## 5 Discussion  
For the proposal briefly outlined in the four steps of the previous section, it is noted that for step (1) the \(T_{\text{-}yr}\) values of \(H\!s\) are related to the GEV model, but any projected return level of the significant wave height available to the designer could be useful, at least as an approximation. Also, since for any given \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline  & \multicolumn{4}{c}{**For Equations (8) and (12)**} & \multicolumn{4}{c}{**For Equations (10) and (11)**} \\ \cline{2-9}
**Month** & \({}^{1}\)_b_ & \(\alpha\) & \(\sigma_{e}\) & \(\varepsilon_{V}\)(\%)_ & \(b\) & \(\alpha\) & \(\sigma_{e}\) & \(\varepsilon_{V}\)(\%)_ \\ \hline January & 6.3130 & 0.5050 & 0.1323 & 12.6 & 6.0266 & 1.6565 & 1.8380 & 9.4 \\ February & 4.6311 & 0.7332 & 0.1448 & 0.48 & 4.4597 & 2.0891 & 1.7735 & 0.73 \\ March & 6.2270 & 0.5223 & 0.1692 & 6.92 & 6.5585 & 1.5731 & 2.0592 & 5.87 \\ April & 4.7280 & 0.7117 & 0.1757 & 0.16 & 3.914 & 2.1898 & 1.7927 & 0.44 \\ May & 4.6922 & 0.6616 & 0.4018 & 9.5 & 5.0670 & 1.5891 & 2.7234 & 13.1 \\ June & 6.3611 & 0.4104 & 0.3205 & 16.1 & 5.2639 & 1.7290 & 2.5623 & 4.2 \\ July & 6.0159 & 0.5132 & 0.4005 & 5.7 & 4.3002 & 2.3281 & 2.9474 & 18.5 \\ August & 5.5229 & 0.5648 & 0.3529 & 8.7 & 3.8972 & 2.1768 & 2.6075 & 9.3 \\ September & 4.6209 & 0.7596 & 0.2295 & 5.4 & 2.7402 & 2.6259 & 2.607 & 11.2 \\ October & 5.1243 & 0.6823 & 0.1626 & 4.7 & 3.8933 & 2.3476 & 2.0973 & 0.03 \\ November & 10.3253 & 0.1050 & 0.1742 & 34.0 & 10.5871 & 0.3736 & 1.9726 & 31.7 \\ December & 4.6688 & 0.6860 & 0.1899 & 10.1 & 3.3722 & 2.2109 & 2.2703 & 5.5 \\ \hline \hline \end{tabular} \({}^{1}\)_b = exp(\(\beta\)), where \(\beta\) is the intercept obtained from the regression in the logarithmic space.  
\end{table} 
Table 1: Fitted parameters of regression analysis for buoy 42,001 in this study considering seasonality. month selected, two options are available in step (2), namely, Equation (8) or Equation (10), the decision for the more suitable option can be based on the \(\varepsilon_{V}\) reported in Table 1, as well as on Figures 7, 10 and 11 and Figures A1-A9. Justification for considering \(H\!s\) and \(V_{w}\) for \(T_{\cdot yr}\) in step (3) as simultaneously occurring metocean variables is based not only on the correlation of recorded (observed) data, but also in checking that the correlation of projected \(H\!s\) and \(V_{w}\) for \(T_{\cdot yr}\), obtained from the time-dependent GEV models, are consistent with the trend of the observed data. Finally, the uncertainty obtained as per Equations (11) or (12) in step (4) approximately delimits all data points if \(\delta=2\) is used (confidence intervals for future values); if the uncertainty from the GEV models is to be employed as reference (perhaps considering the perpendicular embedded lines as an envelope), lower \(\delta\) values could be used, for instance \(\delta=1.5\), which would be a conservative value to delimit the uncertainty given by the GEV models. Use of Equations (11) or (12) using \(\delta\) values could be seen as factored demands like the ones used in codified design. The proposed method allows the possibility of using other metocean variables, data from other buoys and hindcast data. It could use other probabilistic models. More than two variables could be considered if multilinear regression analysis is implemented.