Search Results (59)

The stability of coal prices is of vital importance to national energy security and macroeconomic stability. Against the backdrop of Supply-side Structural Reform and the deepening strategy of “Carbon Peaking and Carbon Neutrality” (Dual Carbon), the coal price formation mechanism has evolved into a complex system incorporating intertemporal inventory adjustment, external energy substitution, and logistics constraints. Based on monthly data from May 2016 to August 2025, this paper constructs a six-dimensional Vector Error Correction Model (VECM) comprising coal prices, raw coal production, port inventory, ocean freight rates, international oil prices, and import volumes to analyze the long-term equilibrium and short-term dynamic transmission mechanisms among these variables. The research results indicate that: First, a stable long-term cointegration relationship exists among the core variables of China’s coal market, and the long-term equilibrium mechanism remains effective despite the market volatility experienced in 2021. Second, port inventory exerts a significant negative intertemporal lag effect on prices, validating the convenience yield mechanism within the theory of storage. Third, ocean freight rates and international oil prices exhibit significant cost compounding effects and energy substitution effects, respectively, with oil price shocks demonstrating greater persistence. Fourth, compared with nominal production, the “effective supply”—integrating inventory and logistics—better explains pricing, though logistics constraints significantly amplify price volatility. Policy implications suggest establishing a dynamic early-warning mechanism based on port inventory thresholds and implementing flexible import quotas to buffer domestic supply shocks. Full article

The ocean archives massive, stable remote sensing datasets, and leveraging these data to achieve intelligent real-time recognition of marine organisms has become a core task in the field of marine remote sensing. However, in complex seabed environments, marine monitoring equipment is often constrained by limited computing power—this creates an urgent demand among oceanographers for detection algorithms with low computational complexity, which can be widely deployed on low-cost, simple marine remote sensing devices. To address this demand, this study proposes a deep learning-based algorithm for lightweight seabed organism detection efficiently (LSOD). This algorithm integrates Mamba and YOLO principles to enable efficient lightweight benthic organism detection. For LSOD’s neck, the original concatenation modules are improved, which efficiently aggregates feature layer information across backbone stages for cross-scale fusion. To further reduce the computational requirements of LSOD, a new detection head module based on group normalization and shared convolution operations is designed. These improvements maintain a reasonable computational load while enhancing the precision of the object detection network. EUDD tests indicate LSOD’s performance: the detection precision achieves 90.6% (sea cucumbers), 91.6% (sea urchins), and 93.5% (scallops). Comparisons with mainstream models confirm its superiority in detecting benthic organisms. This work is expected to provide new insights and approaches for intelligent remote sensing and analysis in marine ranches. Full article

The spontaneous emergence of macroscopic dissipative structures in systems driven by generalized chemical potentials is well established in non-equilibrium thermodynamics. Examples include atmospheric/oceanic currents, hurricanes and tornadoes, Rayleigh–Bénard convection cells and reaction–diffusion patterns. Less well recognized, however, are microscopic dissipative structures that form when the driving potential excites internal molecular degrees of freedom (electronic states and nuclear coordinates), typically via high-energy photons or coupling with ATP. Examples include dynamic nanoscale lipid rafts, kinesin or dynein motors along microtubules, and spatiotemporal Ca²⁺ signaling waves propagating through the cytoplasm. The thermodynamic dissipation theory of the origin of life asserts that the core biomolecules of all three domains of life originated as self-organized molecular dissipative structures—chromophores or pigments—that proliferated on the Archean ocean surface to absorb and dissipate the intense “soft” UV-C (205–280 nm) and UV-B (280–315 nm) solar flux into heat. Thermodynamic coupling to ancillary antenna and surface-anchoring molecules subsequently increased photon dissipation and enabled more complex dissipative processes, including photosynthesis, to dissipate lower-energy but higher-intensity UV-A and visible light. Further thermodynamic coupling to abiotic geophysical cycles (e.g., the water cycle, winds, and ocean currents) ultimately led to today’s biosphere, efficiently dissipating the incident solar spectrum well into the infrared. This paper reviews historical considerations of UV light in life’s origin and our proposal of UV-C molecular dissipative structuring of three classes of fundamental biomolecules: nucleobases, fatty acids, and pigments. Increases in structural complexity and assembly into larger complexes are shown to be driven by the thermodynamic imperative of enhancing solar photon dissipation. We conclude that thermodynamic selection of dissipative structures, rather than Darwinian natural selection, is the fundamental creative force in biology at all levels of hierarchy. Full article

The foldable quadcopter unmanned aerial vehicle (UAV), transported by an autonomous underwater vehicle (AUV) and launched subaquatically, represents cutting-edge technology for expanding ocean-sensing capabilities. However, its launch stability is severely challenged by complex cross-media flow fields. To address this, this paper employs a high-fidelity CFD method validated by experimental data, combined with dynamic overlapping mesh technology. Within a high-precision numerical wave tank, it systematically investigates the evolution of unsteady hydrodynamic characteristics throughout the entire launch process—from the drone’s emergence from the launch tube to its crossing of the water-air interface. Findings reveal that elevated initial launch velocities substantially alter surface flow patterns, inducing shear stress imbalances and complex flow separation on the trailing surface. This significantly amplifies lateral disturbance forces and yawing moments, constituting primary sources of motion instability. More critically, this study first uncovers and quantifies the hydrodynamic interference mechanism during the synchronous launch of dual vehicles: the wake field generated by the lead vehicle imposes a significant flow-shielding effect on the trailing vehicle. This effect alters its longitudinal forces while introducing an asymmetric pressure distribution, thereby generating substantial lateral interference. This study’s profound elucidation of these core hydrodynamic mechanisms provides crucial theoretical foundations for developing safe launch strategies, trajectory prediction, and anti-interference controller design for future AUV-UAV cooperative systems. Full article

The Eastern Adriatic Sea is biogeographically complex, yet knowledge of its hydromedusae is fragmented across two centuries of uneven sampling and shifting taxonomy. This review integrates historical faunistic records (pre-1950), mid-century programmes (1950–2000), modern quantitative time series (post-2000), and citizen science observations to compile an updated checklist of 98 non-siphonophoran hydrozoan taxa. Records are synthesised across eight sub-regions, although the most continuous research has focused on the Northern Adriatic and the open South Adriatic. The clearest long-term signal is in the Northern Adriatic, where diversity collapsed by >60% from the 1960s to the 1980s, largely through the loss of meroplanktonic taxa with benthic polyp stages under eutrophication-driven hypoxia. Since 2000, oligotrophication coincides with a partial recovery, marked by the re-emergence of meroplankton and episodic intrusions of oceanic holoplankton (including Trachymedusae) linked to circulation regimes (BiOS). For the open South Adriatic, bathymetric distributions and diel vertical migration patterns are synthesised to characterise a persistent offshore core. Taxonomic updates and information on non-indigenous and bloom-forming taxa are provided. Methodological biases and gaps, especially polyp-stage ecology and spatial sampling voids, are highlighted, and routine DNA barcoding is recommended. The checklist provides a baseline for tracking change in a shifting ecosystem. Full article

Mylonitic mantle peridotites exposed at the Tosa Megamullion in the Shikoku Basin, Philippine Sea, provide direct evidence for amagmatic ductile shear deformation of the upper mantle beneath a back-arc spreading center. Oceanic core complexes (OCCs), or megamullions, are dome-shaped structures formed by detachment faulting and occur locally along slow-spreading mid-ocean ridges and back-arc basins, where they expose fault rocks derived from ductile shear zones in the lower crust and upper mantle. The Shikoku Basin hosts several OCCs, including the Tosa Megamullion, which formed during the early stage of back-arc spreading. In this study, nine ultramafic rocks were collected from the Tosa Megamullion using the submersible Shinkai6500 during cruise YK23-05S. Although all samples were highly serpentinized, several preserved primary peridotitic textures were composed mainly of olivine, orthopyroxene, with subordinate clinopyroxene, plagioclase, and spinel. Seven samples exhibit well-developed foliation and porphyroclastic textures dominated by orthopyroxene porphyroclasts, ranging from rounded to strongly elongated forms, commonly showing microkinks and undulose extinction. Crystallographic preferred orientations (CPOs) of three representative samples, analyzed using SEM-EBSD, reveal E-type-dominant olivine fabrics characterized by the (001)[100] slip system, with a subordinate contribution from C-type (100)[001] slip. These CPOs suggest deformation under non-dry conditions involving moderate hydration and/or elevated differential stress. These results indicate that the ultramafic rocks from the Tosa Megamullion represent mantle-derived mylonitic peridotites formed by ductile shear beneath the spreading axis and subsequently exhumed under strongly magma-poor, amagmatic conditions. The Tosa Megamullion thus represents an amagmatic end-member of the OCC formation in back-arc basins, dominated by tectonic strain localization rather than by magmatic accretion. Full article

To quantitatively assess the storm surge induced by Super Typhoon Doksuri (2023) along the complex coastline of Fujian Province, a high-resolution Finite-Volume Coastal Ocean Model (FVCOM) was developed, driven by a refined Holland–ERA5 hybrid wind field with integrated physical corrections. The hybrid approach retains the spatiotemporal coherence of the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis in the far field, while incorporating explicit inner-core adjustments for quadrant asymmetry, sea-surface-temperature dependency, and bounded decay after landfall. A series of numerical experiments were conducted, including paired tidal-only and full storm-forcing simulations, along with a systematic sensitivity ensemble in which bottom-friction parameters were perturbed and the anomalous (typhoon-related) wind component was scaled by factors ranging from 0.8 to 1.2. Static sea-level rise (SLR) scenarios (+0.3 m, +0.5 m, +1.0 m) were imposed to evaluate their influence on extreme water levels. Storm surge extremes were analyzed using a multi-scale coastal buffer framework, comparing two extreme extraction methods: element-mean followed by time-maximum, and node-maximum then assigned to elements. The model demonstrates high skill in reproducing astronomical tides (Pearson r = 0.979–0.993) and hourly water level series (Pearson r > 0.98) at key validation stations. Results indicate strong spatial heterogeneity in the sensitivity of surge levels to both bottom friction and wind intensity. While total peak water levels rise nearly linearly with SLR, the storm surge component itself exhibits a nonlinear response. The choice of extreme-extraction method significantly influences design values, with the node-based approach yielding peak values 0.8% to 4.5% higher than the cell-averaged method. These findings highlight the importance of using physically motivated adjustments to wind fields, extreme-value analysis across multiple coastal buffer scales, and uncertainty quantification in future SLR-informed coastal risk assessments. By integrating analytical, physics-based inner-core corrections with sensitivity experiments and multi-scale analysis, this study provides an enhanced framework for storm surge modeling suited to engineering and coastal management applications. Full article

Long-term high-resolution spatial gridded altimeter-derived significant wave height (SWH) data with daily temporal resolution are fundamental to revealing the detailed processes through which weather systems influence the ocean. However, elucidation of those processes is hampered by the sparse coverage and narrow width of the swath of altimeter-derived SWHs. The core problem is how best to extract the spatial structure and then fill missing values around the daily swaths. Although recent developments in deep learning methods have improved the extraction of spatial features, progress regarding the reconstruction of gridded altimeter daily SWHs remains limited. This study reconstructed daily 0.25° × 0.25° gridded SWHs from 1993 to 2024 using a partial convolutional U-Net model with attention and residual blocks. Comparison between the daily reconstructed SWHs and ERA5 SWHs revealed that the reconstructed SWHs improved the accuracy for SWHs of >2.5 m, which are usually underestimated in the ERA5 data. The greatest differences were in China’s offshore waters, especially in the region of the Taiwan Strait and in waters influenced by the Huanghai Warm Current. This study highlights the importance of altimeter swath-derived SWHs in reconstructed gridded SWH datasets, particularly in complex straits and under high sea state conditions. Full article

Formation rendezvous is a critical phase during the deployment or recovery of multiple unmanned underwater vehicles (UUVs) in cooperative missions, and represents one of the core problems in multi-UUV cooperative planning. In practical marine environments with obstacles and currents, multiple constraints must be simultaneously satisfied, including obstacle avoidance, inter-UUV collision prevention, kinematic limitations, and specified initial and terminal states. These requirements make energy-optimal trajectory planning for multi-UUV formation rendezvous highly challenging. Traditional integrated cooperative planning methods often struggle to obtain optimal or even feasible solutions due to the complexity of constraints and the vastness of the solution space. To address these issues, a dual-layer planning framework for multi-UUV formation rendezvous trajectory planning in environments with obstacles and currents is proposed in this paper. The framework consists of an initial individual trajectory planning layer and a secondary cooperative planning layer. In the initial individual trajectory planning stage, the Grey Wolf Optimization (GWO) algorithm is employed to optimize high-order terms of polynomial curves, generating initial trajectories for individual UUVs that satisfy obstacle avoidance, kinematic constraints, and state requirements. These trajectories are then used as inputs to the secondary cooperative planning stage. In the cooperative stage, a Self-Adaptive Particle Swarm Optimization (SAPSO) is introduced to explicitly address inter-UUV collision avoidance while incorporating all individual constraints, ultimately producing a cooperative rendezvous trajectory that minimizes overall energy consumption. To validate the effectiveness of the proposed method, a simulation environment incorporating vortex flow fields and real-world island topography was constructed. Simulation results demonstrate that the proposed hierarchical trajectory planning method is capable of generating energy-optimal formation rendezvous trajectories that satisfy multiple constraints for multi-UUV systems in environments with obstacles and ocean currents, highlighting its strong potential for practical engineering applications. Full article

Convective instabilities at various boundary layers in the earth’s mantle—including the core–mantle boundary, mantle transition zone and lithosphere-asthenosphere boundary— result in upwellings (mantle plumes) and downwellings (subducting slabs). While hotspot volcanism is traditionally linked to mantle plumes, their structure, origins, evolution, and death remain subjects of ongoing debate. Recent progress in seismic tomography has revealed a complex plumbing system connecting the core–mantle boundary and the surface. In particular, recent seismic imaging results suggest the presence of large-scale ponding zones between 660 km and ∼1000 km, associated with several mantle plumes around the globe. The broad upwellings originating from the CMB spread laterally beneath the 660 km seismic discontinuity, forming extensive ponding zones several thousand kilometers wide and extending up from an approximately 1000 km depth. Similar ponding zones are also observed for downwellings, with stagnant subducting slabs, within the 660–1000 km depth range. Here, we review evidence for wide ponding zones characterized by low seismic velocities and anomalous radial and azimuthal anisotropies in light of recent high-resolution regional studies below La Réunion Island in the Indian Ocean and below St Helena/Ascension in the southern Atlantic Ocean. We review and discuss possible interpretations of these structures, as well as possible mineralogical, geodynamic implications and outlook for further investigations aiming to improve our understanding of the mantle plumbing system. Full article

The detection of internal solitary waves (ISWs) in the ocean using Synthetic Aperture Radar (SAR) images is important for the safety of marine engineering structures. Based on 4120 Sentinel SAR images obtained from 2014 to 2024, an ISW dataset covering the Andaman Sea (AS), the South China Sea (SCS), the Sulu Sea (SS), and the Celebes Sea (CS) is constructed, and a deep learning dataset containing 3495 detection samples and 2476 segmentation samples is also established. Based on the YOLOv8 lightweight model, combined with an anti-interference strategy, a multi-size block detection strategy, and a post-processing repair module, an ISW detection method is proposed. This method reduces the false detection rate by 44.20 percentage points in terms of anti-interference performance. In terms of repair performance, the repair rate reaches 85.2%, and the error connection rate is less than 3.1%. The detection results of applying this method to Sentinel images in multiple sea areas show that there are significant regional differences in ISW activities in different sea areas: in the AS, ISW activities peak in the dry season of March and are mainly concentrated in the eastern and southern regions; the western part of the SS and the southern part of the CS are also the core areas of ISW activities. From the perspective of temporal characteristics, the SS maintains a relatively high ISW activity level throughout the dry season, while the CS exhibits more complex seasonal dynamic features. The lightweight detection method proposed in this study has good applicability and can provide support for marine disaster prevention work. Full article

The El Niño–Southern Oscillation (ENSO) is the most consequential mode of interannual climate variability on the planet, yet its prediction has become complex due to the inability of classical paradigms to explain the observed co-evolution of the tropical mean state and interannual variability on decadal timescales. This article synthesizes the extensive research on ENSO rectification, exploring a paradigm that resolves this causality problem by recasting ENSO as an active architect of its own mean state. Tracing the intellectual development of this theory, starting from fundamental concepts such as the “dynamical thermostat” and “heat pump” hypotheses, modern analysis has identified the core physical mechanism as nonlinear dynamical heating (NDH), which is rooted in nonlinear heat advection during asymmetric ENSO cycles. The convergence of evidence from forced ocean models and observational diagnostics confirms a rectified signal characterized by an off-equatorial spatial pattern, providing a primary mechanism for tropical Pacific decadal variability (TPDV). By establishing a coherent framework linking high-frequency asymmetry with low-frequency variations, this review lays the foundation for future research and emphasizes the critical role of the rectification effect in improving decadal climate prediction. Full article

In the context of global climate change and accelerated urbanization, coastal cities face severe threats from storm surges, and accurately predicting coastal water level changes during storm surges has become a core technological demand for disaster prevention and reduction. Storm surges are caused by atmospheric pressure and wind conditions, and their destructive power is closely related to the morphology of the coastline. Traditional tide level prediction models often face difficulties in boundary condition parameterization. Tide level changes result from the combined effect of various complex processes. In past prediction studies, harmonic analysis and numerical simulations have dominated, each with their own limitations. Although machine learning applications in tide prediction have garnered attention, issues such as data inconsistency or missing data still exist. The physical–data fusion approach aims to overcome the limitations of single methods but still faces some challenges. This paper proposes a Deep-Numerical-Reinforcement learning fusion prediction model (DNR), which adopts ensemble learning. First, deep learning models and the numerical model Finite-Volume Coastal Ocean Model (FVCOM) are used to predict tide levels at different tide stations, and then a fusion approach based on the improved reinforcement learning model DDPG_dual is applied for model assimilation. This reinforcement learning fusion model includes a module specifically designed to handle tide extreme points. In the case of the Typhoon Mangkhut storm surge, the DNR model achieved the best results for tide level predictions at six tide stations in the South China Sea. Full article

Salinity extremes (SEs) play a crucial role in marine ecosystems, ocean circulation, and climate variability. Understanding their distribution and drivers is essential for predicting changes in ocean salinity under climate change, particularly in dynamic regions such as the Hawaiian Islands, where mesoscale eddies significantly modulate water mass properties. This study investigates the three-dimensional characteristics of SEs and their responses to mesoscale eddies using mooring observations and sea surface salinity data. We find that high salinity extremes (HSEs) generally occur more frequently than low salinity extremes (LSEs) in the study region, though LSEs exhibit greater duration and intensity. Mesoscale eddies modulate SEs significantly—anticyclonic eddies (AEs) enhance LSEs, whereas cyclonic eddies (CEs) promote HSEs in the upper layer. This relationship reverses in the deeper layer, with AEs favoring HSEs and CEs enhancing LSEs. These opposing effects are driven by a vertical displacement of the subsurface salinity maximum layer, where CEs lift high-salinity subsurface water to the upper ocean via upwelling, creating HSEs in the upper layer and LSEs in the deeper layer, while AEs subduct high-salinity water downward, reducing upper-layer salinity (LSEs) but increasing deeper-layer salinity (HSEs) via downwelling. Spatially, CEs exhibit a single-core high-salinity anomaly, displaced westward by 0.3 times of the eddy radius from the eddy center, with HSEs peaking in frequency and intensity near the core. In contrast, AEs display a dipole salinity anomaly (low northwest/high southeast), aligning with LSE frequency distribution, while HSEs show an inverse pattern. Mooring data further reveal that AE-LSE co-occurrence is highest within 1.2 times of the eddy radius, whereas CE-HSE probability declines with eddy intensity. Notably, AE-HSE and CE-LSE probabilities, though initially weaker, surpass AE-LSE and CE-HSE at certain depths, underlining the complexity of depth-dependent eddy modulation. These findings may advance understanding of ocean salinity dynamics and provide insights into how mesoscale processes modulate extreme events, with implications for marine biogeochemistry and climate modeling. Full article

Based on the new high-resolution multibeam bathymetry data collected by the “Dongfanghong 3” vessel in 2023 in the Parece Vela Basin (PVB) and previous magnetic anomaly data, we systematically analyze the seafloor topographical changes of abyssal hills and oceanic core complexes (OCCs) in the “Chaotic Terrain” region, and the revised seafloor spreading model is constructed in the PVB. Using detailed analysis of the seafloor topography, we identify typical geomorphological features associated with seafloor spreading, such as regularly aligned abyssal hills and OCCs in the PVB. The direction variations of seafloor spreading in the PVB are closely related to mid-ocean ridge rotation and propagation. The formation of OCCs in the “Chaotic Terrain” can be explained by links to the continuous and persistent activity of detachment faults and dynamic adjustments controlled by variations of deep magma supply in the different segments in the PVB. We use 2D discrete Fourier image analysis of the seafloor topography to calculate the aspect ratio (AR) values of abyssal hills in the western part of the PVB. The AR value variations reveal a distinct imbalance in magma supply across various regions during the basin spreading process. Compared to the “Chaotic Terrain” area, the region with abyssal hills indicates a higher magma supply and greater linearity on seafloor topography. AR values fluctuated between 2.1 and 1.7 of abyssal hills in the western segment, while in the “Chaotic Terrain”, they dropped to 1.3 due to the lower magma supply. After the formation of the OCC-1, AR values increased to 1.9 in the eastern segment, and this shows the increase in magma supply. Based on changes in seafloor topography and variations in magma supply across different segments of the PVB, we propose that the seafloor spreading process in the magnetic anomaly linear strip 9-6A of the PVB mainly underwent four formation stages: ridge rotation, rift propagation, magma-poor supply, and the maturation period of OCCs. Full article