This study cross-calibrated the brightness temperatures observed in the Arctic by using the FY-3B/MWRI L1 and the Aqua/AMSR-E L2A. The monthly parameters of the cross-calibration were determined and evaluated using robust linear regression. The snow depth in case of seasonal ice was calculated by using parameters of the cross-calibration of data from the MWRI T_b. The correlation coefficients of the H/V polarization among all channels T_b of the two sensors were higher than 0.97. The parameters of the monthly cross-calibration were useful for the snow depth retrieval using the MWRI. Data from the MWRI T_b were cross-calibrated to the AMSR-E baseline. Biases in the data of the two sensors were optimized to approximately 0 K through the cross-calibration, the standard deviations decreased significantly in the range of 1.32 K to 2.57 K, and the correlation coefficients were as high as 99%. An analysis of the statistical distributions of the histograms before and after cross-calibration indicated that the FY-3B/MWRI T_b data had been well calibrated. Furthermore, the results of the cross-calibration were evaluated by data on the daily average T_b at 18.7 GHz, 23.8 GHz, and 36.5 GHz (V polarization), and at 89 GHz (H/V polarization), and were applied to the snow depths retrieval in the Arctic. The parameters of monthly cross-calibration were found to be effective in terms of correcting the daily average T_b. The results of the snow depths were compared with those of the calibrated MWRI and AMSR-E products. Biases of 0.18 cm to 0.38 cm were observed in the monthly snow depths, with the standard deviations ranging from 4.19 cm to 4.80 cm.

To assess the performances of state-of-the-art global climate models on simulating the Arctic clouds and surface radiation balance, the 2001–2014 Arctic Basin surface radiation budget, clouds, and the cloud radiative effects (CREs) in 22 coupled model intercomparison project 6 (CMIP6) models are evaluated against satellite observations. For the results from CMIP6 multi-model mean, cloud fraction (CF) peaks in autumn and is lowest in winter and spring, consistent with that from three satellite observation products (CloudSat-CALIPSO, CERES-MODIS, and APP-x). Simulated CF also shows consistent spatial patterns with those in observations. However, almost all models overestimate the CF amount throughout the year when compared to CERES-MODIS and APP-x. On average, clouds warm the surface of the Arctic Basin mainly via the longwave (LW) radiation cloud warming effect in winter. Simulated surface energy loss of LW is less than that in CERES-EBAF observation, while the net surface shortwave (SW) flux is underestimated. The biases may result from the stronger cloud LW warming effect and SW cooling effect from the overestimated CF by the models. These two biases compensate each other, yielding similar net surface radiation flux between model output (3.0 W/m²) and CERES-EBAF observation (6.1 W/m²). During 2001–2014, significant increasing trend of spring CF is found in the multi-model mean, consistent with previous studies based on surface and satellite observations. Although most of the 22 CMIP6 models show common seasonal cycles of CF and liquid water path/ice water path (LWP/IWP), large inter-model spreads exist in the amounts of CF and LWP/IWP throughout the year, indicating the influences of different cloud parameterization schemes used in different models. Cloud Feedback Model Intercomparison Project (CFMIP) observation simulator package (COSP) is a great tool to accurately assess the performance of climate models on simulating clouds. More intuitive and credible evaluation results can be obtained based on the COSP model output. In the future, with the release of more COSP output of CMIP6 models, it is expected that those inter-model spreads and the model-observation biases can be substantially reduced. Longer term active satellite observations are also necessary to evaluate models’ cloud simulations and to further explore the role of clouds in the rapid Arctic climate changes.

The four-dimensional variational assimilation (4D-Var) has been widely used in meteorological and oceanographic data assimilation. This method is usually implemented in the model space, known as primal approach (P4D-Var). Alternatively, physical space analysis system (4D-PSAS) is proposed to reduce the computation cost, in which the 4D-Var problem is solved in physical space (i.e., observation space). In this study, the conjugate gradient (CG) algorithm, implemented in the 4D-PSAS system is evaluated and it is found that the non-monotonic change of the gradient norm of 4D-PSAS cost function causes artificial oscillations of cost function in the iteration process. The reason of non-monotonic variation of gradient norm in 4D-PSAS is then analyzed. In order to overcome the non-monotonic variation of gradient norm, a new algorithm, Minimum Residual (MINRES) algorithm, is implemented in the process of assimilation iteration in this study. Our experimental results show that the improved 4D-PSAS with the MINRES algorithm guarantees the monotonic reduction of gradient norm of cost function, greatly improves the convergence properties of 4D-PSAS as well, and significantly restrains the numerical noises associated with the traditional 4D-PSAS system.

To better monitor the vertical crustal movements and sea level changes around Greenland, multiple data sources were used in this paper, including global positioning system (GPS), tide gauge, satellite gravimetry, satellite altimetry, glacial isostatic adjustment (GIA). First, the observations of more than 50 GPS stations from the international GNSS service (IGS) and Greenland network (GNET) in 2007–2018 were processed and the common mode error (CME) was eliminated with using the principal component analysis (PCA). The results show that all GPS stations show an uplift trend and the stations in southern Greenland have a higher vertical speed. Second, by deducting the influence of GIA, the impact of current GrIS mass changes on GPS stations was analysed, and the GIA-corrected vertical velocity of the GPS is in good agreement with the vertical velocity obtained by gravity recovery and climate experiment (GRACE). Third, the absolute sea level change around Greenland at 4 gauge stations was obtained by combining relative sea level derived from tide gauge observations and crustal uplift rates derived from GPS observations, and was validated by sea level products of satellite altimetry. The results show that although the mass loss of GrIS can cause considerable global sea level rise, eustatic movements along the coasts of Greenland are quite complex under different mechanisms of sea level changes.

Medusae in 116 samples collected from the coastal waters of the northern Beibu Gulf during four seasonal oceanographic cruises from October 2017 to August 2018 were analyzed. In total, 34 species were identified. Two of the species are new to science, Proboscidactyla pentacanalis Xu, Chen & Yang sp. nov. and Helgicirrha apapillata Xu, Chen & Wang sp. nov., and three species are newly recorded in the Beibu Gulf, i.e., Hydractinia vacuolata Xu & Huang, 2006, Proboscidactyla flavicirrata Brandnt, 1834 and Phialella macrogona Xu, Huang & Wang, 1985. Collections of the species were deposited at the Third Institute of Oceanography, Ministry of Natural Resources.

During the 29th Chinese National Antarctic Research Expedition, spatial variations in nitrogen isotopic composition of particulate nitrogen (δ¹⁵N_PN) and their controlling factors were examined in detail with regard to nitrate drawdown by phytoplankton and particulate nitrogen (PN) remineralization in the Prydz Bay and its adjacent areas. To better constrain the nitrogen transformations, the physical and chemical parameters, including temperature, salinity, nutrients, PN and δ¹⁵N_PN in seawater column were measured from surface to bottom. In addition, the nitrogen isotopic fractionation factor of nitrate assimilation by phytoplankton in the mixed layer, and the nitrogen isotopic fractionation factor of PN remineralization below the mixed layer were estimated using Rayleigh model and Steady State model, respectively. Our results showed that suspended particles had its lowest δ¹⁵N_PN in the surface layer, which was due to the preferential assimilation of ¹⁴N in nitrate by phytoplankton. The δ¹⁵N_PN in the mixed layer of the Prydz Bay and its adjacent areas decreased from the inner shelf to the outer basin, ascribing to the effect of isotope fractionation during phytoplankton assimilation. In mixed layer, the spatial distribution of δ¹⁵N_PN associated with particulate organic matter (POM) production can be well interpreted according to Rayleigh model and Steady State model. The nitrogen isotope fractionation factor during phytoplankton assimilating nitrate was estimated as 10.0‰ by Steady State model, which was more reasonable than that calculated by Rayleigh model. These results validate the previous reports of fractionation factor during nitrate assimilation by phytoplankton. Increasing δ¹⁵N_PN with depth below the euphotic zone correlated with the decreasing PN contents, and it was attributed to preferential remineralization of ¹⁴N in PN by bacteria. In subsurface and deep layer, the δ¹⁵N_PN distributions also conformed to Rayleigh model and Steady State model during PN remineralization, with a fractionation factor of about 3.6‰ and 3.2‰, respectively. It is the first time to estimate the fractionation factor during POM production and remineralization in the Prydz Bay and its adjacent areas. Such fractionation may provide a useful tool for the follow-up study of the nitrogen dynamics in the Southern Ocean.

The mitochondrial genome (mitogenome) of hybrid grouper Epinephelus moara (♀)×Epinephelus tukula (♂), a new hybrid progeny, can provide valuable information for analyzing phylogeny and molecular evolution. In this study, the mitogenome was analyzed using PCR amplification and sequenced, then the phylogenetic relationship of E. moara (♀)×E. tukula (♂) and 35 other species were constructed using Maximum Likelihood and Neighbor-Joining methods with the nucleotide sequences of 13 conserved protein-coding genes (PCGs). The complete mitogenome of E. moara (♀)×E. tukula (♂) was 16 695 bp in length, which contained 13 PCGs, 2 rRNA genes, 22 tRNA genes, a replication origin and a control region. The composition and order of these genes were consistent with most other vertebrates. Of the 13 PCGs, 12 PCGs were encoded on the heavy strand, and ND6 was encoded on the light strand. The mitogenome of the E. moara (♀)×E. tukula (♂) had a higher AT nucleotide content, a positive AT-skew and a negative GC-skew. All protein initiation codons were ATG, except for COX and ND4 (GTG), ATP6 (CTG), and ND3 (ATA). ND2, COXII, ND3, ND4 and Cytb had T as the terminating codon, COXIII’s termination codon was TA, and the remaining PCGs of that were TAA. All tRNA genes, except for the lacking DHU-arm of tRNA^{Ser (AGN)}, were predicted to form a typical cloverleaf secondary structure. In addition, sequence similarity analysis (99% identity) and phylogenetic analysis (100% bootstrap value) indicated that the mitochondrial genome was maternally inherited. This study provides mitogenome data for studying genetic, phylogenetic relationships and breeding of grouper.

Using the mesoscale eddy trajectory atlas product derived from satellite altimeter data from 1993 to 2016, this study analyzes statistical characteristics and seasonal variability of mesoscale eddies in the Banda Sea of the Indonesian seas. The results show that there were 147 mesoscale eddies that occurred in the Banda Sea, of which 137 eddies were locally generated and 10 originated from outside. The total numbers of cyclonic eddies (CEs, clockwise) and anticyclonic eddies (AEs, anticlockwise) are 76 and 71, respectively. Seasonally, the number of CEs (AEs) is twice larger than the number of AEs (CEs) in winter (summer). In winter, CEs are distributed in the southern and AEs in the northern basins, respectively, but the opposite thing occurs in summer, i.e., the polarities of mesoscale eddies observed at the same location reverse seasonally. The mechanisms of polarity distribution reversal (PDR) of mesoscale eddies are examined with reanalysis data of ocean currents and winds. The results indicate that the basin-scale vorticity, wind stress curl, and the meridional shear of zonal current reverse seasonally, which are favorable to the PDR of mesoscale eddies. The possible generation mechanisms of mesoscale eddies include direct wind forcing, barotropic and baroclinic instabilities, of which the direct wind forcing should play the dominant role.

Japanese Spanish mackerel, Scomberomorus niphonius, is a commercially important, highly migratory species that is widely distributed throughout the northwestern Pacific region. However, its life history and migratory patterns are only partially understood. This study used otolith chemistry to investigate the migratory pattern of S. niphonius in the southern Yellow Sea, an important fishing ground. Transverse sections of otoliths from 15 age-1 spawning or spent individuals, comprising up to one complete migration cycle, were analyzed from the core to the margin by using laser ablation inductively coupled plasma mass spectrometry. The ratios of the element to Ca were integrated with microstructural analysis to produce age-related elemental profiles. Combining multi-elemental analysis of otolith composition with multivariate analytical models, we quantified structural changes in otolith chemistry profiles. Results revealed there were diverse changing patterns of otolith chemistry profiles for detected elements and the elements of Na, Mg, Sr and Ba were important for the chronological signal. Five clusters were identified through chronological clustering, representing the five life stages from the early stage to the spawning stage. Variation of Ba:Ca ratio was most informative, showing a step-decreasing pattern in the first four stages and a rebound in the spawning stage. These results support the hypothesized migratory pattern of S. niphonius: hatching and spending their early life in the coastal sandy ridges system of the southern Yellow Sea, migrating northeastward and offshore for feeding during juvenile stage, aggregating in early October and migrating outward to the Jeju Island for wintering, and returning to the coastal waters for spawning. This study demonstrated the value of life-history related otolith chemistry profiles combined with multivariate analytical models was a means to verify the migration patterns of S. niphonius at regional scales with potential application in fisheries assessment and management.

Parent and alkylated polycyclic aromatic hydrocarbons (alkyl-PAHs), which are a class of important toxic components of crude oil especially in the marine environment, exhibit adverse effects on aquatic life and potentially pose a human health risk. However, the lack of chronic toxicity data is one of the hindrances for alkyl-PAHs when assessing their ecological risks. In this study, predicted no-effect concentrations (PNECs) in seawater and marine sediment for ten parent- and alkyl-PAHs were derived by applying species sensitivity distributions (SSDs) and quantitative structure−activity relationships (QSARs). The local area, Dalian Bay, where an oil-spilled accident happened in 2010, was chosen as a case site to assess ecological risks for ten PAHs in surface seawaters and marine sediments. Their PNECs in seawater and sediment for protecting aquatic organisms in marine ecosystems were calculated and recommended in the range of 0.012−2.79 μg/L and 48.2−1337 ng/g (dry weight), respectively. Overall, the derived PNECs for the studied PAHs in seawater and marine sediment were comparable to those obtained by classical methods. Risk quotient results indicate low ecological risks to ecosystems for ten parent- and alkyl-PAHs in surface seawaters and surface sediments from the Dalian Bay. These findings provide a first insight into the PNECs and ecological risks of alkyl-PAHs, emphasizing the role of the computational toxicology in ecological risk assessments. The use of QSARs has been identified as a valuable tool for preliminarily assessing ecological risks of emerging pollutants, being more predictable of real exposure scenarios for risk assessment purposes.