Sediment oxygen consumption (SOC) is an important parameter of marine sediments and an important characterization parameter of the rate of organic carbon mineralization in seafloor sediments, and the study of SOC can help us to understand the carbon cycling process in the whole ocean. As one of the most important and active sites for organic carbon mineralization and burial, marginal seas have received widespread attention and research around the world, but there is still a lack of relevant attention to the Chinese marginal sea region with typical seasonal variations of the marine environment, especially the Yellow Sea and Bohai Sea. In this paper, the intact core incubation was used to study the SOC in the Yellow Sea and Bohai Sea in April, July and October 2022, and the results showed that the rates of SOC ranged from 7.11 mmol/(m²·d) to 17.33 mmol/(m²·d). There was no significant difference between the SOC of the Yellow Sea and the Bohai Sea in spring (ANOVA, p > 0.05), and the SOC of the Yellow Sea was lower than Bohai Sea in summer (ANOVA, p < 0.01) and autumn (ANOVA, p < 0.01); the SOC of the Yellow Sea was the largest in spring and the smallest in summer, and there was no significant difference between the SOC of the Bohai Sea in summer and autumn, which were significantly higher than that of spring (ANOVA, p < 0.05). Temperature and sediment Chl a concentration were the influencing factors. Meanwhile, the SOC was used to assess the rate of benthic organic carbon mineralization. When compared with the primary productivity, the results indicated that the contribution of benthic organic carbon mineralization to primary productivity in the Bohai Sea ranged from 42.8% to 74.5%, which was one of the key links in the carbon cycle of the Bohai Sea, while the benthic organic carbon mineralization in Yellow Sea plays a less significant role in the carbon cycle of the Yellow Sea carbon cycle than Bohai Sea. This paper systematically studied the SOC in the Yellow Sea and Bohai Sea and its spatial and temporal distribution characteristics, exploring the contribution of organic carbon mineralization to primary productivity in the Yellow Sea and Bohai Sea, which provided theoretical support for the understanding of organic carbon mineralization and burial in the Yellow Sea and Bohai Sea.

Cage aquaculture is one of the most important types of marine aquaculture. Different types of cages have varying shapes in remote sensing images, and the background is complex. Previous methods for cage extraction have not been able to fully simulate human visual behavior and efficiently utilize spectral information. To address these issues, we propose a Spectral Loopy Attention U-Net (SLA-UNet) network model for cage aquaculture information extraction. The model utilizes the Random Forest (RF) algorithm based on the Estimation of Scale Parameter (ESP) to remove redundant spectral information after band operations. It also incorporates a human-like attention mechanism to enhance the important feature channels that affect cage information extraction. Additionally, edge completion is performed to supplement the loss information, achieving high-precision extraction of cage aquaculture information. We selected Zhanjiang City, Guangdong Province and Lingao County, as the study areas. Comparisons were made with the extraction results of the Canny algorithm, Otsu algorithm, PCA_Kmeans algorithm, RF algorithm based on ESP, and the U-Net model. The extraction accuracy of the SLA-UNet model for nearshore cages is 98.3%, and the average extraction accuracy for deep-sea cages is 98.9%, validating the effectiveness of the SLA-UNet model in cage aquaculture recognition.

To clarify the composition and distribution characteristics of macrobenthic communities in Yantai Changdao Island marine ranch and evaluate the impact of marine ranching on these macrobenthos, sampling stations were set up inside and outside the marine ranch in October 2022. Surveys of macrobenthic animals and the characteristics of macrobenthic communities were analyzed. A total of 88 species of macrobenthic animals were collected and identified during this voyage. Although the number of species in the pasture and control area was similar, the dominant groups differed. In the pasture, 70 species were identified, with mollusks being the dominant group; whereas, in the control area, 69 species were identified, with annelids as the dominant group. Eight dominant species were found, including 3 mollusk species in the pasture and 6 species in the control area, comprising 2 mollusk species, 1 echinoderm species, and 3 annelid species. The average abundance and biomass of macrobenthic animals in the pasture were significantly higher than those in the control area. However, Margalef species richness index (d), Pielou evenness index (J'), and Shannon Wiener diversity index (H') values showed little difference between the pasture and the outside. The results of Cluster analysis (CLUSTER) and non-metric multidimensional scaling (NMDS) analysis indicated that relatively low similarity among each station inside and outside the marine ranch. The AMBI and m-AMBI analyses revealed that the overall pollution disturbance in the studied water area was relatively small, indicating good benthic ecological health. Combined with historical data, the analysis revealed a significant increase in species abundance and biomass of macrobenthic communities in the surveyed area. These results suggest that the development of marine pastures has a certain degree of impact on the growth and development of macrobenthic communities.

The double-row perforated cylinder breakwater is a new type of environment-friendly breakwater, and the research on its wave absorbing characteristics is of great engineering significance. With the development of artificial intelligence, solving the water dynamics problem of breakwater based on machine learning technology has become a new research paradigm. This paper proposes a Convolutional Neural Network (CNN) model based on Sparrow Search Algorithm (SSA) to achieve intelligent optimization prediction of transmission coefficient of double-row perforated cylindrical breakwater. The results show that: (1) wave height, wave period, wavelength, wave velocity, row spacing, hole rate and water depth are identified as the key factors affecting the transmission coefficient. (2) When the population size of the SSA-CNN model is 10, the R² value of the wave transmission coefficient prediction reaches 0.9909, and the average relative error is reduced by 22.24% compared with the single CNN model. The research results provide a new optimal prediction model for the study of wave transmission by using neural networks.

This study focuses on the physical process of a sea fog event during Typhoon “Lekima” (1909) in the northern Yellow Sea by using observation data, reanalysis data and backward trajectory model. The analysis indicates that the typhoon circulation was the decisive factor determining whether fog formed offshore and developed inland. The warm and humid southerlies from the South Yellow Sea condensed into fog on the colder sea surface besides the typhoon center, which not only provided sufficient moisture for the formation and development of the sea fog but also formed a significant inversion layer over the fog area with the downdraft in the center of the typhoon. The “stable up and turbulent down” structure in the atmospheric boundary layer improved the development of sea fog on the coast and inland area. However, the horizontal wind steering and the strengthening wind speed behind the typhoon strengthened the wind shear in the atmospheric boundary layer, resulting in the enhanced turbulent mixing and the decrease of the stability in the bottom atmospheric boundary layer, which was the main cause of the fog dissipation.

This study used ERA5 reanalysis data to collect an extreme wave event dataset for various regions in the Arctic Ocean during August to October from 1979 to 2021. The analysis focused on the frequency of extreme wave events, changes in extreme wave heights, features of wave power and wave direction distribution, as well as the change of sea ice during wave events. The results suggest that as sea ice decreases, the range of extreme wave activity in the Arctic expands. All regions, except the Barents Sea, exhibit an increase in the occurrence of extreme wave events. In particular, extreme wave heights in the East Siberian Sea and Laptev Sea have significantly increased at rates of approximately 3.5 cm/a and 2 cm/a, respectively, with event frequency reaching around 4 events per year. The dominant wave direction in the Laptev Sea is southerly, facilitating more frequent wave propagation into the ice zone compared to other seas, with an average wave energy flux ranging from 5−8 kW/m. The changes in sea ice within extreme wave events primarily occur in the marginal ice zones and are associated with wind direction: sea ice is more likely to decrease with on-ice winds, while it is more likely to increase with off-ice winds.

Sea surface gusts are important marine dynamic environmental information required for the development of marine resources, marine disaster prevention and reduction, and marine scientific research. However, so far, there has been a serious lack of observational data on sea surface gusts, which has hindered the development of gust forecasting, application research, and other aspects. This article uses the backscatter coefficients in the C and Ku bands of the dual frequency HY-2B satellite altimeter to correct the existing sea surface wind speed ($ {U}_{10} $) and gust wind speed ($ {U}_{{\mathrm{g}}} $) inversion algorithm. The inversion results were verified for authenticity with the buoy data from the National Buoy Data Center (NDBC) of the United States from 2018 to 2022. The correlation coefficient (R) was 0.91, and the root mean square error (RMSE) was 1.82 m/s; based on the inversion results of this method and the NDBC station data from 2018 to 2022, the RMSE of similar foreign satellites Jason-3 is superior to the conventional 2 m/s accuracy requirement; the inversion results were verified with individual cases of offshore and oceanic stations at different latitudes, and the RMSE was better than 2 m/s. Therefore, based on the existing HY-2B satellite altimeter sea surface wind speed observation data, this article uses different band information to achieve observation of sea surface gusts, which has high observation accuracy. Meanwhile, this method is also applicable to foreign satellite altimeters with the same observation system.

Submesoscale processes associated with strong vertical velocities play significant roles in the vertical transport of tracers between the ocean surface and the interior, including heat, buoyancy, and mass. Based on the results of the (1/48)° LLC4320 model, this study investigates the seasonal variations of submesoscale vertical heat transport in the Kuroshio Extension. The results show that submesoscale vertical heat transport in the Kuroshio Extension exhibits distinct seasonal variations, with strong transport in spring and winter, and weaker transport in summer and autumn. The variation of net submesoscale vertical heat flux in the upper ocean is consistent with the trend of mixed layer depth, which shows overall upward submesoscale heat transport above the mixed layer and strong alternating positive and negative submesoscale vertical heat transport below the mixed layer, resulting in relatively small net submesoscale vertical heat transport. Coherent spectral analysis of vertical heat flux wavenumber-frequency suggests that submesoscale vertical heat transport below the mixed layer may be caused by linear internal waves, but the upward and downward vertical heat transports induced by linear internal waves counteract each other, leading to a reduced net vertical heat transport after averaging over the season.

The Japan Sea is the largest marginal sea in the northwestern Pacific Ocean. For a long time, it has been widely believed that the sediments are deposited in strongly reducing environment, which results in extremely weak magnetic signals and then restricts the application of frequently-used magnetic method in this region. To investigate deeply the availability of magnetic indicators in paleoenvironmental and paleoceanographic studiesin the Japan Sea, we conducted systematic rock magnetic analyses, high-resolution accelerator mass spectrometer (AMS) ¹⁴C dating, and grain-size analysis on a 626-cm-long sediment core (LV87-2-3, water depth 740 m) recovered from the northern Japan Sea that has been studied in relatively low level. The results indicate that the studied core corresponds to a sedimentary record since approximately 48.3 ka BP. The majority of primary ferrimagnetic minerals, mainly magnetite, in the sediments below 55 cm, had been reduced into pyrite, which caused weakly magnetic intensity. This is associated closely with the intensified stratification of water body and the increase in surface productivity during interstadials in the Dansgaard-Oeschger (D-O) cycles. Nevertheless, there are still four strong magneticlayers characterized by elevated percentages of high-coercivity minerals (i.e., hematite and goethite), which are termed as ‘hard-magnetic abnormal’ layers and correspond well with the Heinrich Events. This indicatesrelatively weak reducing conditions that were resulted from the enhanced East Asian Winter Monsoon (EAWM) and injection of high salinity Tsushima Warm Current (TWC). These changes, however, are not reflected by the grain-size of sediment. Our study therefore not only indicates that the role of magnetic parameters in the paleoenvironmental and palaeoceanographic reconstructions of the Japan Sea during the last glacial, but also provides new perspectives and ideasfor relevant investigations in the future.

Plastic floating objects have a profound impact on the marine environment. The nearshore process of the floating objects is mainly influenced by the action of waves. On the kinetic characteristics of plastic floating objects, previous studies were not thorough for the nearshore regime. In this paper, laboratory experiments were used to study the drift-law of plastic-floating objects under finite-water-depth waves. The relationship between the horizontal drift velocity of a weakly inertial plastic blocks and their characteristics, along with the wave steepness were discussed. The experimental results show that the drift of plastic blocks is affected by Stokes drift and Euler return flow, which is in good agreement with the second-order Lagrange drift theory. As the floating object’s size is much smaller than the wave length, size or density of the floating objects has no significant effect on drift. The drift of floating objects is proportional to the square of wave steepness. Based on the experiments conducted in this study and previously published experimental data, the empirical formula is revised to provide useful reference for the nearshore migration law of plastic floating objects and so for the relevant prediction.