Hydrothermal plumes released from the eruption of sea floor hydrothermal fluids contain large amounts of ore-forming materials. They precipitate within certain distances from the hydrothermal vent. Six surficial sediment samples from the Southwest Indian Ridge (SWIR) were analyzed by a portable X-ray fluorescence (PXRF) analyzer on board to find a favorable method fast and efficient enough for sea floor sulfide sediment geochemical exploration. These sediments were sampled near, at a moderate distance from, or far away from hydrothermal vents. The results demonstrate that the PXRF is effective in determining the enrichment characteristics of the ore-forming elements in the calcareous sediments from the mid-ocean ridge. Sediment samples (>40 mesh) have high levels of elemental copper, zinc, iron, and manganese, and levels of these elements in sediments finer than 40 mesh are lower and relatively stable. This may be due to relatively high levels of basalt debris/glass in the coarse sediments, which are consistent with the results obtained by microscopic observation. The results also show clear zoning of elements copper, zinc, arsenic, iron, and manganese in the surficial sediments around the hydrothermal vent. Sediments near the vent show relatively high content of the ore-forming elements and either high ratios of copper to iron content and zinc to iron content or high ratios of copper to manganese content and zinc to manganese content. These findings show that the content of the ore-forming elements in the sediments around hydrothermal vents are mainly influenced by the distance of sediments to the vent, rather than grain size. In this way, the PXRF analysis of surface sediment geochemistry is found to satisfy the requirements of recognition geochemical anomaly in mid-ocean ridge sediments. Sediments with diameters finer than 40 mesh should be used as analytical samples in the geochemical exploration for hydrothermal vents on mid-oceanic ridges. The results concerning copper, zinc, arsenic, iron, and manganese and their ratio features can be used as indicators in sediment geochemical exploration of seafloor sulfides.

The weather research and forecasting (WRF) model is a new generation mesoscale numerical model with a fine grid resolution (2 km), making it ideal to simulate the macro- and micro-physical processes and latent heating within Typhoon Molave (2009). Simulations based on a single-moment, six-class microphysical scheme are shown to be reasonable, following verification of results for the typhoon track, wind intensity, precipitation pattern, as well as inner-core thermodynamic and dynamic structures. After calculating latent heating rate, it is concluded that the total latent heat is mainly derived from condensation below the zero degree isotherm, and from deposition above this isotherm. It is revealed that cloud microphysical processes related to graupel are the most important contributors to the total latent heat. Other important latent heat contributors in the simulated Typhoon Molave are condensation of cloud water, deposition of cloud ice, deposition of snow, initiation of cloud ice crystals, deposition of graupel, accretion of cloud water by graupel, evaporation of cloud water and rainwater, sublimation of snow, sublimation of graupel, melting of graupel, and sublimation of cloud ice. In essence, the simulated latent heat profile is similar to ones recorded by the Tropical Rainfall Measuring Mission, although specific values differ slightly.

Several remotely sensed sea surface salinity (SSS) retrievals with various resolutions from the soil moisture and ocean salinity (SMOS) and Aquarius/SAC-D missions are applied as inputs for retrieving salinity profiles (S) using multilinear regressions. The performance is evaluated using a total root mean square (RMS) error, different error sources, and the feature resolutions of the retrieved S fields. In the mixed layer of the salinity, the SSS-S regression coefficients are uniformly large. The SSS inputs yield smaller RMS errors in the retrieved S with respect to Argo profiles as their spatial or temporal resolution decreases. The projected SSS errors are dominant, and the retrieved S values are more accurate than those of climatology in the tropics except for the tropical Atlantic, where the regression errors are abnormally large. Below that level, because of the influence of a sea level anomaly, the areas of high-accuracy S values shift to higher latitudes except in the high-latitude southern oceans, where the projected SSS errors are abnormally large. A spectral analysis suggests that the CATDS-0.25° results are much noisier and that the BEC-L4-0.25° results are much smoother than those of the other retrievals. Aquarius-CAP-1° generates the smallest RMS errors, and Aquarius-V2-1° performs well in depicting large-scale phenomena. BEC-L3-0.25°, which has small RMS errors and remarkable mesoscale energy, is the best fit for portraying mesoscale features in the SSS and retrieved S fields. The current priority for retrieving S is to improve the reliability of satellite SSS especially at middle and high latitudes, by developing advanced algorithms, combining both sensors, or weighing between accuracy and resolutions.

As rain drops change the radiation and scattering characteristic of the oceans and the atmosphere, the wind speed measuring by spaceborne remote sensors under rainy conditions remains challenging for years. On the basis of a microwave radiometer (RM) loaded on HY-2 satellite, the sensitivity of some brightness temperature (TB) channels to a rain rate and the wind speed are analyzed. Consequently, two TB combinations which show minor sensitivity to rain are obtained. Meanwhile, the sensitivity of the TB combination to the wind speed is even better to the original TB channel. On the basis of these TB combinations, a wind speed retrieval algorithm is developed and compared with WindSat all-weather wind speed product, HY-2 RM original wind speed product and buoy in situ data. The wind speed retrieval accuracy is better than 2 m/s for rainy conditions, which is evidently superior to HY-2 RM original product. The applicability of this new algorithm is testified for the wind speed measuring in rainy weather with HY-2 RM.

Time-series InSAR analysis (e.g., permanent scatterers (PSInSAR)) has been proven as an effective technology in monitoring ground deformation over urban areas. However, it is a big challenge to apply this technology in coastal regions due to the lack of man-made targets. An distributed scatterers interferometric synthetic aperture radar (DSInSAR) is developed to solve the problem of insufficient samples and low reliability in monitoring coastal lowland subsidence, by applying a spatially adaptive filter and an eigendecomposition algorithm to estimating the optimal phase of statistically homogeneous distributed scatterers (DSs). Twenty-four scenes of COSMO-SkyMed images acquired between 2013 and 2015 are used to retrieve the land subsidence over the Shangyu District on south coast of the Hangzhou Bay, Zhejiang Province, China. The spatial pattern of the land subsidence obtained by the PS-InSAR and the DSInSAR coincides with each other, but the density of the DSs is three point five times higher than the permanent scatterers (PSs). Validated by precise levelling data over the same period, the DSInSAR method achieves an accuracy of ±5.0 mm/a which is superior to the PS-InSAR with ±5.5 mm/a. The land subsidence in the Shangyu District is mainly distributed in the urban areas, industrial towns and land reclamation zones, with a maximum subsidence rate –30.2 mm/a. The analysis of geological data, field investigation and historical reclamation data indicates that human activities and natural compaction of reclamation material are major causes of the detected land subsidence. The results demonstrate that the DSInSAR method has a great potential in monitoring the coastal lowland subsidence and can be used to further investigate subsidence-related environmental issues in coastal regions.

Oil spills pose a major threat to ocean ecosystems and their health. Synthetic aperture radar (SAR) sensors can detect oil spills on the sea surface. These oil spills appear as dark spots in SAR images. However, dark formations can be caused by a number of phenomena. It is aimed to distinguishing oil spills or look-alike objects. A novel method based on a bidimensional empirical mode decomposition is proposed. The selected dark formations are first decomposed into several bidimensional intrinsic mode functions and the residue. Subsequently, 64 dimension feature sets are calculated using the Hilbert spectral analysis and five new features are extracted with a relief algorithm. Mahalanobis distances are then used for classification. Three data sets containing oil spills or look-alikes are used to test the accuracy rate of the method. The accuracy rate is more than 90%. The experimental results demonstrate that the novel method can detect oil spills validly and accurately.

The difference analysis of physical-mechanical properties of muddy sediments is made in the central South Yellow Sea and the Zhe-Min (Zhejiang Province to Fujian Province of China) coastal area. The results show that sediments in the two regions are both dominated by mud. There are perfect negative power function correlations between the water content and the density, the compression coefficient and the compression modulus; a good positive power function correlation between the liquid limit and the plastic limit, a perfect positive linear correlation between the water content and the void ratio, and a perfect polynomial function correlation between the miniature vane shear strength and the pocket penetration resistance. In general, compared with sediments in the Zhe-Min coastal area, sediments in the central South Yellow Sea possess high water content, high void ratio, low density, high plasticity, high compressibility, low shear strength. The causes of the differences between physical-mechanical properties of sediments are analyzed from the topographic features, material sources, hydrodynamic conditions, deposition rate, and material composition. Compared with the Zhe-Min coastal area, the central South Yellow Sea is far from the Mainland and low-lying; has poor hydrodynamic condition; the materials diffused to the area are less and dominated by fine clay, have the high content of smectite and organic matters. These factors lead to sediments of the central South Yellow Sea has the higher water content, the higher plasticity, the lower density, and the lower strength than sediments in the Zhe-Min coastal area.

This paper reviews the current achievements of the China Argo project. It considers aspects of both the construction of the Argo observing array, float technology, and the quality control and sharing of its data. The developments of associated data products and data applications for use in the fields of ocean, atmosphere, and climate research are discussed, particularly those related to tropical cyclones (typhoons), ocean circulation, mesoscale eddies, turbulence, oceanic heat/salt storage and transportation, water masses, and operational oceanic/atmospheric/climatic forecasts and predictions. Finally, the challenges and opportunities involved in the long-term maintenance and sustained development of the China Argo ocean observation network are outlined. Discussion also focuses on the necessity for increasing the number of floats in the Indian Ocean and for expanding the regional Argo observation network in the South China Sea, together with the importance of promoting the use of Argo data by the maritime countries of Southeast Asia and India.

Bayesian and restricted maximum likelihood (REML) approaches were used to estimate the genetic parameters in a cultured turbot Scophthalmus maximus stock. The data set consisted of harvest body weight from 2 462 progenies (17 months old) from 28 families that were produced through artificial insemination using 39 parent fish. An animal model was applied to partition each weight value into a fixed effect, an additive genetic effect, and a residual effect. The average body weight of each family, which was measured at 110 days post-hatching, was considered as a covariate. For Bayesian analysis, heritability and breeding values were estimated using both the posterior mean and mode from the joint posterior conditional distribution. The results revealed that for additive genetic variance, the posterior mean estimate ($\sigma _a^2$=9 320) was highest but with the smallest residual variance, REML estimates ($\sigma _a^2$=8 088) came second and the posterior mode estimate ($\sigma _a^2$=7 849) was lowest. The corresponding three heritability estimates followed the same trend as additive genetic variance and they were all high. The Pearson correlations between each pair of the three estimates of breeding values were all high, particularly that between the posterior mean and REML estimates (0.996 9). These results reveal that the differences between Bayesian and REML methods in terms of estimation of heritability and breeding values were small. This study provides another feasible method of genetic parameter estimation in selective breeding programs of turbot.

Lectins are sugar-specific binding proteins or glycoproteins that play important physiological roles in cellular recognition and regulation. And they are also valuable in medicine and pharmacy. Tubeworm is the representative species around the hydrothermal vent in the deep sea. They have developed unique mechanisms to adapt to the harsh environment. In this study, a 1 092 bp cDNA, designed as rpgal, was first cloned and characterized from the tubeworm Ridgeia piscesae. Sequence analysis showed that RPGAL had low homology with the known galectin. And it had two homologous carbohydrate-recognition domains, which is the characteristic of the tandem-repeat type galectins. The RPGAL was successfully recombinant expressed in Escherichia coli and purified. Analysis of biological activity revealed that RPGAL was metal ion independent and it could agglutinate all the vertebrate erythrocytes tested. It was stable at 10–50°C and pH 5–10. And the hemagglutinating activity of RPGAL was strongly inhibited by D-Lactose and lipopolysaccharide. Although RPGAL had no effect on the microorganisms tested, it showed anti-tumor activity towards HeLa cells and HT1080 cells, which was accomplished by apoptosis. The study demonstrated that RPGAL was a novel galectin and provided a potential candidate for therapy of anti-tumor.