This paper presents an innovative approach to enhance the assimilation of high-resolution simulated observations, specifically targeting Surface Water Ocean Topography (SWOT) Ka-band Radar Interferometer Sea Surface Height (SSH) products, within the Regional Ocean Modeling System (ROMS). Responding to the demand for improved assimilation techniques, we developed a multi-scale Four-Dimensional Variational Data Assimilation (4DVAR) system, building upon validated fine-scale correction capabilities from prior studies. The multi-scale strategy was extended to the ROMS-4DVAR system, providing a comprehensive solution for assimilating high-resolution observations. Leveraging the Observing System Simulation Experiment (OSSE) framework, we conducted a twin experiment comprising a nature run and a free run case. Subsequently, synthetic SWOT SSH measurements were decomposed, considering the model configuration resolution. These components, derived from dense SSH observations, were integrated into a two-step 4DVAR assimilation scheme. The first cycle targets large-scale features for model field correction, and the updated analysis serves as the background for the second assimilation step, addressing fine-scale observation components. Comparisons with the primitive ROMS-4DVAR using a single-scale scheme highlight the superiority of the multi-scale strategy in reducing gaps between the model and the SSH observations. The Root Mean Squared Error (RMSE) is halved, and the Mean Absolute Percentage Error (MAPE) decreases from 2.237% to 0.93%. The two-step assimilation procedure ensures comprehensive multi-scale updates in the SSH field simulation, enhancing fine-scale features in the analysis fields. The quantification of three-dimensional-model dynamic fields further validates the efficiency and superiority of the multi-scale 4DVAR approach, offering a robust methodology for assimilating high-resolution observations within the ROMS.

In this study, we for the first time observed two subsurface cyclonic eddies (SCEs) in the southeastern Tropical Indian Ocean. One SCE (SCE‐C) was observed along 8°S transect during the cruise conducted in July 2016. Another SCE (SCE‐A) was also observed near 8°S but by an Argo float in November 2005. The SCE‐C had a maximum thickness of about 500 m (300–800 m) and a radius of ~90 km, while the SCE‐A has a vertical extent of 700 m (200–900 m) and a radius larger than 110 km. The water trapped by SCE shows a three‐compartment structure. Both the two SCEs are characterized by stratified water with negative lens structure and cause prominent temperature/salinity/spiciness anomalies in a wide density range. As the water carried by SCEs is stratified, we can trace the SCE origin by finding an area sharing the same water property with the SCE on different density surfaces. The result suggests that the two SCEs originate from the southwest coast of the Sumatra Island. Considering the topography and hydrologic characteristics of the SCE origin, we speculate that the SCEs are generated due to topography‐induced South Java Undercurrent instability.

Surface waves and internal tides have a great contribution to vertical mixing processes in the upper ocean. In this study, three mixing schemes, including non-breaking surface-wave-generated turbulent mixing, mixing induced by the wave transport flux residue and internal-tide-generated turbulent mixing, are introduced to study the effects surface waves and internal tides on vertical mixing. The three schemes are jointly incorporated into the Marine Science and Numerical Modeling (MASNUM) ocean circulation model as a part of the vertical diffusive terms, which are calculated by the surface wave parameters simulated from the MASNUM wave model and the surface amplitudes of the mode-1 M₂ internal tides extracted from satellite altimetry data using a two-dimensional plane wave fit method. The effects of the mixing schemes on Indian Ocean modeling are tested by five climatological experiments. The surface waves and internal tides enhance the vertical mixing processes in the sea surface and ocean interior, respectively. The combination of the mixing schemes is able to strengthen the vertical water exchange and draw more water from the sea surface to the ocean interior. The simulated results show significant improvement in the thermal structure, mixed layer depth and surface currents if the three schemes are all adopted.

The surface waves are the most energetic motions, which have great contribution to the turbulent mixing in the upper ocean. In this study, a novel turbulent mixing scheme is proposed in terms of the non‐breaking wave velocity shear module with the buoyancy flux. In the scheme, the mixing coefficients can be calculated empirically from the significant wave height, the wave number, the wave frequency, the buoyancy frequency, and the turbulence Prandtl number. The buoyancy fluxes, as well as the non‐breaking wave velocity shear production, are important for the upper‐ocean turbulent mixing, and make the calculated turbulence dissipation rate closer to in situ observations, which are provided by the “Responses of Marine Hazards to Climate Change in the Western Pacific (ROSE)” Project. The effects of the buoyancy flux on the turbulent mixing are examined based on three numerical experiments using the MASNUM ocean model. In the experiments, the topography, the lateral boundaries, initialization conditions, and the surface forcing fluxes are taken from the GEBCO, HYCOM/NCODA, and ERA5 data, respectively. Comparing to the AVHRR remote sensing sea surface temperature (SST) products and in situ observations, the simulated results with the non‐breaking wave‐generated turbulent mixing gain significant improvement in the SST, upper‐ocean temperature structure, and the mixed layer compared with the classic Mellor‐Yamada scheme. The results show that the buoyancy flux is able to suppress the enhanced non‐breaking wave‐generated turbulent mixing, so that the improved model simulates the observations better than that without the buoyancy effects.

The spatial and temporal variability of the Kuroshio surface axis northeast of Taiwan Island is investigated using 24 years of surface geostrophic currents derived from satellite altimeter data from 1993 to 2016. The Kuroshio surface axis is derived by an extraction method with three selected parameters, including the length of the subsidiary line, the intervals between two adjacent points, and the distance between the two adjacent subsidiary lines. The empirical mode decomposition analysis on the 24-year Kuroshio axes reveals that the mean periods of intra-seasonal and inter-annual variability, which are the two dominant components, are about 3.2 months and 1.3 years, respectively. The self-organizing map analysis reveals that the variation of Kuroshio axis northeast of Taiwan Island has four best matching unit (BMU) patterns: straight-path (BMU_S), meandering-path (BMU_M) and two transition stages (BMU_T1 and BMU_T2). The straight-path pattern shows strong seasonality: more likely occurring in summer. The meandering-path pattern is less frequent than straight-path pattern. During a typical period from November 26, 2012 to January 27, 2013, which is chosen as an independent example, the analysis on the satellite altimeter and sea surface temperature data shows that the patterns of the Kuroshio axis change successively in order of BMU_T1→BMU_M→BMU_T2→BMU_S, i.e., the Kuroshio axis migrates from the meandering-path to the straight-path pattern. During the typical period the warm water intrusion and a mesoscale eddy occur at the second stage corresponding to BMU_M and migrate northwestward gradually at the last two stages corresponding to BMU_T2 and BMU_S. The transient order appears only during this typical period but it is not common for the whole study period. The monthly mean relatively vorticity is calculated and analyzed to evaluate the impact of the eddies on the Kuroshio surface axis variability, the results show that the anticyclonic (cyclonic) eddies can promote the Kuroshio surface axis to present the meandering-path (straight-path) pattern because of the potential vorticity conservation. The impacts of the anticyclonic eddies and the cyclonic eddies on the variability of the Kuroshio surface axis are opposite. The long-term day-to-day detection contributes to improving understanding the variability of Kuroshio surface axis northeast of Taiwan Island.