Extreme Wave Analysis Using Satellite Data

Author(s):  
Bin Li ◽  
Chris A. Fleming ◽  
P. D. Cotton
2017 ◽  
Vol 140 ◽  
pp. 79-87 ◽  
Author(s):  
Andrea Sulis ◽  
Riccardo Cozza ◽  
Antonio Annis

1994 ◽  
Vol 32 (6) ◽  
pp. 803-814 ◽  
Author(s):  
Martin Mathiesen ◽  
Yoshimi Goda ◽  
Peter J. Hawkes ◽  
Etienne Mansard ◽  
María Jesús Martín ◽  
...  
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2021 ◽  
Author(s):  
Marta Ramirez ◽  
Melisa Menendez ◽  
Guillaume Dodet

<p>The knowledge of ocean extreme wave climate is of significant importance for a number of coastal and marine activities (e.g. coastal protection, marine spatial planning, offshore engineering). This study uses the recently released Sea State CCI v1 altimeter product to analyze extreme wave climate conditions at global scale. The dataset comprises 28-years inter-calibrated and denoised significant wave height data from 10 altimeter missions.</p><p>First, a regional analysis of the available satellite information of extreme waves associated with both, tropical and extratropical cyclones, is carried out. As tropical cyclones, we analyze two intense events which affected the Florida Peninsula and Caribbean Islands: Wilma (in October 2005) and Irma (in August 2017) hurricanes. As extratropical cyclones, we focused on the extreme waves during the 2013-2014 winter season along the Atlantic European coasts. The extreme waves associated with these events are identified in the satellite dataset and are compared with in situ and high-resolution simulated data. The analysis of the satellite data during the storm tracks and its comparison against other data sources indicate that satellite data can provide added value for the analysis of extreme wave conditions that caused important coastal damages.</p><p>After assessing the quality of extreme wave data measured by altimeters from this regional analysis, we explore a method to characterize wave height return values (e.g. 50yr return period significant wave height) from the multi-mission satellite data. The method is validated through comparisons with return values estimated from long-term wave buoy records. The extreme analysis is based on monthly maxima of satellite significant wave height computed over marine areas of varying extensions and centered on a target location (e.g. the wave buoy location for comparison and validation of the method).  The extension of the areas is defined from a seasonal study of the spatial correlation and the error metrics of the satellite data against the selected coastal location. We found a threshold of 0.85 correlation as the isoline to select the satellite data subsample (i.er. larger areas to select satellite maxima are found during winter seasons). Finally, a non-stationary extreme model based on GEV distribution is applied to obtain quantiles of low probability. Outcomes from satellite data are validated against extreme estimates from buoy records.</p>


Author(s):  
Cristina Izaguirre ◽  
Fernando J. Mendez ◽  
Melisa Menendez ◽  
Alberto Luceño ◽  
Inigo J. Losada

Water ◽  
2018 ◽  
Vol 10 (4) ◽  
pp. 373 ◽  
Author(s):  
Fabio Dentale ◽  
Pierluigi Furcolo ◽  
Eugenio Pugliese Carratelli ◽  
Ferdinando Reale ◽  
Pasquale Contestabile ◽  
...  
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Author(s):  
Ryota Wada ◽  
Takuji Waseda

Abstract Accurate estimation of extreme wave condition is desired for the rational design of offshore structures, but the estimation results are known to have uncertainty from various sources. The quality and quantity of the available extreme wave data differ among ocean regions since the atmospheric causes of extreme waves are not identical. This paper provides insight into how the different extreme wave behaviors influence the uncertainty of extreme wave estimation at each location. A review of extreme waves in four regions, namely the Gulf of Mexico, North West Pacific, Adriatic Sea, and the North Sea, revealed the difference in data uncertainty, shape parameter, and frequency of occurrence. The likelihood-weighted method was introduced to quantitatively assess the impact of each parameter on the uncertainty of extreme wave analysis. Case study based on representative parameters of the Gulf of Mexico and the North Sea revealed the large epistemic uncertainty for a region dominated by tropical cyclones. The assessment conducted in this paper is unique as it evaluates the epistemic uncertainty inherited in the extreme sample data. When the epistemic uncertainty is large, such as the case illustrated for the Gulf of Mexico, the variance from different approaches may not be significant against the epistemic uncertainty inherited in the sample data.


2019 ◽  
Vol 179 ◽  
pp. 202-212 ◽  
Author(s):  
R.M. Campos ◽  
C. Guedes Soares ◽  
J.H.G.M. Alves ◽  
C.E. Parente ◽  
L.G. Guimaraes

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