It has been shown before, and it is intuitively evident, that in a Significant Wave Height (SWH) time series, the longer the sampling interval, the lower is the number of events which are above a given threshold value. As a consequence, the use of data with a low time resolution (such as a 3 h sampling, for instance) causes a considerable undervaluation of the extreme SWH values for a given return time RT. In this paper an example of such a bias is provided, and a method is suggested to estimate it on a regional basis. Results may help to improve the use of historical wave meters data which were often collected with a low time resolution, and may also provide a tool to improve the application of Numerical Meteo-Wave models to the evaluation of extremes.
Sampling bias in the estimation of significant wave height extreme values / Dentale, Fabio; Reale, Ferdinando; D'Alessandro, Felice; Damiani, Leonardo; Di Leo, Angela; Pugliese Carratelli, Eugenio; Roberto Tomasicchio, Giuseppe. - In: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON COASTAL ENGINEERING. - ISSN 2156-1028. - ELETTRONICO. - 35:(2016). (Intervento presentato al convegno 35th International Conference on Coastal Engineering, ICCE 2016 tenutosi a Antalya, Turkey nel November 17-20, 2016) [10.9753/icce.v35.waves.33].
Sampling bias in the estimation of significant wave height extreme values
Leonardo Damiani;
2016-01-01
Abstract
It has been shown before, and it is intuitively evident, that in a Significant Wave Height (SWH) time series, the longer the sampling interval, the lower is the number of events which are above a given threshold value. As a consequence, the use of data with a low time resolution (such as a 3 h sampling, for instance) causes a considerable undervaluation of the extreme SWH values for a given return time RT. In this paper an example of such a bias is provided, and a method is suggested to estimate it on a regional basis. Results may help to improve the use of historical wave meters data which were often collected with a low time resolution, and may also provide a tool to improve the application of Numerical Meteo-Wave models to the evaluation of extremes.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
