We investigated ocean surface and subsurface physical responses to Typhoons Kalmaegi and Sarika in the South China Sea, utilizing synergistic multiple-satellite observations, in situ measurements, and numerical simulations. We found significant typhoon-induced sea surface cooling using satellite sea surface temperature (SST) observations and numerical model simulations. This cooling was mainly caused by vertical mixing and upwelling. The maximum amplitudes were 6 °C and 4.2 °C for Typhoons Kalmaegi and Sarika, respectively. For Typhoon Sarika, Argo temperature profile measurements showed that temperature response beneath the surface showed a three-layer vertical structure (decreasing-increasing-decreasing). Satellite salinity observations showed that the maximum increase of sea surface salinity (SSS) was 2.2 psu on the right side of Typhoon Sarika’s track, and the maximum decrease of SSS was 1.4 psu on the left. This SSS seesaw response phenomenon is related to the asymmetrical rainfall on both sides of the typhoon track. Acoustic Doppler Current Profilers measurements and numerical simulations both showed that subsurface current velocities rapidly increased as the typhoon passed, with peak increases of up to 1.19 m/s and 1.49 m/s. Typhoon-generated SST cooling and current velocity increases both exhibited a rightward bias associated with a coupling between typhoon wind-stress and mixed layer velocity.

Accurate modeling of the ocean response to tropical cyclones (TCs) requires high-quality wind fields to force ocean models. In this study, blended wind fields are generated using multi-source satellite data and the Climate Forecast System Reanalysis (CFSR) wind data. We utilize the hybrid wind fields to drive the Regional Ocean Modeling System (ROMS) for simulating oceanic dynamic and thermodynamic parameters. The model’s simulated ocean surface and sub-surface temperatures, as well as current speeds, are generally consistent with satellite and in situ observations collected during TC Winston and Freddy. The results are significantly better than those simulated by ROMS using wind forcing from CFSR alone. These results suggest that incorporating satellite wind data into the atmospheric forcing has the potential to enhance vertical mixing and improve simulations of the upper ocean response to TCs.

We examined how wind forcing affects the upper ocean response under idealized tropical cyclone (TC) conditions. In this study, we constructed three parameterized wind fields with varying spatial and temporal resolutions for TCs of different intensities and translation speeds. The simulated surface and subsurface temperatures were cooler and deeper when using the blended wind fields owing to their higher wind speeds compared to those from coarse–resolution wind fields. Additionally, TC–induced currents were significantly stronger on the right side of the TC track, with notable differences in current velocities. Similar to the increase in ocean currents, the simulated turbulent kinetic energy driven by the blended winds is significantly higher than that simulated by the coarse-resolution wind fields. These findings suggest that using high-quality wind fields to drive ocean models can enhance the accuracy of the upper ocean response to TCs. The sensitivity of the upper ocean responses to wind forcing depends on the TC’s intensity and translation speed. Stronger and slower-moving TCs induce greater vertical shear and enhanced mixing. Therefore, accurate wind stress as a surface boundary condition is crucial for numerical ocean models.