Gonadal development is a crucial process for sexual reproduction in scleractinian corals, after the gonad matured, corals will spawn in suitable environments, understanding this process is essential for predicting their spawn time. However, there is no report on the gonadal development cycle and the spawning time of corals in Weizhou Island is currently unknown. From September 2021 to May 2022, our study focused on Acropora formosa and Favites abdita in Weizhou Island to observe their gonadal development process and spawning time. In the wild, the oocytes of A. formosa began to develop in September and matured after nine months, while the testes were observed in November and matured after two to three months. In F. abdita, the onset of oocytes was between in October and November, mature oocytes were observed after seven to eight months, with the development period of the testes was about one to two months. Both corals’ gametes matured in May. In tanks, both corals were observed to spawn between May 19 to 22, 2022 ( April 19 to 22, Chinese lunar calendar), which was consistent with their spawning observed in wild. Based on the results, we postulate that the spawning time of A. formosa and F. abdita in Weizhou Island is around April 15th, Chinese lunar calendar. This study provides valuable information on the reproductive biology of Weizhou Island corals.

The intraseasonal variability (ISV) associated with mesoscale eddies in the northern South China Sea has been significant. Comparing the intraseasonal variability of flow at different times helps to elucidate the influence of mesoscale eddies with various dynamic instability, therefore, this study analyzed the dynamic instability of mesoscale eddies in the spring of 2009 and 2020 in the northern South China Sea, to figure out the characteristics of intraseasonal variability. Based on mooring velocity data, it conducted kinetic spectral analysis, and the results demonstrated that the ISV with period of 10‒60 days in 2009 and the ISV with period of 30‒90 days in 2020 displayed a similar vertical feature, with strong intraseasonal signals primarily occurring in the upper layer above 200 m. Moreover, the ISV with period of 30‒90 days was the main intraseasonal component during the corresponding observation period. Lag-regression analysis and calculation of dynamic instability showed that the intraseasonal variation of spring 2009 was affected by fast-moving but weak surface mesoscale eddies, and the dynamic instability was modulated by baroclinic instability and barotropic instability. On the other hand, the intraseasonal variability in the spring of 2020 was influenced by strong baroclinic mesoscale eddies, which might trigger the occurrence of intraseasonal variability in the flow fields more rapidly through enhanced vertical shear of velocity. The findings of this study contribute to a deeper understanding of the impact mechanisms of mesoscale eddies on intraseasonal activities in the northern South China Sea, providing important references and a theoretical basis for ocean dynamics and climate research.

This paper investigates the characteristics of turbulent structures in combined wave-current boundary layers based on the standard $ k $-$ \varepsilon $ model. Good agreements were found between the numerical results and experimental data of the time-averaged mean velocity profiles. Periodic variations of turbulence parameters within a wave cycle (i.e. vorticity magnitudes, TKE and TKE dissipation rates etc.) were observed. The vorticity magnitudes, TKE and TKE dissipation rates all decrease during the deceleration phase, reach their minimum values during the wave trough, increase during the acceleration phase and reach their maximum values during the wave crest. The variations of turbulent structures are very high in the near-wall regions (53% for TKE dissipation rates), and are quite low in the outer regions (3% for TKE dissipation rates). The wave-current boundary layer thickness increases (decreases) during the deceleration phase (acceleration phase). The model developed in this study has solved the existing issue of low accuracy in the near-bed region by previous models based on the “high Reynolds number methods”. The present model performs well in describing the physical process of turbulence variations under the effects of wave-current interaction. This can provide some guidance for the sediment transport in coastal areas, beach erosion prediction and developments of marine renewable energy.

Doppler scatterometer is able to measure radar backscattering coefficient and Doppler frequency over sea surface, such that it can be used to retrieve sea surface wind and sea surface current simultaneously. This paper performs a study on the joint wind and current retrieval based on the observation data from an airborne Doppler scatterometer, which results are compared with those of independent retrieval. The results indicate that the accuracy of sea surface current is significantly improved by introducing the radar backscattering coefficients into the joint inversion method, however, the accuracy of the retrieved wind field from the joint inversion method is slightly lower than that of the independent wind inversion, compared to the European Centre for Medium-Range Weather Forecasts winds. This implies that the Doppler information has little influence on the wind retrieval, while the radar backscattering coefficients (the wind) have a remarkable impact on the sea surface current retrieval. The joint inversion algorithm can mitigates the effects of sea surface wind for the current retrieval. The results of this study provide a new insight to the interplay between wind inversion and current retrieval, and also provide a reference for the data processing of spaceborne Doppler scatterometer.

The tectonic evolution of the northwestern continental margin of the South China Sea were controlled by many factors, such as the Red River Fault, the Hainan mantle plume and the formation and evolution of the South China Sea. The Yinggehai Basin is located in the northwest of the South China Sea, where thick Cenozoic sediments were deposited. The Cenozoic evolution history of the northwestern continental margin of the South China Sea was recorded in detail in the Yinggehai Basin. However, which factor has mainly controlled the evolution of the Yinggehai Basin since the Cenozoic is still ambiguous. In this paper, 7 drilling wells and 23 simulated wells were selected in the Yinggehai Basin, and the sedimentation rate and subsidence rate of the Yinggehai Basin were reconstructed by empty basin tectonic subsidence analysis method. The deep structure of the Yinggehai Basin was simulated by gravity inversion method based on previous study. The results show that during the rift period, the subsidence rate of the Yinggehai Basin in the north and middle sections is larger than in the south section. There are two stages of “step acceleration subsidence” in the north and middle sections, which are 23–11.7 Ma BP and 11.7 Ma BP–present, respectively. The maximum tectonic subsidence rate can be up to 80 m/Ma in the post rift stage in the north section and about 110 m/Ma in the middle section. The maximum tectonic subsidence rate of the Southern Graben and Uplift is both close to 70 m/Ma during the periods of 11.7–5.7 Ma BP and 15.9–11.7 Ma BP, respectively. The Cenozoic subsidence of the Yinggehai Basin is consistent with the change of sedimentary rate, indicates that tectonic subsidence plays a significant role on sedimentary evolution. According to the results of gravity inversion, it may be lower crust high density anomaly intrusion underlying the Yinggehai Basin. We suggested it may be basic rock according to the drilling basalts in the sediments. By comparing with the subsidence rate of surrounding basins in the South China Sea, the acceleration subsidence in the 15.9–11.7 Ma BP may be related to the disappearance of secondary mantle convection due to the ceasing of the seafloor spreading of the South China Sea. The 5.7 Ma BP–present accelerated subsidence of the Yinggehai Basin may be related to the dextral strike-slip activity of the Red River Fault.

The Zhujiang River Mouth Basin is located in the northern shelf of the South China Sea, and its tectonic evolution is very complicated. At the same time, as one of the hydrocarbon-rich basins in offshore China, Zhujiang River Mouth Basin ranks the top in oil and gas production among the offshore basins. With the deepening of exploration, the boundary of the Zhujiang River Mouth Basin has been changing, and the southern boundary of the basin is disputed. In this paper, based on satellite gravity and magnetic anomaly data, the fault distribution of Zhujiang River Mouth Basin is re-studied and the plane location of igneous rocks is identified. The Cenozoic thickness of the study area is retrieved with high-precision seismic data, and the tectonic units of the study area are adjusted according to the processing results. The results show that the fault distribution in the study area is mainly NEE, NE and NW trending. In this study, four new faults were identified based on the satellite gravity data. The overall strike of the igneous rocks in the plane is NEE strike, but there are differences among different regional strikes. There are nearly EW trending igneous rocks in the western basin, NWW trending igneous rocks in the central basin, and no other strike in the eastern basin. According to gravity data and Cenozoic characteristics, Yangjiang Sag is divided into Yangjiang West Sag and Yangjiang East Sag, and Wenchang D Sag and Wenchang E Sag are deleted. The Beiweitan Fault is the same as the Yangjiang-Yitong Fault, which divides the basin into three parts: the west, the middle and the east. The fault strike, the plane position of igneous rock, the thickness of Cenozoic and the tectonic units of the three parts are different. The study of faults, igneous rocks and tectonic units in Zhujiang River Mouth Basin aims to provide geophysical support for subsequent basin research and oil and gas breakthrough.

El Niño-Southern Oscillation (ENSO) is an anomaly in the Tropical Pacific Ocean sea surface that can lead to extreme weather such as hail, floods, and typhoons, therefore, accurate prediction of ENSO is of great significance. An integrated graph convolutional network-transformer (GCNTR) model is presented in this paper. Firstly, transformer network is used to encode data features based on its strong focus ability of the global feature. Secondly, GCN is employed to extract features from graph data, and finally introduces a gated feature fusion mechanism to fuse the encoded features with the features extracted by GCN to achieve the accurate prediction ENSO. The results indicate that the GCNTR model achieves the prediction of ENSO 20 months in advance, which is 3 months longer than ENSOTR and 5 months longer than Transformer, and most of the prediction accuracy of the model is better than other models. Compared to the existing methods, the GCNTR model enables better prediction of ENSO.

The airborne LiDAR bathymetry (ALB) technology has the advantages of high precision, high efficiency, strong mobility and dual use of water and land. It is especially suitable for the rapid detection of complex terraforming in shallow waters such as coastal zones, islands and reefs. When the laser penetrates the water, the energy will attenuate rapidly, which makes it difficult to extract part of the seabed echo effectively and distinguish the true position of the sea bottom. Therefore, an airborne LiDAR bathymetric travel time in the water column extraction algorithm based on echo enhancement is proposed in this paper. The Gold deconvolution algorithm was used to restore the cross section shape of the target and determine the initial range of the seabed. Then, the effective range of backscattering was fitted by double exponential function, and the diffuse attenuation coefficient K_d was obtained. Finally, combined with the seabed LiDAR equation, the waveform in the initial range of the seabed is enhanced by K_d value, and the enhanced echo is decomposed by Gaussian function to determine the seabed position parameters, so as to realize the travel time in the water column extraction of ALB waveform. The feasibility of the proposed algorithm was verified by using the experimental data of RIEGL VQ-840-G ALB in Qingdao Jiaozhou Bay, and the proposed algorithm was compared with the Richardson-Lucy deconvolution model and the peak detection model. The results show that the root mean square error (RMSE) between the proposed algorithm and the single-beam point with the same name is 18.5 cm, which is 29.9% and 41.4% lower than the above two algorithms, respectively. Therefore, the proposed algorithm is feasible and can satisfy the high precision extraction of ALB waveform during water column traveling, which can provide certain technical support for the fine processing of airborne LiDAR bathymetry data.

The Moving Vessel Profiler (MVP) has the advantage of acquiring temperature and salinity profiles with high spatial resolution. However, since a pumpless CTD is used for the temperature and salinity measurements, adjusting the response time of the sensor and correcting for thermal inertia are important issues in processing the measured data and complicate the application of the data. Since the existing thermal inertia correction methods still have salinity peaks at the strong thermocline, in this work we propose a layered method to optimize the thermal inertia correction parameters based on the analysis of the measured temperature gradient profile to correct the temperature and conductivity, and thus the salinity profile. The results show that the method significantly reduces the salinity difference between the upward and downward measured profiles of the MVP and essentially eliminates the salinity peaks, especially in the thermocline. The average absolute salinity difference between the upward and downward measured profiles is reduced from 0.031 to 0.016 1, which corresponds to a 48.1% reduction in salinity error and confirms the appropriateness of the salinity profile correction method proposed in this work for the MVP.

Red Noctiluca scintillans is the main red tide species in China, which often occurs in the Bohai Sea, Yellow Sea, East China Sea and South China Sea. Recently, the red N. scintillans blooms occurred frequently, leading to an urgent need for their monitoring. However, the occurrence of red N. scintillans blooms is characterized by wide distribution range, rapid change and strip distribution. Therefore, the high spatial resolution, large coverage and short revisit period satellites are needed for red N. scintillans blooms monitoring. Although, ocean color satellites have played an important role in red tide detection, they cannot detect the strip distributed red N. scintillans blooms for their low spatial resolution. The Coastal Zone Imager (CZI) onboard HY-1C/D satellite, with high spatial resolution, wide swath and short revisit cycle, has been increasingly used for red tide monitoring. Most existing red N. scintillans blooms detection methods for HY-1C/D CZI are based on deep learning methods, which need a large number of training samples. However, the training samples are difficult to obtain, which affects the accuracy of the models. Therefore, taking red N. scintillans bloom occurred in the Honghai Bay, Guangdong Province in March 2022 as an example, the spectral features of red N. scintillans blooms were analyzed in this paper, the red tide detection method based on the high reflectance features of red N. scintillans blooms in the red and near infrared bands and turbid water in the green band was constructed for HY-1C/D CZI. The experimental results show that based on the method, red N. scintillans blooms can be detected effectively in the turbid water, with precision and F1-Score of 89.72% and 0.90 respectively. Moreover, the method has good applicability, and it is proved to be suitable for the detection of red N. scintillans blooms in different marine environments. Also, it is applicable to different broad band sensors.