The rapid development of coastal economies has aggravated the problem of pollution in the coastal water bodies of various countries. Numerous incidents of massive-scale marine life deaths have been reported because of the excessive discharge of industrial and agricultural wastewater. To investigate the diffusion of typical pollutants after discharge, in this study, a multi-process fusion simulation analysis model of pollutants under the action of ocean currents was established based on the concentration analysis method. Furthermore, key technologies involved, such as the parameter value, data selection, and visualization, were investigated. The iterative analysis and programming realization of three independent sub-processes, such as pollutant diffusion and transport, and the drift path and concentration distribution of pollutants after their discharge into the sea, were visualized. The case study revealed that the increase in the concentration of pollutants in the ocean was affected by the diffusion sub-process, and the transport sub-process plays a critical role in the long-distance transport of pollutants. The proposed method can provide technical support for marine environmental risk assessment and dynamic tracking of marine pollutants.

It is widely recognized that the initial ensemble describes the uncertainty of the variables and, thus, affects the performance of ensemble-based assimilation techniques, which is investigated in this paper with experiments using the Community Earth System Model (CESM) and the Data Assimilation Research Testbed (DART) assimilation software. Five perturbation strategies involving adding noises of different patterns and with/without extra integration are compared in the observation system simulation experiments framework, in which the SST is assimilated with the ensemble adjustment Kalman filter method. The comparison results show that for the observed variables (sea surface temperature), the differences in the initial ensemble lead to different rate of convergence in the assimilation, but all experiments reach convergence after three months. However, other variables (sea surface height and sea surface salinity) are more sensitive to the initial ensemble. The analysis of variance results reveal that the white-noise perturbation scheme has the largest RMSE. After excluding the effect of the white noise perturbation scheme, it can be found that the difference in the effect of different initial ensembles on the SSH with only assimilated SST is concentrated in the region of the Antarctic Circumpolar Current, which is related to the spread of the covariance between the SSH and the SST.