Accurate wave prediction can help avoid disasters. In this study, the significant wave height (SWH) prediction performances of the recurrent neural network (RNN), long short-term memory network (LSTM), and gated recurrent unit network (GRU) were compared. The 10 m u-component of wind (U10), 10 m v-component of wind (V10), and SWH of the previous 24 h were used as input parameters to predict the SWHs of the future 1, 3, 6, 12, and 24 h. The SWH prediction model was established at three different sites located in the Bohai Sea, the East China Sea, and the South China Sea, separately. The experimental results show that the performance of LSTM and GRU networks based on the gating mechanism was better than that of traditional RNNs, and the performances of the LSTM and GRU networks were comparable. The EMD method was found to be useful in the improvement of the LSTM network to forecast the significant wave heights of 12 and 24 h.

A comparative study was conducted on typhoon intensity factors affecting the marine environment using two representative cases: Typhoon Lekima, which made landfall at Shandong Peninsula, the Northern East China Sea, and Typhoon Muifa, which did not. Using the ADCIRC and SWAN models, we developed a coupled numerical model and applied it to simulate the storm surge and destructive waves caused by typhoons. Three typhoon parameters—maximum wind speed, radius of maximum wind speed, and translation speed—were investigated through sensitivity experiments. The storm surge during the typhoon that made landfall showed a positive correlation with the distance of the typhoon’s center. The maximum significant wave height and storm surge had near-linear growth with a maximum wind speed but decreased with the growth rate of the radius of maximum wind. A rapid typhoon translation speed from 47 km/h to 60 km/h could cause a storm surge resonance phenomenon at the northern coast of the East China Sea.

The Yellow Sea cold water mass (YSCWM) occupies a wide region below the Yellow Sea (YS) thermocline in summer which is the most conservative water and may contain clearer climate signals than any other water masses in the YS. This study investigated the low-frequency variability of the southern YSCWM (SYSCWM) and established the “forcing mechanism bridge” using correlation analysis and singular value decomposition. On the interannual timescale, the southern oscillation can affect the SYSCWM through both the local winter monsoon (WM) and the sea surface net heat flux. On the decadal timescale, the Pacific decadal oscillation (PDO) can affect the SYSCWM via two “bridges”. First, the PDO affects the SYSCWM intensity by Aleutian low (AL), WM, and surface air temperature (SAT). Second, the PDO affects the SYSCWM by AL, WM, Kuroshio heat transport, and Yellow Sea warm current. The Arctic oscillation (AO) affects the SYSCWM by the Mongolian high, WM, and SAT. Before and after the 1980s, the consistent phase change of the PDO and the AO contributed to the significant decadal variability of the SYSCWM. Finally, one simple formula for predicting the decadal variability of SYSCWM intensity was established using key influencing factors.

Storm surges and disastrous waves induced by cold air outbreaks, a type of severe weather system, often impact the coastal economic development. Using the Climate Forecast System Reanalysis wind product and the Coupled Ocean–Atmosphere–Wave–Sediment Transport model, we developed a coupled numerical model and applied it to examine the interaction between surface gravity waves and ocean currents during cold air outbreaks in two case studies in the northern East China Sea. The results revealed that wave–current interactions improved the simulation accuracy, especially the water level, as verified by tidal station measurements. We conducted sensitivity experiments to explore the spatiotemporal variation of the impact of wave–current interactions on storm surges and waves in the northern East China Sea, away from the coastline. The wave-induced surge (up to 0.4 m) and the wave-induced current (up to 0.5 m/s) were found to be related to the difference between wave direction and current direction. The significant wave height difference (up to 0.5 m) was sensitive to the storm surge nearshore and sensitive to the current field offshore, while the mean wave direction change (up to 40°) was more sensitive to the current field than to the storm surge. Additionally, the wave–current interaction regulated the momentum balance and wave action balance, respectively. By comparison, the momentum residuals of pressure gradient, Coriolis force, Coriolis–Stokes force, and bottom stress, which were pronounced in different areas, were modulated more significantly by the wave effect than other terms. The dominant mechanisms of wave–current interactions on waves included the current-induced modification of energy generation caused by wind input, the current-induced modification of energy dissipation caused by whitecapping, and the current-induced wave advection.

Effective risk assessment can reduce the economic losses and physical damage caused by marine dynamic processes, such as storm surges. Most risk assessments of marine disasters are based on regional parameters and discrete hazard grades. Targeted, multilevel, and multiangle risk assessments are urgently needed. This study focuses on specific types of affected infrastructure. We established a sensitivity matrix by considering the effects of different disaster causal factors on different types of affected infrastructure. Through this matrix, hazards, vulnerability, and emergency response and recovery capability were effectively combined in a risk assessment framework. We completed the risk calculation for multiple concurrent effects of disasters in areas with superimposed key infrastructure using complementary risk superposition. The hazard grade, vulnerability grade, and coefficient of emergency response and recovery capability were established based on the means of return period, characteristics of disaster distribution, types of affected infrastructure and disaster relief distance, and were continuous by solving functions, normal cumulative distributions, and analytic functions. On the basis of reasonable MIKE21 numerical simulation and abstract spatial distribution of vulnerable assets, we tested the rationality of the assessment system in the Lekima typhoon storm surge process. The results showed that the assessment system accurately reflected the risk of damage to the important infrastructure in terms of spatial distribution. Therefore, this risk assessment framework was suitable for the assessment of a marine dynamic disaster process in the lower Laizhou Bay coastal area of the Bohai Sea, China. Moreover, it provided a reference for disaster prevention and reduction, guided the way for decision making, and effectively reduced disaster losses.