Shengyi Jiao

F_TIDE has been proven to be effective in obtaining the time-varying harmonic parameters of nonstationary tidal signals, and the results near the two endpoints of the analyzed time series are more accurate than those obtained by S_TIDE, which provides good conditions for the prediction of future sea levels. In this paper, F_TIDE is used for the short-term prediction of nonstationary tides in Nome (Alaska) and South Beach (Oregon). The significance of each standard parameter of F_TIDE is quantified by calculating its signal-to-noise ratio to determine the appropriate parameters that can be used for prediction. F_TIDE performs well in forecasting the sea level for three weeks at the Nome gauge and one week at the South Beach gauge. F_TIDE causes 30.1% and 42.0% decreases in the mean absolute errors between the forecasts and the observations compared to T_TIDE. F_TIDE is applied to the original signal at the Nome gauge, and the results show a strong correlation between the variation in M₂ amplitude and the variation in the mean sea level. A potential mechanism is speculated in that changes in tides are affected by the changes in water depth on different time scales, which the sea level pressure, wind, sea ice, and other marine motions may contribute to.

The direct fitting of sea level anomaly (SLA) using satellite along-track data provides a critical approach for monitoring mesoscale ocean dynamics. While bicubic quasi-uniform B-spline surface fitting has demonstrated feasibility in localized sea areas, its applicability to basin-scale regions remains underexplored. This study focuses on the northern Atlantic Ocean, employing B-spline surface fitting to derive SLA fields from satellite along-track data. The results show strong agreement with in situ measurements, yielding a mean absolute error (MAE) of 1.89 cm and a root mean square error (RMSE) of 3.02 cm. Comparative analysis against the Copernicus Marine Environment Monitoring Service (CMEMS) Level-4 gridded SSH data reveals nearly equivalent accuracy (MAE: 1.95 cm; RMSE: 3.06 cm). The relationship between the order of fitting and the spatial extent of the fitting domain is also examined. Furthermore, the influence of the coastline on the fitting results is investigated in detail. As the coastline area expanded, the MAE and RMSE for the entire region increased. But the maximum increase in MAE was only 1.20 cm, and the maximum increase in RMSE was only 2.49 cm. Notably, there was no upward trend in MAE and RMSE in the mesoscale vortex dense area, which highlights the advantage of B-spline’s local support. Geostrophic flow and vertical component of relative vorticity are computed from the satellite along-track SLA data, with results showing agreement with Level-4 gridded geostrophic flow and vertical component of relative vorticity data.

Numerical simulations of the eight major tidal constituents (M₂, S₂, K₁, O₁, N₂, K₂, P₁, and Q₁) in the Bohai, Yellow and East China Seas (BYES) were conducted using the Regional Ocean Modeling System (ROMS) based on altimeter products from X-TRACK. Tidal harmonic constants and two-dimensional tidal current data with a spatial resolution of 1/12° were obtained. To validate the simulation results (SRs), harmonic constants from altimeters and tide gauges, two sea level anomaly time series, and velocity observations from 12 current meters were utilized. Additionally, data from five tidal models were used for comparison. The validation and comparison results demonstrated the accuracy of SR, especially when compared with coastal tide gauge data where SR performs exceptionally well. The cotidal charts and tidal current ellipses obtained through SR exhibited good continuity and consistency with the previous studies, effectively reflecting the tidal characteristics of the BYES. The SR can serve as a valuable reference and support for tidal-related fields in the BYES, including the supplement and verification of ocean measurements and the calculation of reference planes for ocean engineering.

Tidal open boundary conditions (OBCs) of the M₂ tidal constituent in the Bohai and Yellow Seas (BYS) are estimated via the assimilation of multi-satellite altimeter data to optimize regional tidal numerical simulation. A two-dimensional adjoint assimilation model is used for tidal numerical simulation and, as an improvement, trigonometric polynomials fitting (TPF) is applied in the inversion of OBCs. It is assumed that the linearized amplitudes/phases in the open boundary are spatially varying and can be represented by nonlinear functions. Based on the discrete Fourier series, taking the trigonometric function as the basis function, the spatially varying OBCs are constructed by selecting the maximum truncation period. The independent points scheme used in previous studies was also compared in the experiments. Twin experiments show that the errors of simulations with TPF are the smallest in different schemes, and their results show the highest correlation with observations while maintaining the best performance in terms of observation errors. The mean absolute errors (MAEs) in amplitude/phase between the simulated results using estimated OBCs and the satellite altimeter records are 2.82 cm and 2.26°, respectively.

The optimal siting selection strategy for new tidal stations in the Bohai Sea is investigated using a two-dimensional tidal model with the adjoint method. Harmonic constants (HCs) of the M₂ constituent at all computing grids are estimated in the Bohai Sea by assimilating observations from existing tidal stations and altimeter data processed by X-Track software. Several grid points on the coastline are selected as new tidal station sites, and different combinations of selected points are regarded as different siting strategies. The HCs at these new tidal stations are served as “simulated observations” (SOs) which are assimilated into the tidal model to re-estimate the HCs in the Bohai Sea. Through comparisons between the re-estimated HCs and SOs, we can evaluate the effects of different siting strategies. Divide the Bohai Sea into different subdomains, numerical experiments are constructed to investigate the effects of different strategies in different subdomains, while the effects of schemes including inversion variables and different tidal constituents on siting selection are experimented. By analyzing the root-mean-square (RMS) difference between re-estimated HCs and SOs on the coastline in different subdomains, the optimum strategy for siting of new tidal stations in the Bohai Sea is obtained.

The setting of initial values is one of the key problems in ocean numerical prediction, with the accuracy of sea water temperature (SWT) simulation and prediction greatly affected by the initial field quality. In this paper, we describe the development of an adjoint assimilation model of temperature transport used to invert the initial temperature field by assimilating the observed data of sea surface temperature (SST) and vertical temperature. Two ideal experiments were conducted to verify the feasibility and validity of this method. By assimilating the “observed data”, the mean absolute error (MAE) between the simulated temperature data and the “observed data” decreased from 1.74 °C and 1.87 °C to 0.13 °C and 0.14 °C, respectively. The spatial distribution of SST difference and the comparison of vertical data also indicate that the regional error of vertical data assimilation is smaller. In the practical experiment, the monthly average temperature field provided by World Ocean Atlas 2018 was selected as background filed and optimized by assimilating the SST data and Argo vertical temperature observation data, to invert the temperature field at 0 a.m. on 1 December 2014 in the South China Sea. Through data assimilation, MAE was reduced from 1.29 °C to 0.65 °C. In terms of vertical observations data comparison and SST spatial distribution, the temperature field obtained by inversion is in good agreement with SST and Argo observations.