The compositional variability of ocean island basalts (OIBs) is thought to reflect partial melting of a lithologically-heterogeneous mantle source dominated by either pyroxenite or peridotite. The Pohnpei Island in Micronesia, which is associated with the Caroline hotspot, is suggested to have been generated from partial melting of a pyroxenite-rich mantle. To examine this hypothesis, we present new major- and trace-element compositions of olivine phenocrysts in basalts from the island. The olivines exhibit large systematic inter- and intra-crystalline compositional variability. In Sample DS1, olivines record compositional zonation, in which cores have relatively high Fo (77–85), Ni (550×10⁻⁶–2 392×10⁻⁶), and Fe/Mn ratios (66–82), whereas rims have lower Fo (71–78), Ni (526×10⁻⁶–1 537×10⁻⁶), and Fe/Mn ratios (51–62). By contrast, olivines within other samples preserve no clear compositional zonation, exhibiting similar or slightly lower Fo values (66–78), Ni contents (401×10⁻⁶–1 268×10⁻⁶), and Fe/Mn ratios (53–69) as the rims of zoned crystals. The distinct chemical contrast between the two different types of olivine suggests they formed in magma chambers at different depths. Analysis using forward petrological modeling and multi-element indicators (Fe/Mn, Zn/Fe, FC3MS (FeO^T/CaO−(3×MgO/SiO₂)), Mn/Zn, and Ni/(Mg/Fe)) of whole-rock samples and high-Fo olivines is inconsistent with a pyroxenite-rich mantle source. We suggest these inconsistencies reflect an influence on the partition coefficients of Ni and Mn between olivine and liquid during melting at variable pressures and temperatures. In addition, magma recharge and mixing within the magmatic plumbing system can change the composition of olivine. We suggest that identification of the mantle source of OIBs in volcanic islands such as the Pohnpei Island using olivine geochemistry should be treated with caution.

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.

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.

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.

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.

The systematic discrepancies in both tsunami arrival time and leading negative phase (LNP) were identified for the recent transoceanic tsunami on 16 September 2015 in Illapel, Chile by examining the wave characteristics from the tsunami records at 21 Deep-ocean Assessment and Reporting of Tsunami (DART) sites and 29 coastal tide gauge stations. The results revealed systematic travel time delay of as much as 22 min (approximately 1.7% of the total travel time) relative to the simulated long waves from the 2015 Chilean tsunami. The delay discrepancy was found to increase with travel time. It was difficult to identify the LNP from the near-shore observation system due to the strong background noise, but the initial negative phase feature became more obvious as the tsunami propagated away from the source area in the deep ocean. We determined that the LNP for the Chilean tsunami had an average duration of 33 min, which was close to the dominant period of the tsunami source. Most of the amplitude ratios to the first elevation phase were approximately 40%, with the largest equivalent to the first positive phase amplitude. We performed numerical analyses by applying the corrected long wave model, which accounted for the effects of seawater density stratification due to compressibility, self-attraction and loading (SAL) of the earth, and wave dispersion compared with observed tsunami waveforms. We attempted to accurately calculate the arrival time and LNP, and to understand how much of a role the physical mechanism played in the discrepancies for the moderate transoceanic tsunami event. The mainly focus of the study is to quantitatively evaluate the contribution of each secondary physical effect to the systematic discrepancies using the corrected shallow water model. Taking all of these effects into consideration, our results demonstrated good agreement between the observed and simulated waveforms. We can conclude that the corrected shallow water model can reduce the tsunami propagation speed and reproduce the LNP, which is observed for tsunamis that have propagated over long distances frequently. The travel time delay between the observed and corrected simulated waveforms is reduced to <8 min and the amplitude discrepancy between them was also markedly diminished. The incorporated effects amounted to approximately 78% of the travel time delay correction, with seawater density stratification, SAL, and Boussinesq dispersion contributing approximately 39%, 21%, and 18%, respectively. The simulated results showed that the elastic loading and Boussinesq dispersion not only affected travel time but also changed the simulated waveforms for this event. In contrast, the seawater stratification only reduced the tsunami speed, whereas the earth’s elasticity loading was responsible for LNP due to the depression of the seafloor surrounding additional tsunami loading at far-field stations. This study revealed that the traditional shallow water model has inherent defects in estimating tsunami arrival, and the leading negative phase of a tsunami is a typical recognizable feature of a moderately strong transoceanic tsunami. These results also support previous theory and can help to explain the observed discrepancies.

We present major and trace element data of lava recovered from the northern Yap Trench in the western Pacific and discuss their petrogenesis and tectonic implications within the framework of interactions between the Caroline Ridge and Yap Trench. Rocks were collected from both landward and seaward trench slopes and exhibited geochemical characteristics similar to backarc basin basalt (BABB) and mid-ocean ridge basalt (MORB), including high Fe content, tholeiitic affinity, high TiO₂ value at a given FeO_T/MgO ratio, Ti/V ratio between 20 and 50, low Ba/Nb ratio and Th/Nb ratio, and trace element patterns commonly displayed by BABB and MORB, which are distinct from arc lava. These rocks seem to have been generated during mantle upwelling and decompression melting at a spreading center. However, compared with typical forearc lava produced by seafloor spreading in the Mariana forearc region, such as the early Eocene forearc basalts and late Neogene forearc lava in the southernmost Mariana Trench, the Yap Trench lava is derived from a more fertile mantle and feature a more minor subduction component; thus, they cannot be the products of forearc mantle decompression melting. We suggest that the landward slope lava represents backarc basin crust that was overthrust onto the forearc lithosphere during the collision of the Caroline Ridge with the Yap Trench (20–25 Ma), which played a key role in the evolution of the Yap subduction system. Moreover, the seaward slope lava represents the subduction plate crust that accreted onto the deep trench during the collision. This collision event resulted in the cessation of Yap Arc magmatism; thus, the Yap Trench volcanic rocks (<25 Ma) previously suggested to be arc magma products may actually represent the nascent island arc lava with a lower subduction component than in the mature Mariana Arc lava.

The spatial distribution of eddy diffusivity, basic characteristics of coherent mesoscale eddies and their relationship are analyzed from numerical model outputs in the Southern Ocean. Mesoscale fluctuation information is obtained by a temporal-spatial filtering method, and the eddy diffusivity is calculated using a linear regression analysis between isoneutral thickness flux and large-scale isoneutral thickness gradient. The eddy diffusivity is on the order of O (10³ m²/s) with a significant spatial variation, and it is larger in the area with strong coherent mesoscale eddy activity. The mesoscale eddies are mainly located in the upper ocean layer, with the average intensity no larger than 0.2. The mean radius of the coherent mesoscale cyclonic (anticyclonic) eddy gradually decays from (121.2±10.4) km ((117.8±9.6) km) at 30°S to (43.9±5.3) km ((44.7±4.9) km) at 65°S. Their vertical penetration depths (lifespans) are deeper (longer) between the northern side of the Subpolar Antarctic Front and 48°S. The normalized eddy diffusivity and coherent mesoscale eddy activity show a significant positive correlation, indicating that coherent mesoscale eddy plays an important role in eddy diffusivity.

Oyster reefs and their spatial patterns are deemed to change the local hydrodynamic condition and exert profound impacts on the grain size, concentration and transportation of suspended sediments. Meanwhile, high suspended sediment concentration often results in excess mortality among oysters. Oyster reefs are rare and vital ecosystem in Liyashan national marine park, Jiangsu Coast, China. However, urgent conservation efforts should be made on account of the drastic reduction in reef areas. To investigate the sediment dynamics and the geomorphology, two tripod observation systems were deployed and UAV aerial surveys with elevation measurement using Real Time Kinematic (RTK) were also carried out. High mud content (60%) was found in the bed sediment at the reef ridge, causing much lower drag coefficient than other recorded values of living oyster reefs, indicating the death of oysters and the degradation of reefs in Liyashan. Ridgelines of the string reefs at 45° to the current direction and high suspended sediment concentration in the water body (50–370 mg/L) that exceeds the threshold (200 mg/L), which would affect nutrient uptake efficiency and further result in gill saturation, decrease of clearance rate and associated deposition, were probably crucial causes of the death of oysters. The findings are useful for restoring natural oyster reefs and designing artificial reefs for nature-based coastal defense.

Spilled oil floats and travels across the water’s surface under the influence of wind, currents, and wave action. Wave-induced Stokes drift is an important physical process that can affect surface water particles but that is currently absent from oil spill analyses. In this study, two methods are applied to determine the velocity of Stokes drift, the first calculates velocity from the wind-related formula based upon a one-dimensional frequency spectrum, while the second determines velocity directly from the wave model that was based on a two-dimensional spectrum. The experimental results of numerous models indicated that: (1) oil simulations that include the influence of Stokes drift are more accurate than that those do not; (2) for medium and long-term simulations longer than two days or more, Stokes drift is a significant factor that should not be ignored, and its magnitude can reach about 2% of the wind speed; (3) the velocity of Stokes drift is related to the wind but is not linear. Therefore, Stokes drift cannot simply be replaced or substituted by simply increasing the wind drift factor, which can cause errors in oil spill projections; (4) the Stokes drift velocity obtained from the two-dimensional wave spectrum makes the oil spill simulation more accurate.