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An assessment\udof extreme wave characteristics during the design of marine facilities not\udonly helps to ensure their safety but also assess the economic aspects. In\udthis study, return levels of significant wave height (Hs) for different\udperiods are estimated using the generalized extreme value distribution (GEV)\udand generalized Pareto distribution (GPD) based on the Waverider buoy data\udspanning 8 years and the ERA-Interim reanalysis data spanning 38 years. The\udanalysis is carried out for wind-sea, swell and total Hs separately for\udbuoy data. Seasonality of the prevailing wave climate is also considered in\udthe analysis to provide return levels for short-term activities in the\udlocation. The study shows that the initial distribution method (IDM)\udunderestimates return levels compared to GPD. The maximum return levels\udestimated by the GPD corresponding to 100 years are 5.10 m for the monsoon\udseason (JJAS), 2.66 m for the pre-monsoon season (FMAM) and 4.28 m for the\udpost-monsoon season (ONDJ). The intercomparison of return levels by block\udmaxima (annual, seasonal and monthly maxima) and the r-largest method for GEV\udtheory shows that the maximum return level for 100 years\udis 7.20 m in the r-largest series followed by monthly maxima (6.02 m) and\udannual maxima (AM) (5.66 m) series. The analysis is also carried out to\udunderstand the sensitivity of the number of observations for the GEV annual\udmaxima estimates. It indicates that the variations in the standard deviation\udof the series caused by changes in the number of observations are positively\udcorrelated with the return level estimates. The 100-year return level results of Hs\udusing the GEV method are comparable for short-term (2008 to 2016)\udbuoy data (4.18 m) and long-term (1979 to 2016) ERA-Interim shallow data\ud(4.39 m). The 6 h interval data tend to miss high values of Hs, and hence\udthere is a significant difference in the 100-year return level Hs obtained\udusing 6 h interval data compared to data at 0.5 h interval. The study shows\udthat a single storm can cause a large difference in the 100-year Hs value

Variations in return value estimate of ocean surface waves – a study based on measured buoy data and ERA-Interim reanalysis data