Extremewave 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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ftuncampaniairis:oai:iris.unicampania.it:11591/412387 2024-04-14T08:15:52+00:00 Extremewave analysis by integrating model and wave buoy data Dentale F. Furcolo P. Carratelli E. P. Reale F. Contestabile P. Tomasicchio G. R. Dentale, F. Furcolo, P. Carratelli, E. P. Reale, F. Contestabile, P. Tomasicchio, G. R. 2018 http://hdl.handle.net/11591/412387 https://doi.org/10.3390/w10040373 http://www.mdpi.com/2073-4441/10/4/373/pdf eng eng info:eu-repo/semantics/altIdentifier/wos/WOS:000434954900027 volume:10 issue:4 firstpage:373 journal:WATER http://hdl.handle.net/11591/412387 doi:10.3390/w10040373 info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85044362596 http://www.mdpi.com/2073-4441/10/4/373/pdf Gulf of Mexico Mediterranean Sea North Atlantic Spanish coast Small scale storm variation Wave extreme event Wave modeling info:eu-repo/semantics/article 2018 ftuncampaniairis https://doi.org/10.3390/w10040373 2024-03-21T16:14:41Z 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 Università degli Studi della Campania "Luigi Vanvitelli": CINECA IRIS V: Water 10 4 373 |
institution |
Open Polar |
collection |
Università degli Studi della Campania "Luigi Vanvitelli": CINECA IRIS V: |
op_collection_id |
ftuncampaniairis |
language |
English |
topic |
Gulf of Mexico Mediterranean Sea North Atlantic Spanish coast Small scale storm variation Wave extreme event Wave modeling |
spellingShingle |
Gulf of Mexico Mediterranean Sea North Atlantic Spanish coast Small scale storm variation Wave extreme event Wave modeling Dentale F. Furcolo P. Carratelli E. P. Reale F. Contestabile P. Tomasicchio G. R. Extremewave analysis by integrating model and wave buoy data |
topic_facet |
Gulf of Mexico Mediterranean Sea North Atlantic Spanish coast Small scale storm variation Wave extreme event Wave modeling |
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. |
author2 |
Dentale, F. Furcolo, P. Carratelli, E. P. Reale, F. Contestabile, P. Tomasicchio, G. R. |
format |
Article in Journal/Newspaper |
author |
Dentale F. Furcolo P. Carratelli E. P. Reale F. Contestabile P. Tomasicchio G. R. |
author_facet |
Dentale F. Furcolo P. Carratelli E. P. Reale F. Contestabile P. Tomasicchio G. R. |
author_sort |
Dentale F. |
title |
Extremewave analysis by integrating model and wave buoy data |
title_short |
Extremewave analysis by integrating model and wave buoy data |
title_full |
Extremewave analysis by integrating model and wave buoy data |
title_fullStr |
Extremewave analysis by integrating model and wave buoy data |
title_full_unstemmed |
Extremewave analysis by integrating model and wave buoy data |
title_sort |
extremewave analysis by integrating model and wave buoy data |
publishDate |
2018 |
url |
http://hdl.handle.net/11591/412387 https://doi.org/10.3390/w10040373 http://www.mdpi.com/2073-4441/10/4/373/pdf |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_relation |
info:eu-repo/semantics/altIdentifier/wos/WOS:000434954900027 volume:10 issue:4 firstpage:373 journal:WATER http://hdl.handle.net/11591/412387 doi:10.3390/w10040373 info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85044362596 http://www.mdpi.com/2073-4441/10/4/373/pdf |
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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1796314344295759872 |