High-precision tidal harmonic constants are necessary for studies involving tides. This study proposes a new method combined with the adjoint assimilation model and the Chebyshev polynomial fitting (CPF) method to obtain the tidal harmonic constants in the shallow-water region of the Bohai and Yellow Sea (BYS). Based on the CPF method, the full-field harmonic constants and reliable cotidal charts of the eight major constituents (M₂, S₂, K₁, O₁, N₂, K₂, P₁ and Q₁) were fitted from the X-TRACK products briefly and this method was effectively for coastal conditions. Compared with the observations of the X-TRACK products and tidal gauges, for the M₂ constituent, the TPXO9, Finite Element Solutions 2014 (FES2014), National Astronomical Observatory 99b (NAO.99b) and Empirical Ocean Tide 20 (EOT20) models yield the root-mean-square errors (RMSEs) of 18.50, 7.31, 18.73 and 13.32 cm, respectively, while the CPF method yields an RMSE of 10.74 cm. These results indicate that the CPF method could maintain high resolution and obtain accurate cotidal charts consistent with the simulations of the four models in shallow-water regions.

The harmonic constants of long-period tidal constituents are critical for simulating the tide process, obtaining theoretical datum sounding reduction, and conducting further ocean research. In this paper, the equidistant node orthogonal polynomial fitting (ENOPF) method is employed to fit the harmonic constants of the T/P satellite altimeter data and the gridded altimeter data from the Data Unification and Altimeter Combination System (DUACS) to obtain the full-field harmonic constants of the long-period tidal constituents (S_a and S_sa) in the Bohai Sea, Yellow Sea, and East China Sea (BYECS). To verify the validity of the ENOPF method, the long-period tidal harmonic constants of the ENOPF method, the Finite Element Solutions 2014 (FES2014) model, the Empirical Ocean Tide 20 (EOT20) model, and the DUACS data were compared with the observations of the X-TRACK products and the tide gauges. In addition, the root-mean-square errors (RMSEs), amplitude differences ($\Delta \mathrm{H}$), and phase-lag differences ($\Delta \mathrm{G}$) of the comparison results were calculated. According to the error analysis and the cotidal charts, the ENOPF method is better than the other three methods or models for comparing tide gauges (6.19 cm, 5.85 cm, 25.44°; 1.10 cm, 0.72 cm, 59.09°, respectively. The cotidal charts obtained by the ENOPF method are smoother and have better consistency with the actual track data. The results indicate that, due to the polynomial fitting method adopted in ENOPF method, which has the characteristics of improving the resolution infinitely, it is easier to obtain the harmonic constant of full field than with other models or methods. This study proves that the ENOPF method is a reasonable and simple tool in extracting the harmonic constants of the BYECS.

This study used the Massachusetts Institute of Technology general circulation model (MITgcm) to simulate the seabed liquefaction process in the Chengdao area. The liquefied soil and the overlying water are considered as a two-layer fluid system in the model. By constructing various topographies using Gaussian functions, it is possible to achieve an agreement between simulation and measurement. The simulation results reveal the characteristics of pore pressure in different topographies. The main findings include the following: (1) The expansion of liquefaction zone leads to an accelerated attenuation of pore pressure amplitude. (2) A decrease in topographic slope diminishes the wave group characteristics of pore pressure due to the sensitivity of certain wave components with specific frequencies to topographic slope.

Satellite observations of sea surface chlorophyll‐a concentration (SChl) provide a basin‐scale record for interpreting marine productivity and upper ocean biogeochemical variability. However, clouds and other observational limits create gaps in SChl retrieval, which can bias the SChl record, especially in cloud‐prone mid‐to‐high‐latitude oceans. Here, we use satellite SChl data from 2010 to 2019 to quantify sampling bias associated with synoptic‐scale wind speed conditions. In winter, compared with low wind speed conditions, high wind speed conditions are often cloudier, yielding fewer valid retrievals of SChl. At the same time, observed SChl is generally lower under high wind speed conditions across the mid‐to‐high latitudes of the North Atlantic and the North Pacific. Together, these differences bias mean SChl upward. The largest bias occurs in winter, when the bias of gyre‐mean SChl is about 1.4%, with local values exceeding 10%. The resulting SChl bias also propagates into satellite‐based estimates of ocean productivity.