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The ocean front has a non-negligible role in global ocean–atmosphere interactions, marine fishery production, and the marine military. Hence, obtaining the positions of the ocean front is crucial in oceanic research. At present, the positioning method of recognizing an ocean front has achieved a breakthrough in the mean dice similarity coefficient (mDSC) of above 90%, but it is difficult to use to achieve rapid extraction in emergency scenarios, including marine fisheries and search and rescue. To reduce the its dependence on machines and apply it to more requirements, according to the characteristics of an ocean front, a multi-scale model SQNet (Simple and Quick Net) dedicated to ocean front position recognition is designed, and its perception domain is expanded while obtaining current scale data. In experiments along the coast of China and the waters of the Gulf of Mexico, it was not difficult to find that SQNet exceedingly reduced running time while ensuring high-precision results (mDSC of higher than 90%). Then, after conducting intra-model self-comparison, it was determined that expanding the perceptual domain and changing the weight ratio of the loss function could improve the accuracy and operational efficiency of the model, which could be better applied in ocean front recognition. [ABSTRACT FROM AUTHOR]

Red tide is a marine phenomenon caused by the excessive growth of microscopic algae in the ocean. This study aims to analyze the development trends of red tides in the past 20 years and the dynamic external causes that induce red tides based on existing satellite remote sensing and numerical simulation data. And the changes in dominant species of red tides in different seasons are analyzed. The results show significant temperature fluctuations within the week before the red tide occurs, with an average increase of 1.42 °C. In contrast, the change in salinity is relatively small. Meanwhile, ocean fronts are areas in the ocean where different water masses meet and form boundaries. The average strength of ocean fronts increased by 3.7%, indicating enhanced ocean mixing over a short period of time. Under the combined influence of these factors, the probability of a red tide outbreak in the East China Sea increases rapidly. Therefore, this study has important reference value for further research on the causes of red tides and their response to ocean dynamic changes. • Study analyzes 20-year trend of red tides and their dynamic causes. • Before a red tide, average temperature rises by 1.42 °C; salinity changes little. • Increased ocean front strength by 3.7% boosts East China Sea red tide risk. [ABSTRACT FROM AUTHOR]

Cross-front transport is a vital process in the offshore transport of terrestrial materials. The factors influencing cross-front transport are multifaceted and exhibit regional variability. As important factors regulating material transport patterns in the shelf seas of eastern China, the East Asian Winter Monsoon (EAWM) and Kuroshio current (including its branches) vary on multiple time scales, yet their role in controlling offshore transport is not fully understood. In this paper, cross-front offshore transport in the North Yellow Sea is chosen to investigate the aforementioned issue using numerical simulation. By excluding other potential processes for offshore transport, frontal instability is identified as the primary mechanism for offshore transport, which is triggered by winter storms (bursts of the EAWM); hence, the intensity of offshore transport is highly associated with the strength of winter storms on synoptic scales. However, on the inter-annual scale, the intensity of offshore transport is more likely regulated by the strength of the Kuroshio current, and a warming Kuroshio facilitates offshore transport. Although the role of each factor in controlling the intensity of offshore transport is delineated, the interactive effects of the EAWM and Kuroshio current on offshore transport are quite intricate, and how to quantitatively estimate their roles on multiple time scales remains a challenge using modelling. The results obtained from this study can be applied to analyse cross-front transport throughout the eastern China seas and bear significant implications for future studies on pollutant diffusion, nutrient distribution, and sediment transport in the coastal area. • Cross-front transport around the Shandong Peninsula was revealed using a numerical model. • EAWM and Kuroshio affect the strength of cross-front transport on different time scales. • With global warming, the temperature of Kuroshio might gradually become the primary control of cross-front transport. [ABSTRACT FROM AUTHOR]