The sea ice concentration observation from satellite remote sensing includes the spatial multi-scale information. However, traditional data assimilation methods cannot better extract the valuable information due to the complicated variability of the sea ice concentration in the marginal ice zone. A successive corrections analysis using variational optimization method, called spatial multi-scale recursive filter (SMRF), has been designed in this paper to extract multi-scale information resolved by sea ice observations. It is a combination of successive correction methods (SCM) and minimization algorithms, in which various observational scales, from longer to shorter wavelengths, can be extracted successively. As a variational objective analysis scheme, it gains the advantage over the conventional approaches that analyze all scales resolved by observations at one time, and also, the specification of parameters is more convenient. Results of single-observation experiment demonstrate that the SMRF scheme possesses a good ability in propagating observational signals. Further, it shows a superior performance in extracting multi-scale information in a two-dimensional sea ice concentration (SIC) experiment with the real observations from Special Sensor Microwave/Imager SIC (SSMI).

The spatial-temporal patterns of tropical cyclone (TC) intensity changes caused by the warm ocean mesoscale eddy (WOME) distribution are evaluated using two sets of idealized numerical experiments. The results show that the TC was intensified and weakened when a WOME was close to and far away from the TC center, respectively. The area where the WOME enhanced (weakened) TC intensity is called the inner (outer) area in this study. Amplitudes of the enhancement and weakening caused by the WOME in the inner and outer area decreased and increased over time, while the ranges of the inner and outer area diminished and expanded, respectively. The WOME in the inner area strengthened the secondary circulation of the TC, increased heat fluxes, strengthened the symmetry, and weakened the outer spiral rainband, which enhanced TC intensity. The effect was opposite if the WOME was in the outer area, and it weakened the TC intensity. The idealized simulation employed a stationary TC, and thus the results may only be applied to TCs with slow propagation. These findings can improve our understanding of the interactions between TC and the WOME and are helpful for improving TC intensity forecasting by considering the effect of the WOME in the outer areas.

Based on the climatological reanalysis data of the European Center for Medium-Range Weather Forecasts and the Arctic sea ice data of the National Snow and Ice Data Center, the relationship between the Arctic sea ice area (SIA) and the interannual variation of atmospheric meridional heat transport (AMHT) was analyzed. The results show that the atmospheric meridional heat transported by transient eddy (TAMHT) dominates the June AMHT in mid-high latitudes of the Northern Hemisphere, while the western Baffin Bay (B) and the eastern Greenland (G) are two gates for TAMHT entering the Arctic. TAMHT in the western Baffin Bay (B-TAMHT) and eastern Greenland (G-TAMHT) has a concurrent variation of reverse phase, which is closely related to the summer Arctic SIA. Possible mechanism is that the three Arctic atmospheric circulation patterns (AD, AO and NAO) in June can cause the concurrent variation of TAMHT in the B and G regions. This concurrent variation helps to maintain AD anomaly in summer through wave action and changes the polar air temperature, thus affecting the summer Arctic SIA. Calling the heat entering the Arctic as warm transport and the heat leaving Arctic as cold transport, then the results are classified into three situations based on B-TAMHT and G-TAMHT: warm B corresponding to cold G (WC), cold B corresponding to warm G (CW), cold B corresponding to cold G (CC), while warm B corresponding to warm G is virtually non-existent. During the WC situation, the SIA in the Pacific Arctic sediments and Kara Sea decreases; during the CW situation, the SIA in the Laptev Sea and Kara Sea decreases; during the CC situation, the SIA in the Kara Sea, Laptev Sea and southern Beaufort Sea increases.

Sea spray droplets are produced by waves breaking on the sea surface, and they vary the transfer of energy between the atmosphere and ocean. The sea spray generation function (SSGF) is generally considered as a function of the initial radius of the spray droplets and the wind speed. However, ocean waves always exist at the air-sea interface, so it is not reasonable to consider only the effect of sea surface winds while ignoring the effects of ocean waves. Whitecap coverage is an important characteristic parameter of breaking waves, and researchers believe that this parameter is related to both wave state and wind speed. In this paper, the SSGF is parameterized by the whitecap coverage, and a new SSGF describing different droplet radii is organically integrated based on the whitecap coverage parameter. Then, with the relationship between the whitecap coverage and wave state, the influence of ocean waves on the SSGF for different wave states was analyzed by using observational data in the laboratory. The results show that the new SSGF that considers wave effects can reasonably describe the droplet generation process under different wave state conditions.

Polymetallic nodules and cobalt (Co)-rich crusts are enriched in platinum-group elements (PGEs), especially platinum (Pt) and may be important sinks of PGEs. At present, little information is available on PGEs in polymetallic nodules, and their geochemical characteristics and the causes of PGEs enrichment are unclear. Here, PGEs of polymetallic nodules from abyssal basin in the Marcus-Wake Seamount area of the Northwest Pacific Ocean are reported and compared with the published PGEs data of polymetallic nodules and Co-rich crusts in the Pacific. The total PGEs (ΣPGE) content of polymetallic nodules in study area is 258×10^–9 in average, markedly higher than that of Clarion-Clipperton Zone (CCZ) nodules (ΣPGE=127×10^–9) and lower than that of Co-rich crusts in the Marcus-Wake Seamount (ΣPGE=653×10^–9), similar to that of Co-rich crusts in the South China Sea (ΣPGE=252×10^–9). The CI chondrite-normalized PGEs patterns in different regions of polymetallic nodules and cobalt-rich crusts are highly consistent, with all being characterized by positive Pt and negative Pd anomalies. These results, together with those of previous studies, indicate that PGEs in polymetallic nodules and Co-rich crusts are mainly derived directly from seawater. Pt contents of polymetallic nodules from the study area are negatively correlated with water depth, and Pt/ΣPGE ratios in nodules there are also lower than those of the Co-rich crusts in the adjacent area, indicating that sedimentary water depth and oxygen fugacity of ambient seawater are the possible important controlling factors for Pt accumulation in crusts and nodules.

Understanding the connectivity of fish among different typical habitats is important for conducting ecosystem-based management, particularly when designing marine protected areas (MPA) or setting MPA networks. To clarify of connectivity among mangrove, seagrass beds, and coral reef habitats in Wenchang, Hainan Province, China, the fish community structure was studied in wet and dry seasons of 2018. Gill nets were placed across the three habitat types, and the number of species, individuals, and body size of individual fish were recorded. In total, 3 815 individuals belonging to 154 species of 57 families were collected. The highest number of individuals and species was documented in mangroves (117 species, 2 623 individuals), followed by coral reefs (61 species, 438 individuals) and seagrass beds (46 species, 754 individuals). The similarity tests revealed highly significant differences among the three habitats. Approximately 23.4% species used two habitats and 11.0% species used three habitats. A significant difference (p<0.05) in habitat use among eight species (Mugil cephalus, Gerres oblongus, Siganus fuscescens, Terapon jarbua, Sillago maculata, Upeneus tragula, Lutjanus russellii, and Monacanthus chinensis) was detected, with a clear ontogenetic shift in habitat use from mangrove or seagrass beds to coral reefs. The similarity indices suggested that fish assemblages can be divided into three large groups namely coral, seagrass, and mangrove habitat types. This study demonstrated that connectivity exists between mangrove–seagrass–coral reef continuum in Wenchang area; therefore, we recommend that fish connectivity should be considered when designing MPAs or MPA network where possible.

This study used Ecopath model of the Jiaozhou Bay as an example to evaluate the effect of stomach sample size of three fish species on the projection of this model. The derived ecosystem indices were classified into three categories: (1) direct indices, like the trophic level of species, influenced by stomach sample size directly; (2) indirect indices, like ecology efficiency (EE) of invertebrates, influenced by the multiple prey-predator relationships; and (3) systemic indices, like total system throughout (TST), describing the status of the whole ecosystem. The influences of different stomach sample sizes on these indices were evaluated. The results suggest that systemic indices of the ecosystem model were robust to stomach sample sizes, whereas specific indices related to species were indicated to be with low accuracy and precision when stomach samples were insufficient. The indices became more uncertain when the stomach sample sizes varied for more species. This study enhances the understanding of how the quality of diet composition data influences ecosystem modeling outputs. The results can also guide the design of stomach content analysis for developing ecosystem models.

Zooplankton samples were collected using 505, 160 and 77 μm mesh nets around a power plant during four seasons in 2011. We measured total length of zooplankton and divided zooplankton into seven size classes in order to explore how zooplankton community size-structure might be altered by thermal discharge from power plant. The total length of zooplankton varied from 93.7 to 40 074.7 μm. The spatial distribution of meso-zooplankton (200 −2 000 μm) populations were rarely affected by thermal discharge, while macro- (2 000 −10 000 μm) and megalo-zooplankton (>10 000 μm) had an obvious tendency to migrate away from the outfall of power plant. Thus, zooplankton community tended to become smaller and biodiversity reduced close to power plant. Moreover, we compared the zooplankton communities in three different mesh size nets. Species richness, abundance, evenness index and Shannon−Wiener diversity index of the 505 µm mesh size were significantly lower than those recorded from the 160 and 77 µm mesh size. Average zooplankton abundance was highest in the 77 µm mesh net ((27 690.0±1 633.7) ind./m³), followed by 160 µm mesh net ((9 531.1±1 079.5) ind./m³), and lowest in 505 µm mesh net ((494.4±104.7) ind./m³). The ANOSIM and SIMPER tests confirmed that these differences were mainly due to small zooplankton and early developmental stages of zooplankton. It is the first time to use the 77 µm mesh net to sample zooplankton in such an environment. The 77 µm mesh net had the overwhelming abundance of the copepod genus Oithona, as an order of magnitude greater than recorded for 160 µm mesh net and 100% loss through the 505 μm mesh net. These results indicate that the use of a small or even multiple sampling net is necessary to accurately quantify entire zooplankton community around coastal power plant.

The evolution of the shoals and vegetation plays an important role in maintaining the stability of the river regime and the estuarine ecosystem. However, the interaction between the evolution of shoals and vegetation dynamic has rarely been reported. In this study, we determined the interaction between the shoal and vegetation evolution of Jiuduansha in the Changjiang River Estuary in the last 30 years. We did this through the collection and summarization of the existing data of the regional hydrological processes, wading engineering, and vegetation, and combined it with the analysis of nautical charts and remote sensing images. During the past 30 years, the expansion of the shoals within the 0 m isobath in Jiuduansha was obvious, with an increase of 176.5%, while the expansion of the shoals within the 5 m isobath was relatively slow. The regional hydrological characteristics in the Jiuduansha area changed dramatically, especially the sediment discharges. The area of vegetation in Jiuduansha increased from 9.1 km² in 1990 to 65.68 km² in 2015, while the variations in the different vegetation types were different. The best combination of environmental factors with a significant correlation on the shoals within the 0 m isobath is the area of Spartina alterniflora and Phragmites australis. The evolution of Jiuduansha shoals was significantly affected by the variations in hydrological characteristics. Meanwhile, on a long-term scale, the expansion of the shoals could promote the regional vegetation expansions due to the suitable elevation and environmental conditions it provides. The interaction between the shoal and vegetation evolution varied in the different vegetation types and different elevations. In the future, long-term monitoring and detailed data are needed to the systematical analysis of the interaction between the hydrological processes and the evolution of the shoal and vegetation.

To further understand the effect of Kuroshio intrusion on phytoplankton community structure in the northeastern South China Sea (NSCS, 14°–23°N, 114°–124°E), one targeted cruise was carried out from July to August, 2017. A total of 79 genera and 287 species were identified, mainly including Bacillariophyta (129 species), Pyrrophyta (150 species), Cyanophyta (4 species), Chrysophyta (3 species) and Haptophyta (1 species). The average abundance of phytoplankton was 2.14×10³ cells/L, and Cyanobacterium was dominant species accounting for 86.84% of total phytoplankton abundance. The abundance and distribution of dominant Cyanobacterium were obviously various along the flow of the Kuroshio, indicating the Cyanobacterium was profoundly influenced by the physical process of the Kuroshio. Therefore, Cyanobacterium could be used to indicate the influence of Kuroshio intrusion. In addition, the key controlling factors of the phytoplankton community were nitrogen, silicate, phosphate and temperature, according to Canonical Correspondence Analysis. However, the variability of these chemical parameters in the study water was similarly induced by the physical process of circulations. Based on the cluster analysis, the similarity of phytoplankton community is surprisingly divided by the regional influence of the Kuroshio intrusion, which indicated Kuroshio intrusion regulates phytoplankton community in the NSCS.