. Wave climate is also influenced by the annual and interannual variability in monsoon wind and rainfall.

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“…The MCA identifies the linear combinations of the original fields which lead to maximum covariance between temporal expansion coefficients computed from both fields' anomalies. In previous studies found in the literature, the MCA method has been used to determine the leading coupling modes between different variables: The significant wave height and the peak period and the significant wave height and the surface wind over the Southern Atlantic [51], the sea-surface temperature and the surface wind over the Tropical Pacific [52] and the sea-surface temperature and the wind stress over the Peruvian coasts [53].…”

Section: Wind and Wave Maximum Covariance Analysismentioning

confidence: 99%

Optimal strategies of deployment of far offshore co-located wind-wave energy farms

Saenz‐Aguirre

Sáenz

Ulazia

et al. 2022

Energy Conversion and Management

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The most profitable offshore energy resources are usually found away from the coast. Nevertheless, the accessibility and grid integration in those areas are more complicated. To avoid this problematic, large scale hydrogen production is being promoted for far offshore applications. The main objective of this paper is to analyze the ability of wave energy converters to maximize hydrogen production in hybrid wind and wave far offshore farms. To that end, wind and wave resource data are obtained from ERA5 for different locations in the Atlantic ocean and a Maximum Covariance Analysis is proposed for the selection of the most representative locations. Furthermore, the suitability of different sized wave energy converters for auxiliary hydrogen production in the far offshore wind farms is also analysed. On that account, the hydrodynamic parameters of the oscillating bodies are obtained via simulations with a Boundary Element Method based code and their operation is modelled using the software tool Matlab. The combination of both methodologies enables to perform a realistic assessment of the contribution of the wave energy converters to the hydrogen generation of an hybrid energy farm, especially during those periods when the wind turbines would be stopped due to the variability of the wind. The obtained results show a considerable hydrogen generation capacity of the wave energy converters, up to 6.28% of the wind based generation, which could remarkably improve the efficiency of the far offshore farm and bring important economical profit. Wave energy converters are observed to be most profitable in those farms with low covariance between wind and waves, where the disconnection times of the wind turbines are prone to be more prolonged but the wave energy is still usable. In such cases, a maximum of 101.12 h of equivalent rated production of the wind turbine has been calculated to be recovered by the wave energy converters.

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Ocean wave modes in the South Atlantic by a short-scale simulation

Cited by 12 publications

References 23 publications

Influence of Natural Climate Variability on the Extreme Ocean Surface Wave Heights Over the Indian Ocean

Influence of Natural Climate Variability on the Extreme Ocean Surface Wave Heights Over the Indian Ocean

Surface Wave Climatology and Its Variability in the North Indian Ocean Based on ERA-Interim Reanalysis

Optimal strategies of deployment of far offshore co-located wind-wave energy farms

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