Bivariate simulation of non stationary and non Gaussian observed processes - Application to sea state parameters

A method for artificially generating operational sea state histories has been developed. This is a distribution free method to simulate bivariate non stationary and non Gaussian random processes. This method is applied to the simulation of the bivariate process (H-s, T-p) of sea state parameters. The time series respects the physical constraints existing between the significant wave height and the peak period. Furthermore, we show that the persistence properties of the simulations match to those of the observations.

Keyword(s)

Bivariate simulation, Non Gaussian processes, Wave data, Non parametric simulation

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Monbet Valerie, Prevosto Marc (2001). Bivariate simulation of non stationary and non Gaussian observed processes - Application to sea state parameters. Applied Ocean Research. 23 (3). 139-145. https://doi.org/10.1016/S0141-1187(01)00011-6, https://archimer.ifremer.fr/doc/00000/4343/

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