## 4 Results and Discussion
### WST Comparison  
There are two sets of data used in this study: the BMT global statistic WST (hereafter BGW) [5] and the WST developed from the Australian hindcast model (hereafter AHD). In addition, we have the standard WST recommended in the SGISC interim guidelines [1], which is similar to the BGW data as it originated from BGW [8]. Figure 1 shows the standard WST recommended by the SGISC. Figures 4-6 show the WST developed with hindcast mean, wind and swell sea data for the standard WST region (sea areas, 8, 9, 15 and 16, further referred together as sea area S). All WST images are normalised for comparison. Figure 4: Hindcast WST for mean sea (sea area S—full year). Figure 5: Hindcast WST for wind sea (sea area S—full year). Figure 6: Hindcast WST for swell sea (sea area S—full year). Figure 7 shows the pdf of the standard WST provided in the SGISC, along with the associated Rayleigh pdf, and Figure 8 shows the same for sea area S using the AHD mean sea state. It is evident from Figures 7 and 8 that the AHD mean sea pdf and standard WST pdf in the SGISC are almost similar for the sea area S. Additionally, the Rayleigh shape parameter for individual sea areas and sea area S is estimated using BGW, AHD mean sea, AHD wind sea and AHD swell sea data and are provided for comparison in Table 4. The statistical comparison of Table 4 is provided in Table 5. It is clear that the BGW has the highest mean shape parameter followed by AHD mean, AHD wind and AHD swell (Table 5). This shows that the assessed sea areas are wind dominant rather than swell dominant, and the trend of the sea state across all sea areas is the same, as the standard deviation is small. Hence, the evaluation of the SGISC with the standard WST is acceptable for all regions considered. Figure 9 shows the AHD swell sea state pdf, an example of a lower Rayleigh shape parameter. Similarly, for all sea areas, the seasonal WST was compared using the same technique. For this discussion, the AHD mean sea data were considered. Table 6 shows the Rayleigh shape factor comparison of WSTs for seasons 1 to 4. The statistical comparison of Table 6 is provided in Table 7, which shows that the mean Rayleigh shape factor varies over the seasons, with the highest value in season 4 and the lowest in season 2. The percentage change in the shape factor with respect to the average shape parameter of the standard WST recommended by IMO (S%) is provided in Table 7. The percentage change (S%) shows the deviation in the shape parameter for the seasonal WST from the IMO recommended standard WST shape parameter estimated in Table 5. The highest shape factor for the sea area is observed in sea area 9 for season 4, which is 49% higher than standard WST (Table 6 and Figure 10). This shows that the sea area S goes through different wave profiles during each season. The effect would be much greater if the analysis was carried out on monthly intervals instead of being seasonal. The higher shape factor for season 4 indicates that the WST of season 4 has a higher probability of occurrence for larger wave heights  
Figure 7: Plots of standard WST pdf. compared to other seasons. It is clear that in Figure 10, the peak significant wave height has increased and moved to 5 m from 3 m when comparing with Figure 7. This illustrates a significant difference among seasonal WST; hence, merging seasonal and regional sea areas will result in an inaccurate depiction of the sea profile for SGISC application. Thus, the SGISC estimation using the seasonal WST must be carried out to understand the significance of the probability of wave occurrence in different seasons. The following section is the case study of using the seasonal WST for excessive acceleration estimation. Since the standard WST is modified to the seasonal WST, the following is an example of seasonal and regional operational limitation estimates for the excessive acceleration using vulnerability criteria one.