Copula-Based Joint Probability and Return-Period Analysis of Wind–Wave Conditions for Offshore Wind Applications

Reliable characterization of dependent wind–wave extremes is essential for offshore wind engineering in monsoon- and tropical-cyclone-affected seas. Using a 2002–2020 COAWST hindcast for an offshore site in the northern South China Sea, we analyze 161,400 common-valid hourly samples of 10-m wind speed (U10), significant wave height (Hs), and peak wave period (Tp) and construct 221 temporally consistent monthly extreme pairs. Validation shows that the hindcast captures temporal co-variability but systematically underestimates wind and wave magnitudes, especially severe tropical-cyclone winds and high sea states; long-return-period estimates are therefore interpreted as methodological sensitivity measures rather than design loads. SJ-DPI and upper-tail sensitivity models based on Kernel–Pareto and GEV marginals are compared to quantify extrapolation uncertainty, while the primary uncertainty interpretation avoids relying on potentially unstable far-tail fits from limited monthly extremes. Under a common maximum pseudo-likelihood framework, no copula family is uniformly optimal, and AND-type exceedance is more sensitive to dependence-family choice than OR-type exceedance. Cool- and warm-season distributions differ significantly, but a 1000-split placebo test shows that part of the apparent long-return-period shift is attributable to the smaller-sample SJ-DPI bandwidths rather than seasonality alone. These results highlight the need to jointly consider concurrent sampling, marginal-tail specification, dependence uncertainty, and seasonal heterogeneity.