Compressed gas is usually used for the pressure compensation of the deep-sea pressure-maintaining sampler. The pressure and volume of the recovered fluid sample are highly related to the precharged gas. To better understand the behavior of the gas under high pressure, we present a new real gas state equation based on the compression factor Z which was derived from experimental data. Then theoretical calculation method of the pressure and volume of the sample was introduced based on this empirical gas state equation. Finally, the proposed calculation method was well verified by the high-pressure vessel experiment of the sampler under 115 MPa.

Organic and inorganic carbon contents of marine sediments are important to reconstruct marine productivity, global carbon cycle, and climate change. A proper method to separate and determine organic and inorganic carbons is thus of great necessity. Although the best method is still disputable, the acid leaching method is widely used in many laboratories because of its ease-of-use and high accuracy. The results of the elemental analysis of sediment trap samples reveal that organic and inorganic carbon contents cannot be obtained using the acid leaching method, causing an infinitely amplified error when the carbon content of the decarbonated sample is 12%±1% according to a mathematical derivation. Acid fumigation and gasometric methods are used for comparison, which indicates that other methods can avoid this problem in organic carbon analysis. For the first time, this study uncovers the pitfalls of the acid leaching method, which limits the implication in practical laboratory measurement, and recommends alternative solutions of organic/inorganic carbon determination in marine sediments.

Secchi depth (SD, m) is a direct and intuitive measure of water’s transparency, which is also an indicator of water quality. In 2015, a semi-analytical model was developed to derive SD from remote sensing reflectance, thus able to provide maps of water’s transparency in satellite images. Here an in-situ dataset (338 stations) is used to evaluate its potential ability to monitor water quality in the coastal and estuarine waters, with measurements covering the Zhujiang (Pearl) River Estuary, the Yellow Sea and the East China Sea where measured SD values span a range of 0.2–21.0 m. As a preliminary validation result, according to the whole dataset, the unbiased percent difference (UPD) between estimated and measured SD is 23.3% (N=338, R²=0.89), with about 60% of stations in the dataset having relative difference (RD)≤20%, over 80% of stations having RD≤40%. Furthermore, by excluding the field data which with relatively larger uncertainties, the semi-analytical model yielded the UPD of 17.7% (N=132, R²=0.92) with SD range of 0.2–11.0 m. In addition, the semi-analytical model was applied to Landsat-8 images in the Zhujiang River Estuary, and retrieved high-quality mapping and reliable spatial-temporal patterns of water clarity. Taking into account the uncertainties associated with both field measurements and satellite data processing, and that there were no tuning of the semi-analytical model for these regions, these findings indicate highly robust retrieval of SD from spectral techniques for such turbid coastal and estuarine waters. The results suggest it is now possible to routinely monitor coastal water transparency or visibility at high-spatial resolutions from measurements, like Landsat-8 and Sentinel-2 and newly launched Gaofen-5.

With the rapid development of the global economy, maritime transportation has become much more convenient due to large capacities and low freight. However, this means the sea lanes are becoming more and more crowded, leading to high probabilities of marine accidents in complex maritime environments. According to relevant historical statistics, a large number of accidents have happened in water areas that lack high precision navigation data, which can be utilized to enhance navigation safety. The purpose of this work was to carry out ship route planning automatically, by mining historical big automatic identification system (AIS) data. It is well-known that experiential navigation information hidden in maritime big data could be automatically extracted using advanced data mining techniques; assisting in the generation of safe and reliable ship planning routes for complex maritime environments. In this paper, a novel method is proposed to construct a big data-driven framework for generating ship planning routes automatically, under varying navigation conditions. The method performs density-based spatial clustering of applications with noise first on a large number of ship trajectories to form different trajectory vector clusters. Then, it iteratively calculates its centerline in the trajectory vector cluster, and constructs the waterway network from the node-arc topology relationship among these centerlines. The generation of shipping route could be based on the waterway network and conducted by rasterizing the marine environment risks for the sea area not covered by the waterway network. Numerous experiments have been conducted on different AIS data sets in different water areas, and the experimental results have demonstrated the effectiveness of the framework of the ship route planning proposed in this paper.

In the past nearly two decades, the Argo Program has created an unprecedented global observing array with continuous in situ salinity observations, providing opportunities to extend our knowledge on the variability and effects of ocean salinity. In this study, we utilize the Argo data during 2004–2017, together with the satellite observations and a newly released version of ECCO ocean reanalysis, to explore the decadal salinity variability in the Southeast Indian Ocean (SEIO) and its impacts on the regional sea level changes. Both the observations and ECCO reanalysis show that during the Argo era, sea level in the SEIO and the tropical western Pacific experienced a rapid rise in 2005–2013 and a subsequent decline in 2013–2017. Such a decadal phase reversal in sea level could be explained, to a large extent, by the steric sea level variability in the upper 300 m. Argo data further show that, in the SEIO, both the temperature and salinity changes have significant positive contributions to the decadal sea level variations. This is different from much of the Indo-Pacific region, where the halosteric component often has minor or negative contributions to the regional sea level pattern on decadal timescale. The salinity budget analyses based on the ECCO reanalysis indicate that the decadal salinity change in the upper 300 m of SEIO is mainly caused by the horizontal ocean advection. More detailed decomposition reveals that in the SEIO, there exists a strong meridional salinity front between the tropical low-salinity and subtropical high salinity waters. The meridional component of decadal circulation changes will induce strong cross-front salinity exchange and thus the significant regional salinity variations.

A strong spring Wyrtki jet (WJ) presents in May 2013 in the eastern equatorial Indian Ocean. The entire buildup and retreat processes of the spring WJ were well captured by two adjacent Acoustic Doppler Current Profilers mounted on the mooring systems. The observed zonal jet behaved as one intraseasonal event with the significant features of abrupt emergence as well as slow disappearance. Further research illustrate that the pronounced surface westerly wind burst during late-April to mid-May, associated with the active phase of a robust eastward-propagating Madden–Julian oscillation in the tropical Indian Ocean, was the dominant reason for the rapid acceleration of surface WJ. In contrasting, the governing mechanism for the jet termination was equatorial wave dynamics rather than wind forcing. The decomposition analysis of equatorial waves and the corresponding changes in the ocean thermocline demonstrated that strong WJ was produced rapidly by the wind-generated oceanic downwelling equatorial Kelvin wave and was terminated subsequently by the westward-propagating equatorial Rossby wave reflecting from eastern boundaries of the Indian Ocean.

Interannual variability (IAV) in the barrier layer thickness (BLT) and forcing mechanisms in the eastern equatorial Indian Ocean (EEIO) and Bay of Bengal (BoB) are examined using monthly Argo data sets during 2002–2017. The BLT during November–January (NDJ) in the EEIO shows strong IAV, which is associated with the Indian Ocean dipole mode (IOD), with the IOD leading the BLT by two months. During the negative IOD phase, the westerly wind anomalies driving the downwelling Kelvin waves increase the isothermal layer depth (ILD). Moreover, the variability in the mixed layer depth (MLD) is complex. Affected by the Wyrtki jet, the MLD presents negative anomalies west of 85°E and strong positive anomalies between 85°E and 93°E. Therefore, the BLT shows positive anomalies except between 86°E and 92°E in the EEIO. Additionally, the IAV in the BLT during December–February (DJF) in the BoB is also investigated. In the eastern and northeastern BoB, the IAV in the BLT is remotely forced by equatorial zonal wind stress anomalies associated with the El Niño-Southern Oscillation (ENSO). In the western BoB, the regional surface wind forcing-related ENSO modulates the BLT variations.

The characteristics of the T/S structures, water mass exchange and deep circulation in the Andaman Sea are investigated based on the simulation from a high-resolution general circulation model (MITgcm). The results show that, below 1 000 m, the water mass is saltier, warmer and more homogeneous in the Andaman Sea than that in the Bay of Bengal, attributing to the strong vertical mixing at the depth of ~1 800 m. The water mass exchange between the Andaman Sea and the Bay of Bengal goes through three major channels, which manifests itself as follows: the northern channel (Preparis Channel) is the main passage of water mass transport from the Bay of Bengal to the Andaman Sea, whereas the Middle Channel (the south of Andaman Islands and the north of Nicobar Islands) has an opposite transport; the southern channel (Great Channel) features with a four-layer water exchange which results in the least net transport among the three channels; all the transports through the three channels have an intra-annual variation with a period of half a year. At 1 000-m depth, the entire Andaman Sea is occupied by a cyclonic circulation in January and July while by an anticyclonic one in April and October. The semiannual cycle found in both the deep circulation and water mass exchange is likely associated with the downwelling eastward-propagating Kelvin waves induced by the semiannual westerly component in the equatorial Indian Ocean during intermonsoon seasons.

Electron microprobe analysis was conducted on plagioclase from the plagioclase ultraphyric basalts (PUBs) erupted on the Southwest Indian Ridge (SWIR) (51°E) to investigate the geochemical changes in order to better understand the magmatic processes occurring under ultraslow spreading ridges and to provide insights into the thermal and dynamic regimes of the magmatic reservoirs and conduit systems. The phenocryst cores are generally calcic (An_74–82) and are depleted in FeO and MgO. Whereas the phenocryst rims (An_67–71) and the plagioclase in the groundmass (An_58–63) are more sodic and have higher FeO and MgO contents than the phenocryst cores. The crystallization temperatures of the phenocryst cores and the calculation of the equilibrium between the phenocrysts and the matrix suggest that the plagioclase cores are unlikely to have crystallized from the host basaltic melt, but are likely to have crystallized from a more calcic melt. The enrichment in incompatible elements (FeO and MgO), as well as the higher FeO/MgO ratios of the outermost phenocryst rims and the groundmass, are the result of plagioclase-melt disequilibrium diffusion during the short residence time in which the plagioclase crystallized. Our results indicate that an evolved melt replenishing under the SWIR (51°E) drives the eruption over a short period of time.