To explore new operational forecasting methods of waves, a forecasting model for wave heights at three stations in the Bohai Sea has been developed. This model is based on long short-term memory (LSTM) neural network with sea surface wind and wave heights as training samples. The prediction performance of the model is evaluated, and the error analysis shows that when using the same set of numerically predicted sea surface wind as input, the prediction error produced by the proposed LSTM model at Sta. N01 is 20%, 18% and 23% lower than the conventional numerical wave models in terms of the total root mean square error (RMSE), scatter index (SI) and mean absolute error (MAE), respectively. Particularly, for significant wave height in the range of 3–5 m, the prediction accuracy of the LSTM model is improved the most remarkably, with RMSE, SI and MAE all decreasing by 24%. It is also evident that the numbers of hidden neurons, the numbers of buoys used and the time length of training samples all have impact on the prediction accuracy. However, the prediction does not necessary improve with the increase of number of hidden neurons or number of buoys used. The experiment trained by data with the longest time length is found to perform the best overall compared to other experiments with a shorter time length for training. Overall, long short-term memory neural network was proved to be a very promising method for future development and applications in wave forecasting.

Two kinds of regression equations are used to reproduce the sediment flux of the 26 small coastal watersheds in southeastern China. The first kind is the global equations suggested by Milliman and Syvitski (1992), Mulder and Syvitski (1996), Syvitski et al. (2003), and Syvitski and Milliman (2007). The second kind is the modified equations revised by the characteristics of the coastal watersheds, including the drainage area, mean water discharge, and mean sediment discharge. Compared with the observations of the hydrometric stations, the global equations overestimate the sediment flux by 1–2 orders of magnitude. By using the modified equations, the accuracy of the estimated sediment flux is significantly improved, with the relative error in the range of 7%–24%. The reason for the overestimation mainly caused by different parameters’ domain and regression coefficients between global rivers and study coastal watersheds. This study demonstrates that modification needs to be considered when using global regression equations to reproduce the sediment flux of the small coastal watersheds in southeastern China.

The evolution of thermohaline structure at the upper ocean during three tropical cyclones (TCs) in the Northwest Pacific was studied in this study based on successive observation by two new-style underwater gliders during fall 2018. These remote-controllable gliders with CTD sensor enabled us to explore high frequency responses of temperature, salinity, mixed and barrier layers in the upper ocean to severe TCs in this area. Results showed that three significant cooling-to-warming and stratification destructing-to-reconstructing processes at the mixed layer occurred during the lives of three TCs. The maximal cooling of SST all reached ≥0.5°C although TCs with different intensities had different minimal distances to the observed area. Under potential impacts of solar radiation, tide and inertial motions, the mixed layer depth possessed significant high-frequency fluctuations during TC periods. In addition, barrier layers appeared and vanished quickly during TCs, accompanied with varied temperature inversion processes.

The exchange flow structure was examined in the North Passage of Changjiang River Estuary, where a deep waterway project (DWP) was carried out to improve the navigability. Before the construction of the DWP, the friction effect played a significant role in shaping the transverse structure of the exchange flow. The turbulent eddy viscosity generated near the seabed can be transferred to the upper water column, which facilitated vertical momentum exchange. As a result, the landward inflow extended to –2 m below the water surface and the seaward outflow was concentrated on the shallow shoal on the southern side of the cross section. After the construction of the DWP, the turbulent mixing was suppressed as a result of density stratification. The friction felt by the water was constrained in the lower half of the water column and the vertical momentum exchange was reduced. Meanwhile, the channel became dynamically narrowed with a Kelvin number of 0.52. Therefore, the Coriolis played a minor role in shaping the transverse structure of the exchange flow. As a consequence, the exchange flow featured a vertically-sheared pattern, with outflow at the surface and inflow underneath. Additionally, the gravitational circulation was enhanced due to increase in along-channel density gradient and stratification. The exchange flow components associated with the lateral processes (residual currents induced by eddy viscosity-shear covariance and lateral advective acceleration) were reduced, which suggests that lateral processes played a minor role in modifying the along-channel dynamics when the estuary becomes dynamically-narrowed.

Oceanic turbulence measurements made by an acoustic Doppler velocimeter (ADV) suffer from noise that potentially affects the estimates of turbulence statistics. This study examines the abilities of Kalman filtering and autoregressive moving average models to eliminate noise in ADV velocity datasets of laboratory experiments and offshore observations. Results show that the two methods have similar performance in ADV de-noising, and both effectively reduce noise in ADV velocities, even in cases of high noise. They eliminate the noise floor at high frequencies of the velocity spectra, leading to a longer range that effectively fits the Kolmogorov −5/3 slope at mid-range frequencies. After de-noising adopting the two methods, the values of the mean velocity are almost unchanged, while the root-mean-square horizontal velocities and thus turbulent kinetic energy decrease appreciably in these experiments. The Reynolds stress is also affected by high noise levels, and de-noising thus reduces uncertainties in estimating the Reynolds stress.

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.

Imaging altimeter (IALT) is a new type of radar altimeter system. In contrast to the conventional nadir-looking altimeters, such as HY-2A altimeter, Jason-1/2, and TOPEX/Poseidon, IALT observes the earth surface at low incident angles (2.5°–8°), so its swath is much wider and its spatial resolution is much higher than the previous altimeters. This paper presents a wind speed inversion method for the recently launched IALT onboard Tiangong-2 space station. Since the current calibration results of IALT do not agree well with the well-known wind geophysical model function at low incidence angles, a neural network is used to retrieve the ocean surface wind speed in this study. The wind speed inversion accuracy is evaluated by comparing with the ECMWF reanalysis wind speed, buoy wind speed, and in-situ ship measurements. The results show that the retrieved wind speed bias is about –0.21 m/s, and the root-mean-square (RMS) error is about 1.85 m/s. The wind speed accuracy of IALT meets the performance requirement.

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.

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.

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.