Estimated ocean subsurface fields derived from satellite observations provide potential data sources for operational marine environmental monitoring and prediction systems. This study employs a statistic regression reconstruction method, in combination with domestic autonomous sea surface height and sea surface temperature observations from the Haiyang-2 (HY-2) satellite fusion data, to establish an operational quasi-real-time three-dimensional (3D) temperature and salinity products over the Maritime Silk Road. These products feature a daily temporal resolution and a spatial resolution of 0.25° × 0.25° and exhibit stability and continuity. We have demonstrated the accuracy of the reconstructed thermohaline fields in capturing the 3D thermohaline variations through comprehensive statistical evaluations, after comparing them against Argo observations and ocean analysis data from 2022. The results illustrate that the reconstructed fields effectively represent seasonal variations in oceanic subsurface structures, along with structural changes resulting from mesoscale processes, and the upper ocean’s responses to tropical cyclones. Furthermore, the incorporation of HY-2 satellite observations notably enhances the accuracy of temperature and salinity reconstructions in the Northwest Pacific Ocean and marginally improves salinity reconstruction accuracy in the North Indian Ocean when compared to the World Ocean Atlas 2018 monthly climatology thermohaline fields. As a result, the reconstructed product holds promise for providing quasi-real-time 3D temperature and salinity field information to facilitate fast decision-making during emergencies, and also offers foundational thermohaline fields for operational ocean reanalysis and forecasting systems. These contributions enhance the safety and stability of ocean subsurface activities and navigation.

Synthetic aperture radar (SAR) and wave spectrometers, crucial in microwave remote sensing, play an essential role in monitoring sea surface wind and wave conditions. However, they face inherent limitations in observing sea surface phenomena. SAR systems, for instance, are hindered by an azimuth cut-off phenomenon in sea surface wind field observation. Wave spectrometers, while unaffected by the azimuth cutoff phenomenon, struggle with low azimuth resolution, impacting the capture of detailed wave and wind field data. This study utilizes SAR and surface wave investigation and monitoring (SWIM) data to initially extract key feature parameters, which are then prioritized using the extreme gradient boosting (XGBoost) algorithm. The research further addresses feature collinearity through a combined analysis of feature importance and correlation, leading to the development of an inversion model for wave and wind parameters based on XGBoost. A comparative analysis of this model with ERA5 reanalysis and buoy data for of significant wave height, mean wave period, wind direction, and wind speed reveals root mean square errors of 0.212 m, 0.525 s, 27.446°, and 1.092 m/s, compared to 0.314 m, 0.888 s, 27.698°, and 1.315 m/s from buoy data, respectively. These results demonstrate the model’s effective retrieval of wave and wind parameters. Finally, the model, incorporating altimeter and scatterometer data, is evaluated against SAR/SWIM single and dual payload inversion methods across different wind speeds. This comparison highlights the model’s superior inversion accuracy over other methods.

The Agulhas system is the strongest western boundary current system in the Southern Hemisphere and plays an important role in modulating the Indian-to-Atlantic Ocean water exchange by the Agulhas leakage. It is difficult to measure in situ transport of the Agulhas leakage as well as the Agulhas retroflection position due to their intermittent nature. In this study, an innovative kinematic algorithm was designed and applied to the gridded altimeter observational data, to ascertain the longitudinal position of Agulhas retroflection, the stability of Agulhas jet stream, as well as its strength. The results show that the east-west shift of retroflection is related neither to the strength of Agulhas current nor to its stability. Further analysis uncovers the connection between the westward extension of Agulhas jet stream and an anomalous cyclonic circulation at its northern side, which is likely attributed to the local wind stress curl anomaly. To confirm the effect of local wind forcing on the east-west shift of retroflection, numerical sensitivity experiments were conducted. The results show that the local wind stress can induce a similar longitudinal shift of the retroflection as altimetry observations. Further statistical and case study indicates that whether an Agulhas ring can continuously migrate westward to the Atlantic Ocean or re-merge into the main flow depends on the retroflection position. Therefore, the westward retroflection may contribute to a stronger Agulhas leakage than the eastward retroflection.

Surface Water and Ocean Topography (SWOT) is a next-generation radar altimeter that offers high resolution, wide swath, imaging capabilities. It has provided free public data worldwide since December 2023. This paper aims to preliminarily analyze the detection capabilities of the Ka-band radar interferometer (KaRIn) and Nadir altimeter (NALT), which are carried out by SWOT for internal solitary waves (ISWs), and to gather other remote sensing images to validate SWOT observations. KaRIn effectively detects ISW surface features and generates surface height variation maps reflecting the modulations induced by ISWs. However, its swath width does not completely cover the entire wave packet, and the resolution of L2/L3 level products (about 2 km) cannot be used to identify ISWs with smaller wavelengths. Additionally, significant wave height (SWH) images exhibit blocky structures that are not suitable for ISW studies; sea surface height anomaly (SSHA) images display systematic left-right banding. We optimize this imbalance using detrending methods; however, more precise treatment should commence with L1-level data. Quantitative analysis based on L3-level SSHA data indicates that the average SSHA variation induced by ISWs ranges from 10 cm to 20 cm. NALTs disturbed by ISWs record unusually elevated SWH and SSHA values, rendering the data unsuitable for analysis and necessitating targeted corrections in future retracking algorithms. For the normalized radar cross section, Ku-band and four-parameter maximum likelihood estimation retracking demonstrated greater sensitivity to minor changes in the sea surface, making them more suitable for ISW detection. In conclusion, SWOT demonstrates outstanding capabilities in ISW detection, significantly advancing research on the modulation of the sea surface by ISWs and remote sensing imaging mechanisms.

A high-resolution customized numerical model is used to analyze the water transport in the three major water passages between the Andaman Sea (AS) and the Bay of Bengal, i.e., the Preparis Channel (PC), the Ten Degree Channel (TDC), and the Great Channel (GC), based on the daily averaged simulation results ranging from 2010 to 2019. Spectral analysis and Empirical Orthogonal Function (EOF) methods are employed to investigate the spatiotemporal variability of the water exchange and controlling mechanisms. The results of model simulation indicate that the net average transports of the PC and GC, as well as their linear trend, are opposite to that of the TDC. This indicates that the PC and the GC are the main inflow channels of the AS, while the TDC is the main outflow channel of the AS. The transport variability is most pronounced at surface levels and between 100 m and 200 m depth, likely affected by monsoons and circulation. A 182.4-d semiannual variability is consistently seen in all three channels, which is also evident in their second principal components. Based on sea level anomalies and EOF analysis results, this is primarily due to equatorial winds during the monsoon transition period, causing eastward movement of Kelvin waves along the AS coast, thereby affecting the spatiotemporal characteristics of the flow in the AS. The first EOF of the PC flow field section shows a split at 100 m deep, likely due to topography. The first EOF of the TDC flow field section is steady but has potent seasonal oscillations in its time series. Meanwhile, the first EOF of the GC flow field section indicates a stable surface inflow, probably influenced by the equatorial Indian Ocean’s eastward current.

Quality control (QC) is an essential procedure in scatterometer wind retrieval, which is used to distinguish good-quality data from poor-quality wind vector cells (WVCs) for the sake of wind applications. The current wind processor of the China-France Oceanography Satellite (CFOSAT) scatterometer (CSCAT) adopts a maximum likelihood estimator (MLE)-based QC method to filter WVCs affected by geophysical noise, such as rainfall and wind variability. As the first Ku-band rotating fan-beam scatterometer, CSCAT can acquire up to 16 observations over a single WVC, giving abundant information with diverse incidence/azimuth angles, as such its MLE statistical characteristics may be different from the previous scatterometers. In this study, several QC indicators, including MLE, its spatially averaged value (MLE_m), and the singularity exponents (SE), are analyzed using the collocated Global Precipitation Mission rainfall data as well as buoy data, to compare their sensitivity to rainfall and wind quality. The results show that wind error characteristics of CSCAT under different QC methods are similar to those of other Ku-band scatterometers, i.e., SE is more suitable than other parameters for the wind QC at outer-swath and nadir regions, while MLE_m is the best QC indicator for the sweet region WVCs. Specifically, SE is much more favorable than others at high wind speeds. By combining different indicators, an improved QC method is developed for CSCAT. The validation with the collocated buoy data shows that it accepts more WVCs, and in turn, improves the quality control of CSCAT wind data.

Accurate simulation of the evolution of freak waves by the wave phase focusing method requires accurate linear and nonlinear properties, especially in deep-water conditions. In this paper, we analyze the ability to simulate deep-water focused waves of a two-layer Boussinesq-type (BT) model, which has been shown to have excellent linear and nonlinear performance. To further improve the numerical accuracy and stability, the internal wave-generated method is introduced into the two-layer Boussinesq-type model. Firstly, the sensitivity of the numerical results to the grid resolution is analyzed to verify the convergence of the model; secondly, the focused wave propagating in two opposite directions is simulated to prove the symmetry of the numerical results and the feasibility of the internal wave-generated method; thirdly, the limiting focused wave condition is simulated to compare and analyze the wave surface and the horizontal velocity of the profile at the focusing position, which is in good agreement with the measured values. Meanwhile the simulation of focused waves in very deep waters agrees well with the measured values, which further demonstrates the capability of the two-layer BT model in simulating focused waves in deep waters.

The coal-measure source rock in the Chinese sea area plays a significant role as a hydrocarbon source rock, with its genetic environment, development and distribution, and hydrocarbon generation potential serving as essential factors for the exploration of coal-type oil and gas fields. This study focuses on the coal-measure source rock of the Paleogene Enping Formation in the Zhu ⅠDepression, located in the northern South China Sea. The main geological insights obtained are as follows. The coal measures of the Enping Formation are developed in a warm and wet tropical-subtropical climate. The development environment of the coal-measure source rock in the Enping Formation includes the braided river delta upper plain peat swamp, characterized by dry forest swamp coal facies with relatively thick coal seams and a small number of layers. The braided river delta lower plain swamp-interdistributary bay of braided river delta front represents a forest edge-wetland herbaceous swamp coal facies with numerous layers of thin coal seams and poor stability. The shore swamp corresponds to an open water swamp coal facies with multiple layers of thin coal seams and poor stability. The organic matter abundance in the braided river delta upper plain is the highest, followed by the braided river delta lower plain-braided river delta front, and the shore-shallow lake. The organic matter type is predominantly type Ⅱ₁. Thermal evolution analysis suggests that the organic matter has progressed into a substantial oil generation stage. The hydrocarbon generation potential of the coal-measure source rock in the Enping Formation is the highest in the braided river delta upper plain, followed by the braided river delta lower plain-braided river delta front and the shore-shallow lake. Overall, this study proposes three organic facies in the coal-measure source rock of the Enping Formation: upper-plain swamp-dry forest swamp facies, lower plain-interdistributary bay-forest-herbaceous swamp facies, and lake swamp-herbaceous swamp facies.

Based on high-resolution 3D seismic data acquired in the Pearl (Zhujiang) River Mouth Basin of the northern South China Sea, this study investigated the geometry, spatial extension, and throw distribution of the post-rift normal fault through detailed seismic interpretation and fault modeling. A total of 289 post-rift normal faults were identified in the study area and can be classified into four types: (1) isolated normal faults above the carbonate platform; (2) isolated normal faults cutting through the carbonate platform; (3) conjugate normal faults, and (4) connecting normal faults. Throw distribution analysis on the fault planes show that the vertical throw profiles of most normal fault exhibit flat-topped profiles. Isolated normal faults above the carbonate platform exhibit roughly concentric ellipses with maximum throw zones in the central section whereas the normal faults cutting through the carbonate platform miss the lowermost section due to the chaotic seismic reflections in the interior of the carbonate platform. The vertical throws of conjugate normal faults anomalously decrease toward their intersection region on the fault plane whereas the connecting normal faults present two maximum throw zones in the central section of the fault plane. According to the symmetric elliptical distribution model of fault throw, an estimation was made indicating that normal faults cutting through the carbonate platform extended downward between −1 308 s and −1 780 s (two-way travel time) in depth and may not penetrate the entire Liuhua carbonate platform. Moreover, it is observed that the distribution of karst caves on the top of the carbonate platform disaccord with those of hydrocarbon reservoirs and the post-rift normal faults cutting through the carbonate platform in the study area. We propose that these karst caves formed most probably by corrosive fluids derived from magmatic activities during the Dongsha event, rather than pore waters or hydrocarbons.

The deep crustal structure is closely related to oil and gas reserves. Predicting the oil and gas enrichment of depressions based on the Moho depth and crustal thickness is a promising research topic with significant implications for guiding exploration in petroliferous basins. In this study, seismic data were used as a constraint on the use of satellite gravity anomaly inversion to obtain the distribution of Moho depth and crustal thickness in the Bohai Basin. Stretching factors were calculated to analyze the differential distribution of deep crustal structural activity. Four indicators, including the minimum Moho depth, minimum crustal thickness, sum of Moho stretching factors, and sum of crustal stretching factors, were selected. Principal component analysis was applied to reduce the dimensionality of the multi-indicator system and obtain an oil and gas enrichment score for quantitative prediction of favorable prolific depressions. The deviation between the inverted Moho depth and seismic constraints was small; thus, the data effectively reflect the variations in the characteristics of each depression. The analysis revealed significant statistical features related to the minimum Moho depth/crustal thickness and the sum of Moho/crustal stretching factors associated with prolific depressions. Based on the oil and gas enrichment score, the depressions were classified into four categories related to their different deep crustal structural characteristics. Highly active Class Ⅰ, Class Ⅱ, and Class Ⅲ depressions are predicted to be favorable prolific depressions. This study expands the research on quantitatively predicting favorable prolific depressions in the Bohai Basin using the deep crustal structure and can contribute to reducing production costs and improving exploration efficiency in future explorations.