In the storm surge model, the wind drag coefficient C_d is a critical parameter that has a great influence on the forecast of the storm surge level. In the present study, the effect of various wind drag coefficient parameterizations on the storm surge level is investigated in the Bohai Sea, Yellow Sea and East China Sea for Typhoons 7203 and 7303. Firstly, the impacts of initial values of a and b in the linear expression C_d = (a + b × U₁₀) × 10⁻³ on the pure storm surge model are evaluated based on the data assimilation method. Results indicate that when a and b (i.e., the wind drag coefficients given by Smith, Wu, Geernaert et al. and Mel et al.) are non-zeros, the performance of the model has little difference, and the result from Wu is slightly better. However, they are superior to the performance of the model adopting zero initial values. Then, we discuss the influences of diverse ways of calculating wind drag coefficients, which are inverted by data assimilation method (including both linear and constant C_d) and given in the form of linear formulas, on simulating pure storm surge level. They show that the data assimilation-based coefficients greatly exceed those of the ordinary coefficient formulas. Moreover, the wind drag coefficient in the linear form is a little better than that in constant form when the data assimilation method is used. Finally, the assessment of the impact of astronomical tides on the storm surge level is conducted, and the simulation demonstrates that the storm surge model, which has the combination of four constituents (M₂, S₂, K₁, O₁) and wind drag coefficient inverted by the data assimilation method with the linear C_d, exhibits the best performance.

The wind stress drag coefficient plays an important role in storm surge models. This study reveals the influences of wind stress drag coefficients, which are given in form of formulas and inverted by the data assimilation method, on the storm surge levels in the Bohai Sea, Yellow Sea, and East China Sea during Typhoon 7008. In the process of data assimilation, the drag coefficient is based on the linear expression C_d = (a + b × U₁₀) × 10⁻³ (generally speaking, a and b are empirical parameters determined by observed data). The results showed that the performance of the data assimilation method was far superior to those of drag coefficient formulas. Additionally, the simulated storm surge levels obviously changed in the neighborhood of typhoon eye. Furthermore, the effect of initial values of a and b in the C_d expression on the storm surge levels was also investigated when employing the data assimilation method. The results indicated that the simulation of storm surge level was the closest to the observation when a and b were simultaneously equal to zero, whereas the simulations had slight differences when the initial values of a and b were separately equal to the drag coefficients from the work of Smith, Wu, and Geernaert et al.. Therefore, we should choose appropriate initial values for a and b by using the data assimilation method. As a whole, the data assimilation method is much better than drag coefficient parameterization formulas in the simulation of storm surges.

The water exchange capacity (WEC) in semi-enclosed bays is influenced by various dynamical processes. Among them, the wave effects are important and yet not well-understood. In this study, the Dalian Bay, a typical coastal semi-enclosed bay located in northeastern China, was chosen as an example, and the finite volume community ocean model (FVCOM) coupled with a wave module has been employed to investigate the wave effects on WEC in the Dalian Bay in the summer. The Dalian Bay is composed by three small-sized inner bays, Tianshuitao (TST), Hongtuduizi (HTDZ) and Choushuitao (CST), as well as the central part of the Dalian Bay (CPDB). The model performance has been evaluated comprehensively by comparing a suite of quantitative metrics, procedures and spatiotemporal patterns between the simulated results and time series current and wave measurements. The simulated results well-reproduced the observations, justifying the model’s ability in reproducing the hydrodynamics of the research region. The model results and observation all indicated that the averaged current velocities in the Dalian Bay were increased by about 0.1–0.2 m/s under wave effects during one strong wave event. Especially in the TST, the current velocities were increased most significantly. Moreover, dyed tracer experiments have been conducted to investigate the wave effects on WEC, and half-life time of different subregions of the Dalian Bay were also calculated. The results showed regional differences in wave effects. Overall, the impacts of waves were more significant in the northern part of the Dalian Bay. In the summer, southeast winds prevail, which generate waves in the southeast directions. Facilitated by regional geographical settings, waves could reach the northern part directly, which reduced the dyed tracer concentrations substantially, signifying a stronger WEC. Therefore, waves exerted the greatest impacts on the TST and reduced the local half-life time by about 10–20 days through increasing the efficiency of material transports. And the half-life time of the HTDZ, when considering the wave effects, was reduced by 15 days. However, confined by the twisting coastline, the wave effects on WEC in the CPDB and the CST were not that distinguished compared to the other parts of the bay.

Changes in the climate system over recent decades have had profound impacts on the mean state and variability of ocean circulation, while the Nordic Sea overflow has remained stable in volume transport during the last two decades. The changes of the overflow flux depend on the pressure difference at the depth of the overflow outlet on both sides of the Greenland-Scotland Ridge (GSR). Combining satellite altimeter data and the reanalysis hydrological data, the analysis found that the barotropic pressure difference and baroclinic pressure difference on both sides of the GSR had a good negative correlation from 1993 to 2015. Both are caused by changes in the properties of the upper water, and the total pressure difference has no trend change. The weakening of deep convection can only change the temperature and salt structure of the Nordic Sea, but cannot reduce the mass of the water column. Therefore, the stable pressure difference drives a stable overflow. The overflow water storage in the Nordic Sea is decreasing, which may be caused by the reduction of local overflow water production and the constant overflow flux. When the upper interface of the overflow water body in the Nordic Sea is close to or below the outlet depth, the overflow is likely to greatly slow down or even experience a hiatus in the future, which deserves more attention.