A nested-grid ocean circulation modelling system (NGMS-swYS) is used for examining the impact of tides and winds on the three-dimensional (3D) circulation, hydrography and seasonal variability over the southwestern Yellow Sea (swYS). The modelling system is based on the Princeton Ocean Model (POM) and uses a nested-grid setup, with a fine-resolution (~2.7 km) inner model nested inside a coarse-resolution (~9.0 km) outer model. The domain of the outer model covers the China Seas and adjacent deep ocean waters. The domain of the fine-resolution inner model covers the swYS and adjacent waters. The NGMS-swYS is driven by a suite of external forcings, including the atmospheric forcing, tides, freshwater discharge and currents specified at the lateral open boundaries. A comparison of model results with observations and previous numerical studies demonstrates the satisfactory performance of the NGMS-swYS in simulating tides, seasonal mean circulation and distribution of temperature and salinity. Five additional numerical experiments were conducted using NGMS-swYS with different combinations of external forcing. Analysis of model results demonstrates that the monthly mean circulation over the swYS is affected significantly by tides and winds, with large seasonal variability. The northward Subei Shoal Current occurred in both winter and summer months in 2015, with persistent strong southeastward mean currents induced by tides along the 50 m isobath. Model results also demonstrated that strong wind-induced currents occurred with large sea surface cooling during Typhoon Chan-Hom.

A joint distribution of significant wave heights ($H_s$) and peak wave periods ($T_p$) in the northwestern South China Sea is created using a conditional distribution model in this work. An unstructured triangular mesh wave model covering the northwestern South China Sea is established based on the third-generation spectral wave model SWAN. This wave model has been extensively validated against field data and was run from 1979 to 2020 to generate long enough one-hourly $H_s$ and $T_p$. Four probability density functions including Normal, Lognormal, Gamma and 3P Weibull distributions are adopted to construct the marginal independent distribution of $H_s$. The results show that the 3P Weibull distribution is more suitable in fitting the marginal distribution of $H_s$ compared to the other three distributions. Three combinations of dependence functions ($\mu \mathrm{and} \sigma$), namely, power3 and exp3, insquare2 and asymdecrease3, and logistics4 and alpha3, are used to create the Normal and Lognormal distributions for $T_p$. The estimations of dependence functions and corresponding fitted $T_p$ demonstrate that the $\mu \mathrm{and} \sigma$ using power3 and exp3 perform best in producing the conditional distribution of $T_p$. In addition, the environmental contours derived by an IFORM are used to generate the extreme sea states with return periods of 1, 5, 10, 25, 50 and 100 years.