The variability of the sea surface temperature (SST) in the northwest Pacific has been studied on seasonal, annual and interannual scales based on the monthly datasets of extended reconstructed sea surface temperature (ERSST) 3b (1854–2017, 164 years) and optimum interpolation sea surface temperature version 2 (OISST V2 (1988–2017, 30 years). The overall trends, spatial–temporal distribution characteristics, regional differences in seasonal trends and seasonal differences of SST in the northwest Pacific have been calculated over the past 164 years based on these datasets. In the past 164 years, the SST in the northwest Pacific has been increasing linearly year by year, with a trend of 0.033 ^∘C/10 years. The SST during the period from 1870 to 1910 is slowly decreasing and staying in the range between 25.2 and 26.0 ^∘C. During the period of 1910–1930, the SST as a whole maintained a low value, which is at the minimum of 164 years. After 1930, SST continued to increase until now. The increasing trend in the past 30 years has reached 0.132 ^∘C/10 years, and the increasing trend in the past 10 years is 0.306 ^∘C/10 years, which is around 10 times that of the past 164 years. The SST in most regions of the northwest Pacific showed a linear increasing trend year by year, and the increasing trend in the offshore region was stronger than that in the ocean and deep-sea region. The change in trend of the SST in the northwest Pacific shows a large seasonal difference, and the increasing trend in autumn and winter is larger than that in spring and summer. There are some correlations between the SST and some climate indices and atmospheric parameters; the correlations between the SST and some atmospheric parameters have been discussed, such as those of the North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO), Southern Oscillation Index (SOI) anomaly, total column water (TCW), NINO3.4 index, sea level pressure (SLP), precipitation, temperature at 2 m (T2) and wind speed. The lowest SST in China offshore basically occurred in February and the highest in August. The SST fluctuation in the Bohai Sea and Yellow Sea (BYS) is the largest, with a range from 5 to 22 ^∘C; the SST in the East China Sea (ECS) is from 18 to 27 ^∘C; the smallest fluctuations occur in the South China Sea (SCS), maintained at range of 26 to 29 ^∘C. There are large differences between the mean and standard deviation in different sea regions.

Studying the sea–air interaction between the upper ocean and typhoons is crucial to improve our understanding of heat and momentum exchange between the atmosphere and the ocean. There is a strong heat flux exchange between the atmosphere and the ocean during the impact of a typhoon, and the physical fields, such as the wind field, wave field, flow field, and SST field, also interact with each other. A fully coupled Atmosphere–Wave–Ocean model in the South China Sea was established by the mesoscale atmospheric model WRF, wave model SWAN, and the regional ocean model ROMS based on the COAWST model system. Typhoon Kai-tak was simulated using this fully coupled model and some other coupled schemes. In this paper, the variation of sea surface temperature (SST) and ocean subsurface temperature caused by Typhoon Kai-tak is analyzed by the fully coupled model, and the basic characteristics of the response of the upper ocean to the typhoon are given. The simulation results demonstrate that the fully coupled WRF-SWAN-ROMS model shows that the typhoon passes through the sea with obvious cooling. In the cold eddy region, the sea surface temperature cools 4 to 5 °C, and the cooling zone is concentrated on the right side of the track. The change of sea surface temperature lags more than 12 h behind the change of sea surface height. The decrease of SST on the left side of the track was relatively small: ranging from 1.5 to 2.5 °C. The disturbance of typhoon causes the subsurface water to surge to the surface, changes the temperature distribution of the surface, and causes the mixing layer to deepen about 40 m to 60 m. The simulation results reveal the temporal and spatial distribution of sea temperature and mixed layer depth. The sea surface temperature field has an asymmetrical distribution in space and has a lag in time. The heat exchange at the air–sea interface is very strong under the influence of the typhoon. The heat exchange between the air and sea is divided into latent heat and sensible heat, and the latent heat generated by water vapor evaporation plays a dominant role in the heat exchange at the air–sea interface, which shows that the heat carried by the vaporization of the sea surface is one of the important factors for the decrease of sea temperature under the influence of the typhoon.

Typhoons are major marine dynamic disasters that affect the coastal ocean areas of China. During a typhoon, the coupling dynamic factors, such as wind, waves, storm surges, and river runoff, greatly enhance the mass and energy exchange at the various interfaces of the ocean. A fully coupled atmosphere-wave-ocean model in the South China Sea (SCS) was established based on the WRF, SWAN, and ROMS models. The variation of sea surface salinity (SSS) and ocean subsurface salinity caused by Typhoon Kai-tak (201213) was analyzed by the fully coupled model, and the basic characteristics of the response of the upper ocean to the typhoon are given in this paper. The simulation results demonstrate that the salinity of the sea surface showed a sharp change during Typhoon Kai-tak, and it changed gradually after entering the recovery period. During the passage of Typhoon Kai-tak, the disturbance caused by strong winds strengthened the mixing process of the water in the Pearl River Estuary (PRE) and its adjacent waters. As the typhoon developed, under the influence of Ekman pumping, the mixing effect between the subsurface and the bottom and the upper water was obvious. Before the impact of Typhoon Kai-tak, the salinity had obvious stratification characteristics along the water depth. Due to the influence of the storm surge, the surface water with increased salinity was transported to the estuary, which led to an increase in the salinity of the estuary’s surface water. In this condition, it is highly likely for there to be saltwater intrusion. The salinity distribution characteristics of three schemes (ROMS model only, coupled WRF-ROMS model, and fully coupled WRF-SWAN-ROMS model) were compared in this study. In the fully coupled WRF-SWAN-ROMS model, the disturbance of the bottom water was the most obvious, and the salinity value was greater than that of the coupled WRF-ROMS model, which indicates that under the influence of waves, the mixing and exchange abilities were strengthened.