A suitable metocean hindcast database for the design of Marine energy converters

Boudière, Edwige; Maisondieu, Christophe; Ardhuin, Fabrice; Accensi, Mickaël; Pineau‐Guillou, Lucia; Lepesqueur, Jérémy

doi:10.1016/j.ijome.2013.11.010

Cited by 113 publications

(93 citation statements)

References 21 publications

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“…Peak periods (not illustrated here) ranged from 8 to 18 s (around 10 s on average). Even during "calm" periods, H S values are generally no lower than 0.8 m. Figure 2a illustrates the ability of the model of Boudière et al [35] to describe H S over the period, with a root mean square error (RMSE) of 0.24 cm and a R 2 of 0.95. Measured and modelled T S and S S are illustrated in Figure 2b Model results are compared with AWAC measurements in terms of (a) significant wave height, (b) surface temperature, (c) surface salinity, current direction ((d,e), respectively), and current intensity ((f,g), respectively).…”

Section: Hydrodynamic Validation Of the Modelmentioning

confidence: 97%

“…Initial & boundary conditions (3D velocities, temperature, salinity) GLORYS global ocean reanalysis [34] Wave (Significant height, peak period, bottom excursion and orbital velocities) WaveWatch III hindcast [35] Meteorological conditions (Atmospheric pressure, wind, temperature, relative humidity, cloud cover) ARPEGE model [36] Tide (14 components) FES2004 solution [37] River discharge (flow and SSC) Daily runoff data (French freshwater office)…”

Section: Forcing Sourcementioning

confidence: 99%

“…Regarding wave forcing, a wave hindcast database built with the WaveWatchIII (WWIII) model (realistic and validated configuration of Boudière et al [35]) enabled the computation of bottom wave-induced shear stresses (τ w in N·m −2 ). The wave-induced shear stress was computed according to the formulation of Jonsson [38], with a wave-induced friction factor determined following Soulsby et al [39].…”

Section: Forcing Sourcementioning

confidence: 99%

See 2 more Smart Citations

Modelling Fine Sediment Dynamics: Towards a Common Erosion Law for Fine Sand, Mud and Mixtures

Mengual

Hir

Cayocca

et al. 2017

Water

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This study describes the building of a common erosion law for fine sand and mud, mixed or not, in the case of a typical continental shelf environment, the Bay of Biscay shelf, characterized by slightly energetic conditions and a seabed mainly composed of fine sand and muddy sediments. A 3D realistic hydro-sedimentary model was used to assess the influence of the erosion law setting on sediment dynamics (turbidity, seabed evolution). A pure sand erosion law was applied when the mud fraction in the surficial sediment was lower than a first critical value, and a pure mud erosion law above a second critical value. Both sand and mud erosion laws are formulated similarly, with different parameters (erodibility parameter, critical shear stress and power of the excess shear stress). Several transition trends (linear or exponential) describing variations in these erosion-related parameters between the two critical mud fractions were tested. Suspended sediment concentrations obtained from simulations were compared to measurements taken on the Bay of Biscay shelf with an acoustic profiler over the entire water column. On the one hand, results show that defining an abrupt exponential transition improves model results regarding measurements. On the other hand, they underline the need to define a first critical mud fraction of 10 to 20%, corresponding to a critical clay content of 3-6%, below which pure sand erosion should be prescribed. Both conclusions agree with results of experimental studies reported in the literature mentioning a drastic change in erosion mode above a critical clay content of 2-10% in the mixture. Results also provide evidence for the importance of considering advection in this kind of validation with in situ observations, which is likely to considerably influence both water column and seabed sediment dynamics.

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Section: Hydrodynamic Validation Of the Modelmentioning

confidence: 97%

Section: Forcing Sourcementioning

confidence: 99%

Section: Forcing Sourcementioning

confidence: 99%

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Modelling Fine Sediment Dynamics: Towards a Common Erosion Law for Fine Sand, Mud and Mixtures

Mengual

Hir

Cayocca

et al. 2017

Water

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“…WW3 is used with a spatial resolution of about 1.5 km and its spectral resolution corresponds to 32 frequencies ranging from 0.0373 to 0.7159 Hz and 24 points for the propagation direction (every 15 • ). At open boundaries, WW3 is forced by 3-hourly energy spectra from the HOMERE hindcast database (Boudière et al, 2013). The atmospheric roughness length is estimated from the Charnock parameter supplied by WW3 (Eq.…”

Section: Mesonh-mars3d-wavewatch IIImentioning

confidence: 99%

SURFEX v8.0 interface with OASIS3-MCT to couple atmosphere with hydrology, ocean, waves and sea-ice models, from coastal to global scales

et al. 2017

Self Cite

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Abstract. This study presents the principles of the new coupling interface based on the SURFEX multi-surface model and the OASIS3-MCT coupler. As SURFEX can be plugged into several atmospheric models, it can be used in a wide range of applications, from global and regional coupled climate systems to high-resolution numerical weather prediction systems or very fine-scale models dedicated to process studies. The objective of this development is to build and share a common structure for the atmosphere-surface coupling of all these applications, involving on the one hand atmospheric models and on the other hand ocean, ice, hydrology, and wave models. The numerical and physical principles of SURFEX interface between the different component models are described, and the different coupled systems in which the SURFEX OASIS3-MCT-based coupling interface is already implemented are presented.

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“…This database has been performed using the numerical wave model WaveWatchIII® (WW3) version 4.09 (BOUDIERE et al, 2013). WW3 is a third generation spectral wave model based on the conservation equation for the density of wave action.…”

Section: Long Term Numerical Dataset (Ltnd)mentioning

confidence: 99%

Measure-Correlate-Predict techniques to improve long term numerical datasets: application to wave potential estimate

Kervella¹,

Demagny²,

Batifoulier³

2016

XIVèmes Journées, Toulon

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Abstract:Many long-term numerical databases (LTND) are distributed by research centers from various countries (like Previmer, NCEP, ..). These LTND usually provide integrated wave parameters which enable the computation of operational and also extreme statistics thanks to their duration (generally between 10 and 30 years). Although these LTND are validated in several places, it is rarely the case at your location of interest and therefore data extracted from a LTND doesn't necessarily offer the best results at this point. Nevertheless, it is possible to improve the results of these LTND in a "post-processing" step, ie without re-running the numerical simulations with data assimilation. This paper will present different techniques of Measure-Correlate-Predict (MCP) to improve the results of these LTND using in-situ data. Some of these techniques are then implemented to modify a long-term wave database in northern Bay of Biscay in France. The effect of this change is evaluated in terms of significant wave heights and wave peak period, and also in term of theoretical wave energy potential calculated using the deep waters and JONSWAP approximations, by comparing the obtained results with insitu measurements. A discussion is then opened on the way of propagating these local corrections and on the way of making it on larger spatial extents and on different physical types of LTND (wave, current, wind), thanks to the Metocean Analytics software (http://www. openocean.fr/en/metocean-analytics/).

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A suitable metocean hindcast database for the design of Marine energy converters

Cited by 113 publications

References 21 publications

Modelling Fine Sediment Dynamics: Towards a Common Erosion Law for Fine Sand, Mud and Mixtures

Modelling Fine Sediment Dynamics: Towards a Common Erosion Law for Fine Sand, Mud and Mixtures

SURFEX v8.0 interface with OASIS3-MCT to couple atmosphere with hydrology, ocean, waves and sea-ice models, from coastal to global scales

Measure-Correlate-Predict techniques to improve long term numerical datasets: application to wave potential estimate

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