Estimation of wave period statistics using numerical coastal wave model

Abstract

We used field and model wave data to investigate that zero crossing and average wave period distribution follow Gamma distribution. Since Gamma CDF is an infinite power series, further mathematical treatment is difficult. Hence its shape parameter is approximated to the nearest integer to arrive at Erlang distribution. An expression is derived from Erlang distribution to estimate various mean wave periods and significant wave period and validated by relative root mean square (RRMS) error criteria. It is shown by mathematical logic that the significant wave period distribution follows Erlang (or Gamma) distribution and is validated. The average of one-third and one-tenth highest wave periods (T s ) estimated from Erlang distribution are in accordance with the values computed from recorded buoy and numerical coastal wave model wave period data. The predicted T s values from coastal wave model wave period data underestimates the values from buoy wave period data.

On the distribution of significant wave height and associated peak periods

“…Anyway, no attempt appeared to have been made to gauge other wave period statistics from these models. Muraleedharan et al (2009) determined m (t); the empirical average conditional exceedance of zero crossing wave periods t for a shallow water site (Valiathura, southwest coast of India, depth of recording 5.5 m) in the Arabian Sea for the month of January, 1981. The long-term data of shallow water mean zero crossing wave periods ðT z Þ off Valiathura, computed by CESS (1980CESS ( -1984 for the rough south west rainstorm seasons (May-October) were additionally considered.…”

Probabilistic modelling of linear and directional wind and wave data with applications to the marine environment

“…For instance, the operational performance of a wave energy converter depends on the wave period while its survivability on wave height. In the context of analysing these wave parameters through univariate probability models, various models have been applied, including among others the Lognormal (Athanassoulis et al, 1994;Haver, 1985), the three-parameter Weibull (Burrows and Salih, 1986;Soares and Henriques, 1996;Vanem, 2016), the Gamma (Muraleedharan et al, 2009) and the Beta distributions (Ferreira and Soares, 1999).…”