The lack of dimensionality of ocean observations makes it difficult to utilize multi-scale data assimilation to correct model errors with limited observations. Since satellite observations can provide high-resolution and time-continuous sea surface information, this study utilizes sea surface temperature (SST), sea surface salinity (SSS), and sea surface height (SSH) anomalies to invert the vertical temperature and salinity fields and thus realize multi-scale data assimilation in the three-dimensional space. We propose a temperature and salinity inversion network (TSI-Net) for reconstructing the mapping of the sea surface’s spatial distribution features to vertical structural features to obtain pseudo-observed fields. In this study, measured satellite remote-sensing data and temperature and salinity profiles are used to correct the model errors in the waters around the China Sea. The sensitivity analysis shows that the multi-component inversion can better fit the temperature field relationship, with a correlation coefficient of about 0.87. The results of the assimilation experiments show that the analytical field obtained by assimilating the pseudo-observed field is more consistent with the target field in terms of the spatial distribution characteristics.

Using the local multiscale energy and vorticity analysis (MS-EVA) and based on the global high-resolution ocean reanalysis product GLORYS12V1 for 20 years, this study investigates the energy transfers and conversions of Kuroshio in the Luzon Strait and its adjacent regions through three scales, namely, the climatological scale, the seasonal scale, and the eddy scale. The results show that the inverse cascades of kinetic energy dominate the energy transfer east of Luzon (at both the eddy and seasonal scales). Kuroshio transfers the climatological kinetic energy to the eddy scale through a forward energy cascade in Luzon Strait and east of Taiwan. Because the topography of Luzon Strait and Kuroshio jointly block and limit the westward propagation of non-local eddies, the eddy energy in the South China Sea west of Luzon Strait tends to depend on local forward potential energy cascades. In these subregions, potential energy drives the accumulation of kinetic energy under the action of buoyancy conversion: interannual (seasonal) potential energy as the source of multiscale energy in the Luzon Strait (the east of Taiwan).

Motivated by the need for a simple and effective assimilation scheme that could be used in a relocatable ocean model, a new assimilation algorithm called ensemble optimal smoothing (EnOS) was developed. This scheme was a straightforward extension of the ensemble optimal interpolation (EnOI) by involving time correlation information in the Kalman gain. The main advantage of this scheme was the ability to estimate the present state from the time history of observation. We first examined the new scheme in an ideal ocean model using simulated observations. Further applying these two assimilation schemes to the Chinese offshore and adjacent waters, the root-mean-square error (RMSE) of the EnOS scheme was reduced by 6.4% relative to EnOI. The results showed that the EnOS was more efficient and effective in eliminating model errors when compared to the EnOI scheme.

Previous studies have pointed out that spectral nudging is still insufficient in improving the long-term simulation ability of numerical models. In response to this problem, this study started with the Luzon Strait and its adjacent areas and discussed the influence of the selection of correction targets on its long-term spectral nudging. We established two sets of numerical experiments with the same parameter configuration except for the correction target: one was the monthly climatological target, and the other was the monthly real-time. The results showed that, compared with the climatology, the real-time target improved the consistency with the observations in large-scale variability on the premise of ensuring the correction of the climatological bias of the model. Further verification of the real-time scheme better simulated the meso- and small-scale characteristics, especially more accurately reproducing the position, intensity, and movement trend of eddies when the Kuroshio intrusion event occurred. Multi-scale energy analysis revealed the significance of adjusting large-scale potential energy to improve the overall simulation ability. The premise is that the correction target needs to fully contain these effective large-scale signals and non-stationary features, and then introduce them into the numerical integration of the regional model through appropriate band-pass filter parameter settings, driving a more reasonable large-scale background state thereby.