Extreme Wave Analysis by Integrating Model and Wave Buoy Data

Estimating the extreme values of significant wave height (HS), generally described by the HS return period TR function HS(TR) and by its confidence intervals, is a necessity in many branches of coastal science and engineering. The availability of indirect wave data generated by global and regional w...

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Published in:Water
Main Authors: Fabio Dentale, Pierluigi Furcolo, Eugenio Pugliese Carratelli, Ferdinando Reale, Pasquale Contestabile, Giuseppe Roberto Tomasicchio
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2018
Subjects:
Online Access:https://doi.org/10.3390/w10040373
https://doaj.org/article/5b3359c38ed6467eb241e6441036b140
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spelling ftdoajarticles:oai:doaj.org/article:5b3359c38ed6467eb241e6441036b140 2023-05-15T17:33:46+02:00 Extreme Wave Analysis by Integrating Model and Wave Buoy Data Fabio Dentale Pierluigi Furcolo Eugenio Pugliese Carratelli Ferdinando Reale Pasquale Contestabile Giuseppe Roberto Tomasicchio 2018-03-01T00:00:00Z https://doi.org/10.3390/w10040373 https://doaj.org/article/5b3359c38ed6467eb241e6441036b140 EN eng MDPI AG http://www.mdpi.com/2073-4441/10/4/373 https://doaj.org/toc/2073-4441 2073-4441 doi:10.3390/w10040373 https://doaj.org/article/5b3359c38ed6467eb241e6441036b140 Water, Vol 10, Iss 4, p 373 (2018) wave extreme events Mediterranean Sea North Atlantic Spanish coasts Gulf of Mexico wave modeling small scale storm variations Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500 article 2018 ftdoajarticles https://doi.org/10.3390/w10040373 2022-12-31T16:27:04Z Estimating the extreme values of significant wave height (HS), generally described by the HS return period TR function HS(TR) and by its confidence intervals, is a necessity in many branches of coastal science and engineering. The availability of indirect wave data generated by global and regional wind and wave model chains have brought radical changes to the estimation procedures of such probability distribution—weather and wave modeling systems are routinely run all over the world, and HS time series for each grid point are produced and published after assimilation (analysis) of the ground truth. However, while the sources of such indirect data are numerous, and generally of good quality, many aspects of their procedures are hidden to the users, who cannot evaluate the reliability and the limits of the HS(TR) deriving from such data. In order to provide a simple engineering tool to evaluate the probability of extreme sea-states as well as the quality of such estimates, we propose here a procedure based on integrating HS time series generated by model chains with those recorded by wave buoys in the same area. Article in Journal/Newspaper North Atlantic Directory of Open Access Journals: DOAJ Articles Water 10 4 373
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic wave extreme events
Mediterranean Sea
North Atlantic Spanish coasts
Gulf of Mexico
wave modeling
small scale storm variations
Hydraulic engineering
TC1-978
Water supply for domestic and industrial purposes
TD201-500
spellingShingle wave extreme events
Mediterranean Sea
North Atlantic Spanish coasts
Gulf of Mexico
wave modeling
small scale storm variations
Hydraulic engineering
TC1-978
Water supply for domestic and industrial purposes
TD201-500
Fabio Dentale
Pierluigi Furcolo
Eugenio Pugliese Carratelli
Ferdinando Reale
Pasquale Contestabile
Giuseppe Roberto Tomasicchio
Extreme Wave Analysis by Integrating Model and Wave Buoy Data
topic_facet wave extreme events
Mediterranean Sea
North Atlantic Spanish coasts
Gulf of Mexico
wave modeling
small scale storm variations
Hydraulic engineering
TC1-978
Water supply for domestic and industrial purposes
TD201-500
description Estimating the extreme values of significant wave height (HS), generally described by the HS return period TR function HS(TR) and by its confidence intervals, is a necessity in many branches of coastal science and engineering. The availability of indirect wave data generated by global and regional wind and wave model chains have brought radical changes to the estimation procedures of such probability distribution—weather and wave modeling systems are routinely run all over the world, and HS time series for each grid point are produced and published after assimilation (analysis) of the ground truth. However, while the sources of such indirect data are numerous, and generally of good quality, many aspects of their procedures are hidden to the users, who cannot evaluate the reliability and the limits of the HS(TR) deriving from such data. In order to provide a simple engineering tool to evaluate the probability of extreme sea-states as well as the quality of such estimates, we propose here a procedure based on integrating HS time series generated by model chains with those recorded by wave buoys in the same area.
format Article in Journal/Newspaper
author Fabio Dentale
Pierluigi Furcolo
Eugenio Pugliese Carratelli
Ferdinando Reale
Pasquale Contestabile
Giuseppe Roberto Tomasicchio
author_facet Fabio Dentale
Pierluigi Furcolo
Eugenio Pugliese Carratelli
Ferdinando Reale
Pasquale Contestabile
Giuseppe Roberto Tomasicchio
author_sort Fabio Dentale
title Extreme Wave Analysis by Integrating Model and Wave Buoy Data
title_short Extreme Wave Analysis by Integrating Model and Wave Buoy Data
title_full Extreme Wave Analysis by Integrating Model and Wave Buoy Data
title_fullStr Extreme Wave Analysis by Integrating Model and Wave Buoy Data
title_full_unstemmed Extreme Wave Analysis by Integrating Model and Wave Buoy Data
title_sort extreme wave analysis by integrating model and wave buoy data
publisher MDPI AG
publishDate 2018
url https://doi.org/10.3390/w10040373
https://doaj.org/article/5b3359c38ed6467eb241e6441036b140
genre North Atlantic
genre_facet North Atlantic
op_source Water, Vol 10, Iss 4, p 373 (2018)
op_relation http://www.mdpi.com/2073-4441/10/4/373
https://doaj.org/toc/2073-4441
2073-4441
doi:10.3390/w10040373
https://doaj.org/article/5b3359c38ed6467eb241e6441036b140
op_doi https://doi.org/10.3390/w10040373
container_title Water
container_volume 10
container_issue 4
container_start_page 373
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