Estimation of the hundred year return level of the signiﬁcant wave height for the French Guiana coast

Osinski, Robert; Dalphinet, Alice; Aouf, Lotfi; Palany, Philippe

doi:10.1590/s1679-87592018017906604

Cited by 3 publications

(2 citation statements)

References 19 publications

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“…This is roughly 100 hPa lower than background sea level pressure, meaning Irma had the potential to trigger a one-meter storm surge from the inverse barometer effect alone, in addition to contributions from winds, currents and waves. Significant wave heights around Saint-Martin reached 10 m (over a local depth of~20 m) according to Météo-France estimates (Figure 5d) from the WaveWatchIII spectral wave model at 200 m resolution [32,33], with maximum heights exceeding 12 m. A 2-3 m storm surge was forecast by Météo-France with the Hycom2d barotropic coastal circulation model [34]. This is in reasonable agreement with the 2.04 m surge measured at the Marigot tide gauge in Saint-Martin on 6 September 2017 at 10:31 a.m. given the strong model sensitivity to hurricane track and intensity [35].…”

Section: Hurricane Characteristicsmentioning

confidence: 95%

Coastal Processes and Influence on Damage to Urban Structures during Hurricane Irma (St-Martin & St-Barthélemy, French West Indies)

Rey

Leone

Candela

et al. 2019

JMSE

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This study aims to better understand coastal processes associated with extreme cyclonic events through the study of the coastal changes, flooding and damage that resulted from the passage of a category 5 hurricane (Irma) on 6 September 2017 over the islands of Saint-Martin and Saint-Barthélemy in the Lesser Antilles. Hurricane Irma was contextualized from tropical cyclone track data and local weather observations collected by Météo-France, as well as high-resolution numerical modelling. Field work involved the study of accretion coasts through qualitative observations, topo-morphological and sedimentary surveys, as well as image acquisition with Unmanned Aerial Vehicle (UAV) surveys during two trips that were made 2 and 8 months after the catastrophe. Wave propagation and flood numerical models are presented and compared to field data. Our field analysis also reports on the devastating impacts of storm surges and waves, which reached 4 and 10 meters height, respectively, especially along east-facing shores. The approaches reveal a variety of morpho-sedimentary responses over both natural and highly urbanized coasts. The analysis shows the effects of coastal structures and streets on flow channeling, on the amplification of some erosion types, and on water level increase. Positive spatial correlation is found between damage intensity and marine flood depth. The signatures of ocean-induced damage are clear and tend to validate the relevance of the intensity scale used in this study.

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Section: Hurricane Characteristicsmentioning

confidence: 95%

Coastal Processes and Influence on Damage to Urban Structures during Hurricane Irma (St-Martin & St-Barthélemy, French West Indies)

Rey

Leone

Candela

et al. 2019

JMSE

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“…The later needs some time to travel, so that regions which are predominated by swell can be assumed to need a longer period to produce a reasonable spread with this setting. Osinski et al (2018) estimated the hundred-year return level of the significant wave height of northerly swell events at the French Guiana coast. Such events are generated in the Northern Atlantic and travel until the north-eastern coast of South America.…”

Section: Wave Fieldsmentioning

confidence: 99%

Ensemble hindcasting of wind and wave conditions with WRF and Wavewatch III<sup>®</sup> driven by ERA5

Osinski¹,

Radtke²

2019

Preprint

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Abstract. When hindcasting wave fields of storm events with state-of-the-art wave models, the quality of the results strongly depends on the meteorological forcing dataset. The wave model will inherit the uncertainty of the atmospheric data, and additional discretisation errors will be introduced due to a limited spatial and temporal resolution of the forcing data. In this study, we demonstrate that applying an atmospheric downscaling with the atmospheric mesoscale model WRF can address all these three issues. Not only does it add regional detail to the wind field and can increase the temporal resolution of the wind fields, which gives a more detailed representation of transient events such as storms. It can also be used to generate ensembles with perturbed atmospheric conditions which allow for a flow dependent and spatiotemporally variable uncertainty estimation. We test different strategies to generate an ensemble hindcast of a storm event in February 2002 in the Baltic Sea, which provoked a severe storm surge. The WRF model used for this purpose is driven by the ECMWF ERA5 reanalysis, and wind fields are passed to the third-generation wave model Wavewatch III®. A combination of initial conditions from the ERA5 ensemble of data assimilations and stochastic pertubations during runtime is identified as the most promising strategy. The final aim of the ensemble approach is to quantify the hindcast error, but this approach can also be used to generate alternative representations of historical extreme events to sample the recent climate and to increase the sample size for statistical studies, such as for civil engineering applications for coastal protection studies.

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Ensemble hindcasting of wind and wave conditions with WRF and WAVEWATCH III® driven by ERA5

Osinski

Radtke

2020

Ocean Sci.

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Abstract. When hindcasting wave fields of storm events with state-of-the-art wave models, the quality of the results strongly depends on the meteorological forcing dataset. The wave model will inherit the uncertainty of the atmospheric data, and additional discretization errors will be introduced due to a limited spatial and temporal resolution of the forcing data. In this study, we apply an atmospheric downscaling to (i) add regional details to the wind field, (ii) increase the temporal resolution of the wind fields, (iii) provide a more detailed representation of transient events such as storms and (iv) generate ensembles with perturbed atmospheric conditions, which allows for a flow-dependent and spatio-temporally variable uncertainty estimation. We test different strategies to generate an ensemble hindcast of a relatively strong storm event in February 2002 in the Baltic Sea. The Weather Research and Forecasting (WRF) model used for this purpose is driven by the ECMWF ERA5 reanalysis, and wind fields are passed to the third-generation wave model WAVEWATCH III®. A combination of initial conditions from the ERA5 ensemble of data assimilations and stochastic perturbations during runtime is identified as the most promising strategy. The final aim of the ensemble approach is to quantify the hindcast error, but this approach can also be used to generate alternative representations of historical extreme events to sample the recent climate and to increase the sample size for statistical studies, such as for civil engineering applications for coastal protection studies.

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Estimation of the hundred year return level of the signiﬁcant wave height for the French Guiana coast

Cited by 3 publications

References 19 publications

Coastal Processes and Influence on Damage to Urban Structures during Hurricane Irma (St-Martin & St-Barthélemy, French West Indies)

Coastal Processes and Influence on Damage to Urban Structures during Hurricane Irma (St-Martin & St-Barthélemy, French West Indies)

Ensemble hindcasting of wind and wave conditions with WRF and Wavewatch III<sup>®</sup> driven by ERA5

Ensemble hindcasting of wind and wave conditions with WRF and WAVEWATCH III® driven by ERA5

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Estimation of the hundred year return level of the signiﬁcant wave height for the French Guiana coast

Cited by 3 publications

References 19 publications

Coastal Processes and Influence on Damage to Urban Structures during Hurricane Irma (St-Martin & St-Barthélemy, French West Indies)

Coastal Processes and Influence on Damage to Urban Structures during Hurricane Irma (St-Martin & St-Barthélemy, French West Indies)

Ensemble hindcasting of wind and wave conditions with WRF and Wavewatch III&lt;sup&gt;®&lt;/sup&gt; driven by ERA5

Ensemble hindcasting of wind and wave conditions with WRF and WAVEWATCH III® driven by ERA5

Contact Info

Product

Resources

About

Ensemble hindcasting of wind and wave conditions with WRF and Wavewatch III<sup>®</sup> driven by ERA5