The interface of assimilating radiance on a new satellite sensor GMI (Global Precipitation Measurement (GPM) microwave imager) was constructed in the framework of the mesoscale numerical model WRF (Weather Research and Forecasting Model) and its three-dimensional variational assimilation system (3DVAR). The assimilation of GMI radiance data is applied for the typhoon system based on the case of typhoon Matmo in the Pacific typhoon season in 2014 before its landing. The results show that, after assimilating the GMI radiance data under the clear sky condition, the typhoon position in the background of the model is effectively corrected. The GMI data are able to improve the warm core structure of the typhoon when compared with the control experiment without assimilation and enhanced the typhoon vortex circulation structure at the same time. Data assimilating of GMI data further improves the forecast skills of the typhoon track.

Particle filter (PF) is a very promising nonlinear data assimilation method. However, due to the particle degeneracy problem, it has not been widely used in large geophysical models. In contrast, the ensemble Kalman filter (EnKF) and its derivative methods have been widely used in operational data assimilation systems in recent years. A newly proposed local particle filter (LPF) which employs the localization technique in particle filter, can effectively avoid the degeneracy problem with low computational costs and has great potential for practical applications. In this paper, data assimilation experiments using LPF and EnKF are conducted in a fully coupled Community earth system model. The sythetic satellite sea surface temperature data are assimilated with each method. Different impact of local parameters on each method is investigated, and the data assimilation performances of LPF and EnKF are compared. The comparison results show that the performance of LPF is more sensitive to localization parameter. With the optimal localization strategy, it is shown that LPF can be better than EnKF, and have a potential to be further improved.

The accurate classification of sea ice is of great significance for mastering the growth and development of sea ice and ensuring the safety of navigation. Due to the influence of data sources and classification methods, the improvement of sea ice classification accuracy is limited. In this paper, for high spatial resolution optical remote sensing images, an accurate sea ice classification method based on texture features and normalized difference vegetation index (NDVI) was proposed, and a random forest classifier was used to construct a sea ice classification method. Taking Jiaozhou Bay of Qingdao as the experimental area and GF-2 as the experimental data, the sea ice types were extracted and compared with other classification methods. The results show that for GF-2 high-resolution optical remote sensing data, compared with the traditional random forest, support vector machine, automatic classification and regression tree methods and maximum likelihood classification method of combining texture features, the overall classification accuracy was improved by 13.70%, 11.60%, 19.22% and 29.37%, respectively. The Kappa coefficient was increased by 0.16, 0.13, 0.22 and 0.44, respectively. Compared with the random forest method based on texture features and normalized difference water index, the overall classification accuracy was improved by 9.67% and Kappa coefficient was increased by 0.09. It shows that the sea ice classification method constructed in this paper can effectively improve the accuracy of sea ice classification, and provide an effective technical means for the accurate classification of sea ice.

Marine biotechnology refers to the applied science and technology for large-scale production marine bioproducts and provision of services for industry and community based on sustainable utilization and management of marine bioresources. The 1st International Marine Biotechnology Conference was held in Tokyo, Japan in 1989. Over the last 30 years, the global marine biotechnology had progressed rapidly in promoting the sustainable and healthy development of marine aquaculture, the development of novel marine bioproducts, the conservation of marine environment and bioresources, and the construction of “harmonic ocean” etc. It served not only the upgrade of traditional marine bioindustry of fisheries and aquaculture, but also the growth of many newly emerging industries such as marine pharmaceuticals, marine biomaterials and marine functional foods. The theme of 12th International Marine Biotechnology Conference held in Shizuoka, Japan on 9−13 September 2019, with “the next generation of marine biotechnology” as the theme. The conference served to strengthen the platform for the global exchange of new advances in marine biotechnology and the effective development of cooperations for government, academy and industry. This conference had promoted heavily on the roles of young scientists and entrepreneurs for the advances in marine biotechnology. This review, based on new advances reflected in the conference, proposes notable key directions in marine biotechnology for China over the next 5−10 years, and suggests the priorities of training young talents especially those integrated with entrepreneurs’ skills and to developing the leading strategic position in fostering new industries.

The CO₂ flux at the sea-air interface, which is equal to the product of the gas transfer velocity, solubility, and the CO₂ partial pressure difference between sea and the atmosphere, is estimated using the bulk equation, where the gas transfer velocity is usually associated with the wind speed. Different authors have proposed different parameterization schemes, in which the gas transfer velocity is a polynomial of different powers of the wind speed. In this paper, we summarize the main findings on the gas transfer velocity as a function of wind speed. We discover that the observation method has a greater influence on the gas transfer velocity than the power of the wind speed polynomial. On this basis, this paper calculates the global CO₂ flux from 1982−2018 using several different parametric formulas for the gas exchange rate. The ocean is a sink for atmospheric CO₂, the equatorial sea area is a source, and the ocean near 40° in the northern and southern hemispheres forms a strong absorption zone along the latitudinal direction. The annual average value of oceanic CO₂ absorption (in terms of carbon) over 1982−2018 is (−1.53±0.15)Pg/a. The oceanic absorption decreases year by year until 1999, reaching a minimum in 1999, after which the oceanic absorption begins to increase, with the increase in oceanic absorption occurring mainly in the Southern Ocean.

As a typical high-turbidity bay, the carbonate systems in the Hangzhou Bay are not well documented. In this paper, the spatial distributions of inorganic carbonate paramenters in the Hangzhou Bay were analyzed based on data collected from two summer surveys in 2018 and 2019. The results showed that dissolved inorganic carbon (DIC) concentration and total alkalinity (TA) in surface layer of the Hangzhou Bay ranged from 1 553 μmol/kg to 1 964 μmol/kg and from 1 577 μmol/kg to 2 101 μmol/kg, respectively, which were lower than that of the Changjiang River Estuary (1 407−2 110 μmol/kg and 1 752−2 274 μmol/kg). The spatial distributions of DIC concentration and TA were controlled by the mixing of fresh water and offshore sea water. They were affected by strong tide, which gradually increased DIC concentration from inner bay to outlet of the bay. Air-sea carbon exchange and biological respiration led to decrease and increase of DIC concentration, with the contributions of (−42.3±11.7)% and (34.2±14.3)%, respectively. Such two compensate processes resulted in a net balanced state. The average surface pCO₂ in the Hangzhou Bay was 799 μatm (675−932 μatm), indicating that bay waters were source of atmospheric CO₂. The revelle factor in the Hangzhou Bay varied from 12.8 to 23.8, suggesting a weaker CO₂ buffering capacity than the adjacent East China Sea (the mean value was 11.9). Compared with other estuaries/gulfs, the characteristics of high turbidity and strong tides in the Hangzhou Bay made the spatial distributions of the carbonate system in the bay water had regional specificity.

In order to study the growth, death, transport and distribution of early life history of winter-spring cohort of neon flying squid Ommastrephes bartramii in the Northwest Pacific Ocean, parameterized early biological processes, such as growth and death. Used the physical model (FVCOM-Global) to simulate and generate three-dimensional physical field of the North Pacific Ocean (10°−60°N, 120°E−110°W), and adopted the Lagrangian particle tracking method to couple the physical model and the biological model (individual-based model), and constructed an individual-based ecological model of early life history of winter-spring cohort of O. bartramii in the Northwest Pacific Ocean, and used this model to numerically simulate the transport distribution of winter-spring cohort from 1997 to 2010. The simulation results showed that within a certain temperature range, the closer to the optimum water temperature, the faster the growth rate of winter-spring cohort. When the age was 38 days, the mantle length could reach 11.76 millimeters, and then gradually changed from exponential growth to linear growth. The simulative recruitment had interannual fluctuation from 1997 to 2010. Considering the different number of winter-spring cohort parents, the years with the most and the least actual recruitment were 1999 and 2009, respectively. In the simulation stage, the winter-spring cohort was mainly located in the spawning ground, transported to the west in the south of 25°N, and gradually transported to the north and northeast in the north of 25°N, especially affected by the strong current in the later period of transport. In the vertical direction, the larvae within 100 meters water depth accounted for nearly half. This study can lay a foundation for further study of ecological dynamics of winter-spring cohort of O. bartramii in the Northwest Pacific Ocean.

Chilean jack mackerel (Trachurus murphyi) is one of the important economic fisheries in the Southeast Pacific Ocean. The stock abundance is inherently affected by recruitment. To find out the status of recruitment is of great significance to the sustainable yield and scientific management of resources. The recruitment of Chilean jack mackerel between 1971 and 2017 is divided into different regimes based on regime test. Then, the Bayesian model averaging is applied to the relationship between recruitment and five environmental factors (sea surface temperature, sea surface salinity, sea surface height, El Niño and Pacific decadal oscillation), and the impact of regime change in recruitment forecast is also discussed. The results show that the first regime (1971−1980) is more disturbed by fishing; in the second regime (1981−1990), El Niño has the highest probability of explaining for the change of recruitment; the environmental factor with the highest explanatory probability is Pacific Decadal Oscillation in the third regime (1991−2001); in the fourth regime (2002−2015), El Niño most likely explains the change in recruitment; comparing the analysis of regime shift and no regime shift models, there is a significant difference between the two. However, the results, with different regimes, are more reasonable to explain the change of recruitment. Recruitment abundance is affected by multiple environmental factors, but in different regimes, the dominant environmental factor changes. The regime shifts of recruitment are induced by the alternation of cold and warm periods of interdecadal Pacific decadal oscillation, and El Niño. It is suggested that different regime shift and their impact factors should be considered in the future assessment and management of Chilean jack mackerel resources.

In order to understand the population dynamics of ichthyoplankton and the changing laws of biodiversity in the Laizhou Bay, four investigations (respectively in spring, summer, autumn and winter) of 20 positions in the Laizhou Bay from 2014 to 2015, the seasonal variations of species composition and community structure of ichthyoplankton in this area, involving its dominant species, community diversity and seasonal turnover rate were studied in this paper. The results showed that 135275 fish eggs and 2456 larvae were collected, total 22 species. Main species of ichthyoplankton changed significantly with the seasons, from Engraulis japonicus and Liza haematocheilus in spring, to Thryssa kammalensis and Allanetta bleekeri in summer, to Protosalanx hyalocranius in autumn, to Zoarces elongates in winter. The richness index (D) and diversity index (H′) were the highest in summer, and the evenness index (J′) was the highest in autumn. The species turnover rate from spring to summer was the lowest. Analysis of the results of clustering using R language with the highest likelihood suggest the existence of three assemblages of ichthyoplankton in the surveyed waters: spring group, summer and autumn group, winter group. The main divergent species of spring group and summer-autumn group, spring group and winter group were Engraulis japonicus. While the main divergent species of summer autumn group and winter group were Zoarces elongates and Thryssa kammalensis. This study shows that there are significant seasonal differences in the species composition, quantity distribution and biodiversity of ichthyoplankton in the Laizhou Bay. The research results supplement the basic data of fish early replenishment resources in the Laizhou Bay and provide basis for fishery resources conservation in the Laizhou Bay.

The benthic macroinvertebrate is the important ecological group in river ecosystem. The study of the community composition and distribution characteristics on the benthic macroinvertebrate can provide theoretical support for river ecosystem management. In June (summer) and November (autumn) 2018, surveys on the benthic macroinvertebrate with trawl and ground cages were carried out in 16 fixed sampling sites in the inland rivers of Chongming Island. The community composition, distribution characteristics and corresponding influencing factors of the benthic macroinvertebrates were analyzed then. A total of 14 species belonging to 5 orders, 8 families of the benthic macroinvertebrates were collected in the surveys. Most of them were arthropods. Among them, 10 species were freshwater type, 3 species were estuarine brackish water type and 1 species was catadromous migration type. And 12, 6 and 11 benthic macroinvertebrate species were recorded in the Beiheng Canal, Nanheng Canal, and the vertical canals respectively. The dominants of the benthic macroinvertebrates were freshwater species, and the common species were Macrobrachium nipponense, and Exopalaemon modestus. The number of species, abundance and biomass of the benthic macroinvertebrates in the Beiheng Canal and the vertical canals were higher than those in the Nanheng Canal. The number of species, abundance and biomass of the benthic macroinvertebrates in the summer were higher than those in the autumn. Seasonal variations were one of the important features of the characteristics of the benthic macroinvertebrate assemblages in the inland rivers of Chongming Island. Add all these together, the inland rivers of Chongming Island had some characteristics of both estuaries and inland rivers, which were related to the geographical location, hydrological conditions, riverine habitats, water quality characteristics and regional human activities of the Chongming Island.