The water mass in the East China Sea (ECS) shelf has a complicated three-dimensional (3D) hydrologic structure. However, previous studies mostly concentrated on the sea surface based on the sparse in situ and incomplete satellite-derived observations. Therefore, the 3D interpolation technology was introduced for the reconstruction of hydrologic structure in the ECS shelf using in situ temperature and salinity observations in the summer and autumn of 2010 to 2011. Considering the high accuracy and good fitness of the radial basis function (RBF) methods, we applied the RBF methods to the in situ observations to completely reconstruct the 3D hydrologic fields. Other 3D interpolation methods and 2D methods were also tested for a comparison. The cubic and thin plate spline RBFs were recommended because their mean absolute error (MAE) in the 10-fold cross-validation experiments maintained the order of ~10−2. The 3D RBF reconstructions showed a reasonable 3D hydrologic structure and extra details of the water masses in the ECS shelf. It also helps evaluate regional satellite-derived sea surface temperature (SST). Comparisons between the interpolated and satellite-derived SST indicates that the large bias of satellite-derived SST in the daytime corresponds to weak mixing during low-speed wind and shows seasonal variation.

The adjoint assimilation method has been widely used in various ocean models, and a series of technical schemes have been developed at the same time. Open boundary conditions (OBCs) in the two-dimensional (2D) tidal model of the M2 tidal constituent in the Bohai and the Yellow Seas (BYS) were inverted successfully using the adjoint assimilation methods in previous studies. However, the cost function in the adjoint assimilation method usually used the L2 norm in the past, which is difficult to maintain the robustness of the method when there are outliers. Meanwhile, using the L1 norm with strong robustness will shield the outliers’ information fully. Therefore, we propose a new scheme that replaces the L2 norm with the Huber function to improve the robustness of the adjoint assimilation method and absorb the data’s useful information to some extent. This scheme was verified in the ideal experiments in which magnitudes of the misfit vector were significantly reduced and the quality control (QC) process was simplified consequently. In the practical experiments, the introduction of the Huber function improved the accuracy of inversion in the inshore area using mixed data containing tide gauges and satellite altimetry. With this scheme, the root-mean-square errors (RMSEs) between the estimation and the observed values at tide gauge stations were reduced from ∼8 cm with the original scheme to ∼6cm. Testing the new scheme in more complex models and how it might be affected by the factors remains a topic for future study.