## 3 Extreme Value Analysis Considering Seasonality
As in a previous study [28], clear peaks approximately around the seasons of December-February and August-October, associated with cold fronts and hurricanes, respectively, are observed in Figure 1.  
To inspect whether a difference using the updated information in the present study (i.e., with data up to 2019) and that from the previous study [28] (with data up to 2012) exists, the \(T_{\text{-30}}\) values reported in [28] are also depicted in Figure 1 (dashed lines). It can be observed that inclusion of recent data points in the analysis does have an effect in the projected values, leading to a decrease in the peak \(H\)s values for hurricane and cold front seasons--more noticeable for the former--and an increase at midyear months. To further investigate the impact of selecting different time windows in the assessment of projected values associated with a given return period, two more lines are shown in Figure 1, which were computed using the oldest (dotted line) and the newest (dashed-dotted line) maximum 20 available recorded monthly data per year; selection of at least a 20 years range for the analysis is recommended to properly characterize metocean variables probabilistically [3]. There is a noticeable impact of using these different time windows to assess the \(H\)s values for \(T_{\text{-30}}\). Determining if this could be attributed to climate change is feasible, since studies in the literature [31] report that higher or lower metocean variables could be attributed to climate change, which depends on region and location, although it is important to acknowledge uncertainty in claiming any categorical trend [31]. This potential variation in wave climate could importantly impact maritime structures [31]. Future studies are desirable to further investigate this topic; nevertheless, it can be concluded that selection of different time ranges does have an impact in the projected return values of \(H\)s (and other metocean variables). Moreover, it is accepted that using more metocean data leads to more reliable extreme value analyses [2,3], but the use of less data and more recent data could lead to a higher projected return period value for some months. Consequently, future research and discussion on this issue is recommended. Figure 1: Monthly maximum and 30-yr return period values of \(H\)s using different time ranges. Figure 2 is analog to Figure 1, except that \(V_{w}\) values are shown. Less accentuated peaks can be observed for hurricane and cold front seasons in Figure 2, perhaps because not the maximum, but the companion values are employed, even though the trends are similar, at least for the updated (solid line) and previously used [28] time ranges (dashed lines). For the scope of this study, only models corresponding to the solid lines in Figures 1 and 2 are used (i.e., the whole set of available data at buoy 42,001 is considered), although projected metocean variables for other return periods are also used. The values for other return periods, used later in this study, for each month are listed in Appendix A in Tables A1 and A2 for \(H\)s and \(V_{w}\), respectively. No details in this study are given about the parameters of the GEV models as were provided in previous studies (e.g., [28]), since attention is focused on proposing a simplified approach to correlate extreme \(H\)s data and their companion \(V_{w}\) data associated with given \(T_{,yr}\) values. This is developed in the following section.