Many seamounts are covered with cobalt-rich ferromanganese crusts, and are increasingly attracting interest for the potential extraction of valuable mineral resources from deep seabed environments. However, the impacts of potential mining activities on the vulnerable seamount ecosystem remain unclear. To enhance the understanding of connectivity in benthic invertebrate populations in the Northwest Pacific, several seamounts were surveyed and biological samples collected. In the present study, the ophiuroid species Ophioplinthaca defensor is reported for the first time from four deep seamounts in the Northwest Pacific, and described, providing more detailed morphological diagnosis characters. To assess the population structure of the species between and within seamounts, two mitochondrial markers (COI and 16S) were sequenced. In total, 20 haplotypes from 32 COI sequences and 8 haplotypes from 37 16S sequences were recovered. The star-shaped TCS networks and non-significant pairwise population differences reveal the absence of distinct population structures between and within seamounts. In addition, the O. defensor population seemed to have undergone a demographic expansion in history. This is the first study on the genetic population structure of a benthic invertebrate from seamounts in the Northwest Pacific, and this results suggest a potentially high, long distance dispersal capacity in O. defensor between seamounts, which could inform the development of the Regional Environmental Management Plans for the cobalt-rich crust seamounts in the area.

In order to satisfy the increasing demand for the marine forecasting capacity, the Bohai Sea, the Yellow Sea and the East China Sea Operational Oceanography Forecasting System (BYEOFS) has been upgraded and improved to Version 2.0. Based on the Regional Ocean Modeling System (ROMS), a series of comparative experiments were conducted during the improvement process, including correcting topography, changing sea surface atmospheric forcing mode, adjusting open boundary conditions, and considering atmospheric pressure correction. (1) After the topography correction, the volume transport and meridional velocity maximum of Yellow Sea Warm Current increase obviously and the unreasonable bending of its axis around 36.1°N, 123.5°E disappears. (2) After the change of sea surface forcing mode, an effective negative feedback mechanism is formed between predicted sea surface temperature (SST) by the ocean model and sea surface radiation fluxes fields. The simulation errors of SST decreased significantly, and the annual average of root-mean-square error (RMSE) decreased by about 18%. (3) The change of the eastern lateral boundary condition of baroclinic velocity from mixed Radiation-Nudging to Clamped makes the unreasonable westward current in Tsushima Strait disappear. (4) The adding of mean sea level pressure correction option which forms the mean sea level gradient from the Bohai Sea and the Yellow Sea to the western Pacific in winter and autumn is helpful to increasing the fluctuation of SLA and outflow of the Yellow Sea when the cold high air pressure system controls the Yellow Sea area.

Ceuthonoe, a new genus with type species C. nezhai sp. n. commensal with euplectellid glass sponge (Hexactinellida: Euplectellidae), is described and illustrated, based on the material collected from Weijia Guyot, western Pacific. The new genus is distinguished by a combination of characters: body with 32 segments; 14 pairs of elytra; prostomium with prominent cephalic peaks and facial tubercle; aciculae and chaetae on tentaculophores; biramous parapodium, each ramus with a long aciculum penetrating epidermis, without supra- or subacicular process; and noto- and neurochaetae with unidentate tips. Ceuthonoe gen. n. is mostly silimar to genera of Polynoinae in morphology. However the phylogenetic analysis based on cytochrome c oxidase subunit I, 16S, 18S, and 28S genes suggested that this new genus was separated from the main branch of Polynoinae. The study also discussed the genera related to the new genus.

Storm surges pose significant danger and havoc to the coastal residents’ safety, property, and lives, particularly at offshore locations with shallow water levels. Predictions of storm surges with hours of warning time are important for evacuation measures in low-lying regions and coastal management plans. In addition to experienced predictions and numerical models, artificial intelligence (AI) techniques are also being used widely for short-term storm surge prediction owing to their merits in good level of prediction accuracy and rapid computations. Convolutional neural network (CNN) and long short-term memory (LSTM) are two of the most important models among AI techniques. However, they have been scarcely utilised for surge level (SL) forecasting, and combinations of the two models are even rarer. This study applied CNN and LSTM both individually and in combination towards multi-step ahead short-term storm surge level prediction using observed SL and wind information. The architectures of the CNN, LSTM, and two sequential techniques of combining the models (LSTM–CNN and CNN–LSTM) were constructed via a trial-and-error approach and knowledge obtained from previous studies. As a case study, 11 a of hourly observed SL and wind data of the Xiuying Station, Hainan Province, China, were organised as inputs for training to verify the feasibility and superiority of the proposed models. The results show that CNN and LSTM had evident advantages over support vector regression (SVR) and multilayer perceptron (MLP), and the combined models outperformed the individual models (CNN and LSTM), mostly by 4%–6%. However, on comparing the model computed predictions during two severe typhoons that resulted in extreme storm surges, the accuracy was found to improve by over 10% at all forecasting steps.

The present climate simulation and future projection of the mixed layer depth (MLD) and subduction process in the subtropical Southeast Pacific are investigated based on the geophysical fluid dynamics laboratory earth system model (GFDL-ESM2M). The MLD deepens from May and reaches its maximum (>160 m) near (24°S, 104°W) in September in the historical simulation. The MLD spatial pattern in September is non-uniform in the present climate, which shows three characteristics: (1) the deep MLD extends from the Southeast Pacific to the West Pacific and leads to a “deep tongue” until 135°W; (2) the northern boundary of the MLD maximum is smoothly near 18°S, and MLD shallows sharply to the northeast; (3) there is a relatively shallow MLD zone inserted into the MLD maximum eastern boundary near (26°S, 80°W) as a weak “shallow tongue”. The MLD non-uniform spatial pattern generates three strong MLD fronts respectively in the three key regions, promoting the subduction rate. After global warming, the variability of MLD spatial patterns is remarkably diverse, rather than deepening consistently. In all the key regions, the MLD deepens in the south but shoals in the north, strengthing the MLD front. As a result, the subduction rate enhances in these areas. This MLD antisymmetric variability is mainly influenced by various factors, especially the potential-density horizontal advection non-uniform changes. Notice that the freshwater flux change helps to deepen the MLD uniformly in the whole basin, so it hardly works on the regional MLD variability. The study highlights that there are regional differences in the mechanisms of the MLD change, and the MLD front change caused by MLD non-uniform variability is the crucial factor in the subduction response to global warming.

Authigenic carbonate samples were collected from the northern Okinawa Trough. Based on their carbon and oxygen isotopes, these samples were found to be methane-related carbonates precipitated by the anaerobic oxidation of methane (AOM). Petrological analysis revealed numerous framboidal pyrites that had been partly oxidized. In order to trace the variation and diagenetic information of these framboidal pyrites, their diameters and geochemical components were studied using an electron probe. The results showed that their diameters varied from 4 µm to 17 µm (n = 60; geometric mean of 9.9 µm) and were of a normal distribution. The diameters of single pyrite that formed the framboidal pyrites varied from 1 µm to 2 µm. The framboidal pyrites with diameters of 6–14 µm accounted for ~80% of the total. The geometric mean of 9.9 µm indicates that they are probably diagenetic pyrites that were precipitated in a lower dysoxic environment (weakly oxygenated bottom waters). The S/Fe ratio of the framboidal minerals ranged from 0 to 1.67, and the pyrite content of single framboid varied between 0% and 86.4%. Therefore, numerous pyrites were oxygenated to iron oxides or oxyhydroxides, and were retained as pseudomorphism pyrites. The size of framboidal pyrites precipitated in cold seeps can be used to trace the redox environment; however, acquisition of additional data via investigation of different cold seeps is necessary to obtain more persuasive results.

The sea ice conditions in the Kara Sea have important impacts on Arctic shipping, oil and gas production, and marine environmental changes. In this study, sea ice coverage (C_R) less than 30% is considered as open water, its onset and end dates are defined as T_open and T_close, respectively. The sea ice melt onset (T_melt) is defined as the date when ice-sea freshwater flux initially changes from ice into the ocean. Satellite-based sea ice concentration (SIC) from 1989 to 2019 shows a negative correlation between T_open and T_close (r = –0.77, p < 0.01) in the Kara Sea. This phenomenon is also obtained through analyzing the hindcast simulation from 1994 to 2015 by a coupled ocean and sea-ice model (NAPA1/4). The model results reveal that thermodynamics dominate the sea ice variations, and ice basal melt is greater than the ice surface melt. Heat budget estimation suggests that the heat flux is significant correlated with T_open (r = –0.95, p < 0.01) during the melt period (the duration of multi-year averaged T_melt to T_open) influenced by the sea ice conditions. Additionally, this heat flux is also suggested to dominate the interannual variation of the heat input during the whole heat absorption process (r = 0.81, p < 0.01). The more heat input during this process leads to later T_close (r = 0.77, p < 0.01). This is the physical basis of the negative correlation between T_open and T_close. Therefore, the duration of open water can be predicted by T_open and thence support earlier planning of marine activities.

The influences of the three types of reanalysis wind fields on the simulation of three typhoon waves occurred in 2015 in offshore China were numerically investigated. The typhoon wave model was based on the simulating waves nearshore model (SWAN), in which the wind fields for driving waves were derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis-Interim (ERA-interim), the National Centers for Environmental Prediction climate forecast system version 2 (CFSv2) and cross-calibrated multi-platform (CCMP) datasets. Firstly, the typhoon waves generated during the occurrence of typhoons Chan-hom (1509), Linfa (1510) and Nangka (1511) in 2015 were simulated by using the wave model driven by ERA-interim, CFSv2 and CCMP datasets. The numerical results were validated using buoy data and satellite observation data, and the simulation results under the three types of wind fields were in good agreement with the observed data. The numerical results showed that the CCMP wind data was the best in simulating waves overall, and the wind speeds pertaining to ERA-Interim and CCMP were notably smaller than those observed near the typhoon centre. To correct the accuracy of the wind fields, the Holland theoretical wind model was used to revise and optimize the wind speed pertaining to the CCMP near the typhoon centre. The results indicated that the CCMP wind-driven SWAN model could appropriately simulate the typhoon waves generated by three typhoons in offshore China, and the use of the CCMP/Holland blended wind field could effectively improve the accuracy of typhoon wave simulations.

In this paper, an ice floe inner stress caused by the wave-induced bending moment is derived to estimate the stress failure of ice floe. The strain and stress failures are combined to establish a wave-induced ice yield scheme. We added ice stress and strain failure module in the Finite-Volume Community Ocean Model (FVCOM), which already includes module of ice-induced wave attenuation. Thus a fully coupled wave-ice dynamical interaction model is established based on the ice and wave modules of FVCOM. This model is applied to reproduce the ice and wave fields of the breakup events observed during the second Sea Ice Physics and Ecosystem Experiment (SIPEX-2) voyage. The simulation results show that by adopting the combined wave-induced ice yield scheme, the model can successfully predict the ice breakup events, which the strain failure model is unable to predict. By comparing the critical significant wave height deduced from strain and stress failure schemes, it is concluded that the ice breakup is caused by the strain failure when wave periods are shorter than a threshold value, while the stress failure is the main reason for the ice breakup when wave periods are longer than the threshold value. Neglecting either of these two ice-break inducement mechanisms could overestimate the ice floe size, and thus underestimate the velocity of the ice lateral melt and increase the error of simulation of polar ice extent.

Ocean currents are a key element in ocean processes and in meteorology, affecting material transport and modulating climate change patterns. The Doppler frequency shift information of the synthetic aperture radar (SAR) echo signal can reflect the dynamic characteristics of the sea surface, and has become an essential sea surface dynamic remote sensing parameter. Studies have verified that the instantaneous Doppler frequency shift can realize the SAR detection of the sea surface current. However, the validation of SAR-derived ocean current data and a thorough analysis of the errors associated with them remain lacking. In this study, we derive high spatial resolution flow measurements for the Kuroshio in the East China Sea from SAR data using a theoretical model of shifts in Doppler frequency driven by ocean surface current. Global ocean multi observation (MOB) products and global surface Lagrangian drifter (GLD) data are used to validate the Kuroshio flow retrieved from the SAR data. Results show that the central flow velocity for the Kuroshio derived from the SAR is 0.4–1.5 m/s. The error distribution between SAR ocean currents and MOB products is an approximate standard normal distribution, with the 90% confidence interval concentrated between –0.1 m/s and 0.1 m/s. Comparative analysis of SAR ocean current and GLD products, the correlation coefficient is 0.803, which shows to be significant at a confidence level of 99%. The cross-validation of different ocean current dataset illustrate that the SAR radial current captures the positions and dynamics of the Kuroshio central flow and the Kuroshio Counter Current, and has the capability to monitor current velocity over a wide range of values.