The tropical Pacific Ocean supports many productive commercial fisheries. However, few studies of ecosystem structure in the tropical Pacific Ocean have been carried out. In this study, we analyzed the food web structure in the central and eastern tropical Pacific Ocean based on trophic relationships of 35 pelagic species collected by Chinese tuna longline observers from June to November in 2017. Topology indices (node degree, D; centrality indices, BC and CC; topological importance indices, TI¹, TI³; keystone indices, K, K_t and K_b) and Key-Player algorithms (KPP-1, KPP-2) were used to select key species and construct a simplified food web combined with body size data. The Kendall rank correlation and hierarchical clustering analysis indicated that different topology indices resulted in consistent rankings of key species. Most key species were the same as those selected in other studies in the Pacific Ocean, such as Shortbill spearfish (Tetrapturus angustirostris), Swordfish (Xiphias gladius), Albacore tuna (Thunnus alalunga), cephalopods and scomber. The food web would be separated into many unconnected parts (F=0.632, F^D=0.795, R^D=0.957) after the removal of the five key species, indicating the key roles of these species in the food web structure and stability. Body size was considered an influential indicator in constructing the simplified food web. This study can improve our understanding of the food web structure in the tropical Pacific Ocean and provide scientific basis for further ecosystem dynamics studies.

Habitat suitability index (HSI) models have been widely used to analyze the relationship between species abundance and environmental factors, and ultimately inform management of marine species. The response of species abundance to each environmental variable is different and habitat requirements may change over life history stages and seasons. Therefore, it is necessary to determine the optimal combination of environmental variables in HSI modelling. In this study, generalized additive models (GAMs) were used to determine which environmental variables to be included in the HSI models. Significant variables were retained and weighted in the HSI model according to their relative contribution (%) to the total deviation explained by the boosted regression tree (BRT). The HSI models were applied to evaluate the habitat suitability of mantis shrimp Oratosquilla oratoria in the Haizhou Bay and adjacent areas in 2011 and 2013–2017. Ontogenetic and seasonal variations in HSI models of mantis shrimp were also examined. Among the four models (non-optimized model, BRT informed HSI model, GAM informed HSI model, and both BRT and GAM informed HSI model), both BRT and GAM informed HSI model showed the best performance. Four environmental variables (bottom temperature, depth, distance offshore and sediment type) were selected in the HSI models for four groups (spring-juvenile, spring-adult, fall-juvenile and fall-adult) of mantis shrimp. The distribution of habitat suitability showed similar patterns between juveniles and adults, but obvious seasonal variations were observed. This study suggests that the process of optimizing environmental variables in HSI models improves the performance of HSI models, and this optimization strategy could be extended to other marine organisms to enhance the understanding of the habitat suitability of target species.

The West Pacific Ocean is considered as the provenance center of global marine life and has the highest species diversity of numerous marine taxa. The phytoplankton, as the primary producer at the base of the food chain, effects on climate change, fish resources as well as the entire ecosystem. However, there are few large-scale surveys covering several currents with different hydrographic characteristics. This study aimed to explore the relationships between the spatio-temporal variation in phytoplankton community structure and different water masses. A total of 630 water samples and 90 net samples of phytoplankton were collected at 45 stations in the Northwest Pacific Ocean (21.0°–42.0°N, 118.0°–156.0°E) during spring and summer 2017. A total of 281 phytoplankton taxa (>5 μm) belonging to 61 genera were identified in the study area. The distribution pattern of the phytoplankton community differed significantly both spatially and temporally. The average abundances of phytoplankton in spring and summer were 797.07×10² cells/L and 84.94×10² cells/L, respectively. Whether in spring or summer, the maximum abundance always appeared in the northern transition region affected by the Oyashio Current, where nutrients were abundant and diatoms dominated the phytoplankton community; whereas the phytoplankton abundance was very low in the oligotrophic Kuroshio region, and the proportion of dinoflagellates in total abundance increased significantly. The horizontal distribution of phytoplankton abundance increased from low to high latitudes, which was consistent with the trend of nutrient distributions, but contrary to that of water temperature and salinity. In the northern area affected by the Oyashio Current, the phytoplankton abundance was mainly concentrated in the upper 30 m of water column, while the maximum abundance often occurred at depths of 50–75 m in the south-central area affected by the Kuroshio Current. Pearson correlation and redundancy analysis (RDA) showed that phytoplankton abundance was significant negatively correlated with temperature and salinity, but positively correlated with nutrient concentration. The phytoplankton community structure was mainly determined by nutrient availability, especially the N:P ratio.

A new paradigm for ship detection in polarimetric synthetic aperture radar (Pol-SAR) image is presented. We firstly utilize the scattering similarity parameters to investigate the differences of scattering mechanism between ships and sea clutter. Based on these differences, we propose a novel ship detection metric, denoted as the scattering similarity based metric (SSM), to conduct ship detection task. The distribution model of SSM metric is investigated and modeled by kernel density estimation (KDE). Based on the statistical distribution, an adaptive constant false alarm rate (CFAR) detection scheme is implemented. We compare the proposed SSM with two classic polarimetric metrics, i.e., the polarimetric cross-entropy (PCE) and the reflection symmetry metric (RSM). The experimental results conducted on C-band RADARSAT-2 Pol-SAR data demonstrate the feasibility and advantage of the proposed SSM metric both in sea clutter modeling and in ship detection.

This study explores the influence of Stokes drift and the thermal effects on the upper ocean bias which occurs in the summer with overestimated sea surface temperature (SST) and shallower mixed layer depth (MLD) using Mellor-Yamada turbulence closure scheme. The upper ocean thermal structures through Princeton ocean model are examined by experiments in the cases of idealized forcing and real observational situation. The results suggest that Stokes drift can generally enhance turbulence kinetic energy and deepen MLD either in summer or in winter. This effect will improve the simulation results in summer, but it will lead to much deeper MLD in winter compared to observational data. It is found that MLD can be correctly simulated by combining Stokes drift and the thermal effects of the cool skin layer and diurnal warm layer on the upper mixing layer. In the case of high shortwave radiation and weak wind speed, which usually occurs in summer, the heat absorbed from sun is blocked in the warm layer and prevented from being transferred downwards. As a result, the thermal effects in summer nearly has no influence on dynamic effect of Stokes drift that leads to deepening MLD. However, when the stratification is weak in winter, the thermal effects will counteract the dynamic effect of Stokes drift through enhancing the strength of stratification and suppress mixing impact. Therefore, the dynamic and thermal effects should be considered simultaneously in order to correctly simulate upper ocean thermal structures in both summer and winter.

The present study reveals the fact that the relationship between the spring (April–May) North Atlantic Oscillation (NAO) and the following summer (June–September) tropical cyclone (TC) genesis frequency over the western North Pacific (WNP) during the period of 1950–2018 was not stationary. It is shown that the relationship between the two has experienced a pronounced interdecadal shift, being weak and insignificant before yet strong and statistically significant after the early 1980s. Next we compare the spring NAO associated dynamic and thermodynamic conditions, sea surface temperature (SST) anomalies, and atmospheric circulation processes between the two subperiods of 1954–1976 and 1996–2018, so as to illucidate the possible mechanism for this interdecadal variation in the NAO-TC connection. During the latter epoch, when the spring NAO was positive, enhanced low-level vorticity, reduced vertical zonal wind shear, intensified vertical velocity and increased middle-level relative humidity were present over the WNP in the summer, which is conducive to the genesis of WNP TCs. When the spring NAO is negative, the dynamic and thermodynamic factors are disadvantageous for the summertime TC formation and development over the WNP. The results of further analysis indicate that the persistence of North Atlantic tri-pole SST anomalies from spring to the subsequent summer induced by the spring NAO plays a fundamental role in the linkage between the spring NAO and summer atmospheric circulation. During the period of 1996–2018, a remarkable eastward propagating wave-train occurred across the northern Eurasian continent, forced by the anomalous SST tri-pole in the North Atlantic. The East Asian jet flow became greatly intensified, and the deep convection in the tropics was further enhanced via the changes of the local Hadley circulation, corresponding to a positive spring NAO. During the former epoch, the spring NAO-induced tri-pole SST anomalies in the North Atlantic were non-existent, and the related atmospheric circulation anomalies were extremely weak, thereby leading to the linkage between spring NAO and WNP TC genesis frequency in the following summer being insignificant.

The objectives of this study are carried out a series of controlled large wave flume experiments using fine-grained sediment from the Huanghe River Delta, exploring the complete sequence of sediment behavior in the bottom boundary layer (BBL) during wave-induced liquefaction. The results show that: (1) The BBL in silty seabed is exposed to a progressive wave, goes through a number of different stages including compaction before liquefaction, sediment liquefaction, and compaction after liquefaction, which determines the range and thickness of BBL. (2) With the introduction of waves, first, the sediment surface has settled by an amount S (S=1–2 cm) in the course of wave loadings with an insufficient accumulation of pore water pressure. And a thin high concentration layer formed the near-bed bottom. (3) Once the liquefaction sets in, the liquefied sediment with an ‘orbital motion’ and the sub-liquefied sediment form a two-layer-sediment region. The range of BBL extends downwards and stopped at a certain depth, subsequently, develops upwards with the compaction process. Meanwhile, re-suspended sediments diffuse to the upper water column. (4) During the dynamics process of the BBL beneath progressive waves, the re-suspended sediment increment ranked as sediment liquefaction > erosion before liquefaction > compaction after liquefaction.

The accuracy of typhoon forecasts plays an important role in the prediction of storm surges. The uncertainty of a typhoon’s intensity and track means it is necessary to use an ensemble model to predict typhoon storm surges. A hydrodynamic model, which is operational at the National Marine Environmental Forecasting Center, is applied to conduct surge simulations for South China coastal areas using the best track data with parametric wind and pressure models. The results agree well with tidal gauge observations. To improve the calculation efficiency, the hydrodynamic model is modified using CUDA Fortran. The calculation results are almost the same as those from the original model, but the calculation time is reduced by more than 99%. A total of 150 typhoon cases are generated by combining 50 typhoon tracks from the European Centre for Medium-Range Weather Forecasts with three possible typhoon intensity forecasts. The surge ensembles are computed by the improved hydrodynamic model. Based on the simulated storm surges for the different typhoon cases, ensemble and probability forecast products can be provided. The mean ensemble results and probability forecast products are shown to agree well with the observed storm surge caused by Typhoon Mangkhut. The improved model is highly suitable for ensemble numerical forecasts, providing better forecast products for decision-making, and can be easily implemented to run on regular workstations.

In shallow coastal regions where water surface fluctuations are non-negligible compared to the mean water depth, the use of sigma coordinates allows the calculation of residual velocity around the mean water surface level. Theoretical analysis and generic numerical experiments were conducted to understand the physical meaning of the residual velocities at sigma layers in breadth-averaged tidal channels. For shallow water waves, the sigma layers coincide with the water wave surfaces within the water column such that the Stokes velocity and its vertical and horizontal components can be expressed in discrete forms using the sigma velocity. The residual velocity at a sigma layer is the sum of the Eulerian velocity and the vertical component of the Stokes velocity at the mean depth of the sigma layer and, therefore, can be referred to as a semi-Lagrangian residual velocity. Because the vertical component of the Stokes velocity is one order of magnitude smaller than the horizontal component, the sigma residual velocity approximates the Eulerian residual velocity. The residual transport velocity at a sigma layer is the sum of the sigma residual velocity and the horizontal component of the Stokes velocity and approximates the Lagrangian residual velocity in magnitude and direction, but the two residual velocities are not conceptually the same.

This study compares the seasonal and interannual-to-decadal variability in the strength and position of the Kuroshio Extension front (KEF) using high-resolution satellite-derived sea surface temperature (SST) and sea surface height (SSH) data. Results show that the KEF strength has an obvious seasonal variation that is similar at different longitudes, with a stronger (weaker) KEF during the cold (warm) season. However, the seasonal variation in the KEF position is relatively weak and varies with longitude. In contrast, the low-frequency variation of the KEF position is more distinct than that of the KEF strength even though they are well correlated. On both seasonal and interannual-to-decadal time scales, the western part of the KEF (142°–144°E) has the greatest variability in strength, while the eastern part of the KEF (149°–155°E) has the greatest variability in position. In addition, the relationships between wind-forced Rossby waves and the low-frequency variability in the KEF strength and position are also discussed by using the statistical analysis methods and a wind-driven hindcast model. A positive (negative) North Pacific Oscillation (NPO)-like atmospheric forcing generates positive (negative) SSH anomalies over the central North Pacific. These oceanic signals then propagate westward as Rossby waves, reaching the KE region about three years later, favoring a strengthened (weakened) and northward (southward)-moving KEF.