In order to quantitatively analyze the data measurement accuracy of ocean buoys under normal and extreme sea conditions, in this study, we simulated the six-degree-of-freedom motion response of self-designed ocean buoys under different sea conditions based on a separated vortex simulation and the fluid volume method and analyzed the impact of the unsteady motion of buoys on data measurement. The results indicate that under normal sea conditions, the deviation between the numerical method used in this paper and the experimental results is less than 10%. The heaving motion of a buoy is most sensitive to changes in wave conditions. The fluctuation intensity of buoy motion is modulated by the height and wavelength of waves. When the wave height and wavelength are similar to the overall geometric size of a buoy, the wave characteristics of the buoy’s heave, yaw, and pitch motion are significant. In addition, under extreme sea conditions, the movement of the buoy can also cause a deviation in the measured velocity in the transverse flow direction, but the overall deviation is less than 10%. In extreme sea conditions, the wind speed measurement results should be corrected to improve the measurement accuracy of a buoy.

Current marine research that leverages remote sensing data urgently requires gridded data of high spatial and temporal resolution. However, such high-quality data is often lacking due to the inherent physical and technical constraints of sensors. A necessary trade-off therefore exists between spatial, temporal, and spectral resolution in satellite remote sensing technology: increasing spatial resolution often reduces the coverage area, thereby diminishing temporal resolution. This manuscript introduces an innovative remote sensing image fusion algorithm that combines Sentinel-2 (high spatial resolution) and Sentinel-3 (relatively high spectral and temporal resolution) satellite data. The algorithm, based on a cross-attention mechanism and referred to as the Cross-Attention Spatio-Temporal Spectral Fusion (CASTSF) model, accounts for variations in spectral channels, spatial resolution, and temporal phase among different sensor images. The proposed method enables the fusion of atmospherically corrected ocean remote sensing reflectance products (Level 2 OSR), yielding high-resolution spatial data at 10 m resolution with a temporal frequency of 1–2 days. Subsequently, the algorithm generates chlorophyll-a concentration remote sensing products characterized by enhanced spatial and temporal fidelity. A comparative analysis against existing chlorophyll-a concentration products demonstrates the robustness and effectiveness of the proposed approach, highlighting its potential for advancing remote sensing applications.

The stability performance of the buoy is an important parameter that should be taken into account when designing marine buoys. This paper introduces a theoretical and numerical analysis method to examine the stability of marine buoys, including analysis of the initial stability and large inclination stability by calculating the natural period, metacentric height, static stability, and dynamic stability, deriving the calculation process of the static stability lever in detail to obtain the righting moment, and so on, showing that the designed buoy in this paper has sufficient stability performance with theoretically excellent resistance performance to the wind and waves. Additionally, the hydrodynamic performance of the buoy at different heights is also further analyzed for structural optimization, which concluded that the buoy would have a more balanced stability performance when the buoy’s width-to-height ratio is 0.375–0.5, hoping that the computational model and ideas used in this paper can provide a reference for the theoretical stability analysis and buoy design of other types of buoys.