The significant wave height (SWH) is a key parameter for describing the ocean waves. In this paper, the SWH in the Taiwan Strait provided by the ERA-Interim reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF) in March 2013 is compared with the buoy observations and the simulation results of the SWAN (Simulating Waves Nearshore) model. The results showed that the correlation coefficient of SWH between the buoy data and the ERA-Interim as well as the SWAN results is 0.94 and 0.98, respectively. The average SWH of the ERA-Interim data is about 51% of the buoy data and 70% of the SWAN results. The monthly averaged values of the spatial anomaly correlation coefficient (ACC) of the SWH between the ERA-Interim data and the SWAN results is 0.51. The ACC was minimal when the wind started, it boosted rapidly with increasing of the wind speed and reached the maximum before the wind speed reached the peak. Then the ACC turned to decrease at the peak wind speed. Integrated analysis imply that the ERA-Interim data can reflect the spatial distribution and the temporal variations trend of the SWH over the Taiwan Strait during this period, but it’s evidently smaller than the SWAN model data.

Black-hole eddy can be extracted based on elliptic Lagrangian Coherent Structures (eLCSs), which can transport material and maintain coherent under geostrophic for a long time. It was similar to the black hole in the ocean, so it was called black-hole eddy. In this paper, the boundary of black-hole eddy was extracted based on the data of the geostrophic flow velocity field. Using the method of eLCSs and choosing a targeted eddy (Eddy A) in the western Pacific to analyze. Sea surface temperature, sea surface salinity and chlorophyll concentration data are used to verify that the Eddy A is coherent in horizontal material transport. The temperature, salinity and dissolved oxygen data obtained by Argo in different depths are used to prove the coherence in vertical of Eddy A. The result demonstrates that the boundary of black-hole eddy is more coherent than Eulerian boundary in a long time scale and can describe the transport of material more objectively.

Sea fog is a kind of disastrous weather phenomenon which occurs on the sea surface. Mastering the distribution and dynamic changes of sea fog can effectively reduce the disasters caused by sea fog. Satellite remote sensing observation has the characteristics of near real time, wide coverage, continuous observation and so on. Especially the geostationary satellite remote sensing observation with high time resolution, which can continuously and dynamically track the occurrence, development and extinction of sea fog. The sea fog events in the Yellow Sea and Bohai Sea are taken from 2018 to 2019 as examples in this paper. Based on the analysis of the multi-channel bright temperature radiation characteristics of sea fog in the Yellow Sea and Bohai Sea by using Himawari-8 (H-8) geostationary satellite data, the separation index of sea fog and cloud, the separation index of sea fog and water, the slope index of multi-band brightness temperature difference and texture index of mid-infrared bright temperature are defined through the difference and ratio combination of different bands, and the night sea fog monitoring algorithm based on multi-exponential probability distribution is proposed to realize the automatic identification of sea fog at night. The algorithm is applied to H-8 and GEO-KOMPSAT2A (GK-2A) geostationary satellite data respectively. The position distribution and coverage area of sea fog identify by multi-time satellite observations of six sea fog events from February to June 2020 are compared to achieve mutual verification. The results show that the algorithm proposed in this paper can effectively recognize sea fog at night. The monitoring results every 10 minutes of continuous observations of H-8 and GK-2A at night on April 29, 2020 are selected to follow up and analyze the area where sea fog occurred, it shows the occurrence, development and evolution of the sea fog event clearly. It indicates that the algorithm can monitor the distribution of sea fog and track the development and change of fog. It can provide scientific basis and decision-making basis for the prevention and mitigation of sea fog.

The seabed soil layer will gradually accumulate pore pressure under the action of wave cyclic load, reduce the stability of the soil layer, and threaten offshore engineering. In order to study the accumulation mechanism of pore water pressure, the discrete element pore density flow method was proposed, and the discrete element analysis software MatDEM was improved to realize the simulation of the accumulation process of seabed sediment pore pressure. Based on the field test device and the mechanical parameters of the soil body, a discrete element model was established. By comparing field test and numerical simulation results, it was found that after applying the wave load to the seabed sediment, a higher pore pressure was generated in the surface soil body and gradually transferred to the deep layer. Under the action of cyclic wave load, the cumulative range of pore pressure between soil particles gradually increased. When the pore pressure accumulation time was long enough, the pore pressure in the soil layer converged to the average of the maximum and minimum loads applied. As the number of load cycles increased, the pore pressure at all depths increased cumulatively until the soil body liquefied and the internal soil particles became resuspended sediments. Under the action of periodic wave loads, the soil particles moved after being liquefied and suspended, and the shallow particles had a large displacement, and the overall performance of the soil was circular arc movement.

China-France Oceanography Satellite scatterometer (CSCAT) is the first rotating fan beam scatterometer internationally, which was flown onboard China-France Oceanography Satellite (CFOSAT) on October 2018. Based on the maximum likelihood estimation wind inversion algorithm, the residual characteristics of the CSCAT sea surface wind inversion cost function in detail, focuses on the influence of the new observation geometry on the wind inversion residual and wind quality is analyzed in this article, we establish the likelihood probability model function of the ambiguous solutions. The results show that the residual characteristic of the CSCAT wind inversion varies with the position of the wind vector cell (WVC) across the swath. The exponential distribution of the ambiguous solution likelihood probability model function is between −0.4 and −1.8. The results provide an important reference for the quality control of CSCAT and the refinement adjustment of the two dimensional variational ambiguity removal algorithm.

In this study, we quantify the mixed-layer salinity (MLS) budget in the Indian Ocean using the salinity budget equation along with Argo salinity, SODA ocean current, evaporation, and precipitation data. The results show that the distribution and seasonal variability for the terms of freshwater flux, advection and entrainment in the Indian Ocean, and their contributions to the variations of MLS. Regarding the climatological annual mean, the negative contribution (15.14%) of the horizontal advection term to MLS is much larger than its positive contribution (9.89%). This implies that the horizontal advection transports low-salinity water to the salty regions, resulting in a decrease in MLS there. The distribution and seasonal variability of the freshwater flux term are generally consistent with those of precipitation, with a positive contribution (13.70%) higher than negative contribution (7.81%). It suggests that the freshwater flux term increases MLS in the Indian Ocean because of the evaporation overwhelming the precipitation. Analysis on the regions with significant seasonal variations of MLS indicates that from June to November, the Southwest Monsoon Current transports low-salinity water from the western equatorial Indian Ocean to the western Arabian Sea, causing salinity in that region to decrease. The advection of high-salinity water from the southern and central to the northern of Bengal Bay is the main reason for the increase in salinity there.

The geochemistry, occurrence phase and enrichment mechanism of REE and PGE were studied in cobalt-rich crusts from the Seamount Xufu in the Pacific by ICP-OES, ICP-MS and phase analysis methods. The results showed that, REE and PGE were enriched in cobalt-rich crusts, REE contents were 1 842−2854 μg/g, and PGE contents were 144−1180 ng/g. REE and PGE contents in the old layers were higher than that in the new layers, and the phosphatization in the old layers might play an active role in the REE and PGE enrichment. Moreover, LREE contents were more than HREE contents, and REE diagrams showed the positive Ce anomalies and no Eu anomalies, so Ce was enriched in cobalt-rich crusts. Meanwhile, there was an obvious contrast between PGE, and PPGE contents were more than IPGE contents. PGE diagrams showed the positive Pt anomalies and negative Pd anomalies, so Pt was enriched and Pd was poor in cobalt-rich crusts. In addition, REE in the new layers were mainly enriched in the iron oxide phase, and the enrichment ratios were 65.40%−70.05%. While REE in the old layers were mainly enriched in the residual phase, and the enrichment ratios were 62.27%−65.77%, because it might be related to the phosphate. Meanwhile, PGE in the new or old layers were mainly enriched in the iron oxide phase, and the enrichment ratios were 63.66%−69.51%, and also the residual phase ranged from 29.20% to 34.68% had an impact on PGE enrichment. Therefore, REE and PGE enrichment were presumed to the iron oxide colloid particles adsorption. In the marine oxidative environment, the soluble Ce³⁺ and Pt²⁺ were oxidized to insoluble Ce⁴⁺ and Pt⁴⁺ respectively, and the precipitates were adsorbed into the iron oxide phase, so REE and PGE were enriched in cobalt-rich crusts.

The community structure of scleractinian corals in the southwest seawaters the of the Weizhou Island was analyzed with the data collected in a survey conducted with the method of line intercept transect from May 14 to 22, 2019. The results showed that 38 species of scleractinian corals in 9 families were found, dominated by mass corals such as porites sp., favites abdita, goniopora stutchburyi etc. The coverage of the living scleractinian corals ranged from 5.20% to 31.20%, the average coverage were 16.66%, higher at the sites far from or close to the shore but with deeper water. The living scleractinian coral had low recruitment rate, few diseases and low mortality rate. Species diversity, dominance and evenness of the scleractinian coral communities were positively correlated one another (p<0.05). The coverage and biodiversity of the living scleractinian corals were higher at the sites where anthropogenic disturbance was less, i.e. closer to the cliff, deeper water, fewer boating and diving etc. The living scleractinian corals closer to sandy beach influenced severely by suspended sediment on eroded coast and diving had the lowest coverage, the highest dominance of the dominant species and relatively lower diversity. Human activities, southwest monsoon, storm surge, suspended sediment on eroded coast and extreme weather are the main influential factors on the coral reef ecosystem in the southwest seawaters of the Weizhou Island.

Ocean waves can affect the roughness of the ocean surface, and the waves generated by tropical cyclones impact the momentum and energy fluxes across the air-sea interface. In this study, the impacts of ocean waves on the momentum and energy fluxes under tropical cyclones is examined by using the tropical cyclone observation dataset IBTrACS (International Best Track Archive for Climate Stewardship) and the simulations from wave model WW III (WAVEWATCH III). It is found that the intensity of tropical cyclones increased by about 1 m/s every decade in the past 30 years, but the change of translation speed is not obvious. For the stronger tropical cyclones, the difference for momentum flux and the energy flux between the air-sea interface can be significantly increased by the waves. Owing to the asymmetry of wind and surface wave fields under tropical cyclones, momentum difference and energy difference also demonstrate asymmetric distribution: the area with larger momentum difference is behind the moving direction of tropical cyclone, while energy difference is the largest in the right-rear quadrant, and both are relatively smaller in the left front quadrant. The inverse wave age is highly correlated with momentum difference and energy difference, and the correlation coefficient is about 0.95, indicating that the younger the surface wave, the more momentum and energy absorbed and stored by surface wave field. The inverse wave age increases with the increase of tropical cyclone translation speed, and the speed is positively correlated with momentum difference and energy difference according to the correlation coefficient above 0.8. Therefore, the surface waves affect the distribution and magnitude of momentum and energy input from the atmosphere to the ocean under tropical cyclones. In the future study of ocean boundary dynamics and thermodynamics, especially the study of tropical cyclones, considering the influence of ocean wave evolution is necessary.

Tuna is an important fishing target in China’s pelagic fishery. Its morphological indexes are of great significance for the study of the growth, development and life history of tunas. Manual measurement of morphological index is a very tedious and inefficient measurement method, while computer vision is an efficient and objective automatic measurement method. Therefore, in this paper, images of three Thunnus species are preprocessed by the computer vision library (OpenCV). It mainly uses image processing techniques such as bilateral filter, gray transformation, image binarization and contour extraction to obtain the contour image of tuna. According to the pre-selected feature points, the computer vision technology is used to traversal all the pixel points on the contour image, and 17 pre-selected feature points of each contour image are automatically located. By using the computer vision technology, the pixel length of the morphological index of the three species of tuna is automatically measured and the actual length of the morphological index is calculated. The absolute error and relative error between automatic measurement and manual measurement are compared and analyzed. The results show that the computer vision technique is effective in the automatic measurement of the morphological indexes of the three Thunnus species. The absolute error ranges of 12 morphological indices of Thunnus obesus, Thunnus albacores and Thunnus alalunga are 0.00−1.46 cm, 0−1.73 cm and 0−1.32 cm, respectively, and the relative error ranges are 0.01%−5.84%, 0%−6.17% and 0%−6.89%, respectively. It is expected to provide a basis for intelligent identification of tuna and a basic reference for automatic measurement of other fish.