Search Results (371)

Three-dimensional (3D) ocean physical fields are essential for understanding ocean dynamics, but reconstructing them solely from sea-surface remote sensing remains challenging. We present 3DV-Unet, an end-to-end deep learning framework that reconstructs eddy-resolving three-dimensional essential ocean variables (temperature, salinity, and currents) from multi-source satellite data. The model employs a 3D Vision Transformer bottleneck to capture cross-depth and cross-variable dependencies, ensuring physically consistent reconstruction. Trained on 2011–2019 reanalysis and satellite data, 3DV-Unet achieves RMSEs of ~0.30 °C for temperature, 0.11 psu for salinity, and 0.05 m/s for currents, with all R² values above 0.93. Error analyses further indicate higher reconstruction errors in dynamically complex regions such as the Kuroshio Extension, while spectral analysis indicates good agreement at 100 km+ but systematic deviation in the 20–100 km band. Independent validation against 6113 Argo profiles confirms its ability to reproduce realistic vertical thermohaline structures. Moreover, the reconstructed 3D fields capture mesoscale eddy structures and their life cycle, offering a valuable basis for investigating ocean circulation, energy transport, and regional variability. These results demonstrate the potential of end-to-end volumetric deep learning for advancing high-resolution 3D ocean reconstruction and supporting physical oceanography and climate studies. Full article

Heavy rainfall events in the southern Anhui region are the main meteorological disasters, often leading to floods and secondary disasters. This article explores the mechanisms supporting extreme precipitation by studying the spatiotemporal characteristics of heavy rainfall events during 2022–2024 and their related atmospheric circulation patterns. Using high-resolution precipitation data, ERA5 and GDAS reanalysis datasets, and the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model analysis, the main sources and transport pathways of water that cause heavy rainfall in the region were determined. The results indicate that large-scale circulation systems, including the East Asian monsoon (EAM), the Western Pacific subtropical high (WPSH), the South Asian high (SAH), and the Tibetan Plateau monsoon (PM), play a decisive role in regulating water vapor flux and convergence in southern Anhui. Southeast Asia, the South China Sea, the western Pacific, and inland China are the main sources of water vapor, with multi-level and multi-channel transport. The uplift effect of mountainous terrain further enhances local precipitation. The Indian Ocean basin mode (IOBM) and zonal index are also closely related to the spatiotemporal changes in rainfall and disaster occurrence. The rainstorm disaster risk assessment based on principal component analysis, the information entropy weight method, and multiple regression shows that the power index model fitted by multiple linear regression is the best for the assessment of disaster-causing rainstorm events. The research results provide a scientific basis for enhancing early warning and disaster prevention capabilities in the context of climate change. Full article

Sea surface salinity (SSS) observations play a crucial role in the study of ocean circulation, climate variability, and marine ecosystems. However, current satellite SSS products suffer from systematic biases due to factors such as radio frequency interference (RFI) and land contamination, resulting in fundamental limitations to their application for SSS monitoring. To address this issue, we propose a physics-informed neural network (PINN) approach that directly integrates radiative transfer physical processes into the neural network architecture for SMAP L2 SSS bias correction. This method ensures oceanographically consistent corrections by embedding physical constraints into the forward propagation model. The results demonstrate that PINN achieved a root mean square error (RMSE) of 0.249 PSU, representing a 5.3% to 8.5% relative performance improvement compared to conventional methods—GBRT, ANN, and XGBoost. Further temporal stability analysis reveals that PINN exhibits significantly reduced RMSE variations over multi-year periods, demonstrating exceptional long-term correction stability. Meanwhile, this method achieves more uniform bias improvement in contaminated nearshore regions, showing distinct advantages over the inconsistent correction patterns of conventional methods. This study establishes a physics-constrained machine learning framework for satellite SSS data correction by integrating oceanographic domain knowledge, providing a novel technical pathway for reliable enhancement of Earth observation data. Full article

Reconstructing the deep water salinity during the Last Glacial Maximum (LGM, 26.5~19 ka BP), corresponding to Marine Isotope Stage 2, the most recent and coldest period, is crucial for understanding glacial deep ocean circulation variation and its effect on the climate. The South China Sea (SCS) is one of the largest marginal seas in the western Pacific Ocean, where LGM deep water salinity reconstruction remains unexplored. This study employs pore water [Cl⁻] profiles acquired from boreholes of Site U1499 of IODP Expedition 367 and Sites U1431 and U1433 of IODP Expedition 349 to reconstruct the LGM salinity in the deep SCS. Utilizing a one-dimensional diffusion-advection numerical model, the LGM salinity of the deep northern SCS is determined to be 35.68 ± 0.04 g/kg, and that of the deep central SCS is 35.61 ± 0.03 g/kg, revealing an intra-basin salinity gradient of ~0.07 g/kg. LGM salinity gradients within the SCS were reduced relative to modern ones, indicating attenuated deep circulation within the SCS during the LGM. Furthermore, a diminished salinity gradient (Δ = 0.02 g/kg) across the Luzon Strait between the SCS and Pacific and an enhanced vertical stratification between Upper Circumpolar Deep Water (UCDW) and Lower Circumpolar Deep Water (LCDW) collectively support a sluggish deep Pacific circulation during the LGM. Full article

The recently developed localized particle filter (LPF) is extended to a fully coupled general circulation model (CGCM), specifically the Community Earth System Model (CESM), to assess its efficacy in assimilating multisource ocean observations, including satellite sea surface temperature (SST) and in situ temperature and salinity (TS) profiles. The LPF introduces localization in the weighting and resampling steps to avoid the filter degeneracy problem, thereby enhancing its performance in assimilating nonlinear systems. Data assimilation experiments using real ocean observations reveal that the LPF has notable advantages in improving the quality of subsurface and deep ocean temperature and salinity, particularly below 200 m. The results are evaluated against objective analysis data, confirming the potential applicability of the LPF in operational settings. Furthermore, a comparative analysis with the ensemble adjustment Kalman filter (EAKF) elucidates the merits and limitations of the LPF, and further underscores the pronounced advantage of LPF in the deep ocean. However, when TS profiles are already assimilated, supplementing the LPF with additional SST data produces adverse effects, a behavior markedly different from that of the EAKF. This discrepancy signals the need for refined data pre-processing strategies within the LPF in real operational applications. Full article

Plastic pollution is an increasing global concern, with estuaries being especially vulnerable as transition zones between freshwater and marine systems. These ecosystems often accumulate large amounts of waste, affecting wildlife and water quality. This study focuses on analysing the circulation patterns of the Ave Estuary, a small, shallow system on Portugal’s north-western coast, and their influence on litter transport and distribution. This site was selected for installing an aquatic litter removal technology under the EU-funded MAELSTROM project. A 2DH hydrodynamic model using Delft3D FM, coupled with the Wflow hydrological model, was implemented and validated. Various scenarios were simulated to assess estuarine dynamics and pinpoint zones prone to litter accumulation and flood risk. The results show that tidal action and river discharge mainly drive the estuary’s behaviour. Under low discharge, floating litter should be mostly transported toward the ocean, while high discharge conditions should result in litter movement at all depths due to stronger currents. High water levels and flooding occur mainly upstream and in specific low-lying areas near the mouth. Low-velocity zones, which can favour litter accumulation, were found around the main channel and on the western margin near the estuary’s mouth, even during high flows. These findings highlight persistent accumulation zones, even under extreme event conditions. 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

The North Atlantic Ocean is vital to Earth’s climate system. Scientific investigations have identified the Atlantic Meridional Overturning Circulation (AMOC) as a significant factor influencing global climate change. This circulation involves ocean currents that carry relatively warm, salty water northward in the upper layers, while transporting colder, less salty water southward in the deeper layers. The AMOC relies on descending water at deep convection sites in the high-latitude North Atlantic (NA), where warmer water cools, becomes denser, and sinks. A concern regarding the AMOC is that the freshening of the sea surface at these convection sites can slow it by inhibiting deep convection. Researchers have used oceanographic observations and models of Earth’s climate and ocean circulation to investigate decadal shifts in the AMOC and NA. We examined these findings to provide insights into these models, observational analyses, and palaeoceanographic reconstructions, aiming to deepen our understanding of AMOC variability and offer potential predictions for future climate change in the North Atlantic. While the influence of high-latitude freshwater is crucial and may slow the AMOC, evidence also shows a complex feedback mechanism. In this mechanism, the negative feedback from wind stress can stabilize the AMOC, partially counteracting the positive feedback effects of freshwater at high latitudes. Although some models predict significant shifts in AMOC dynamics, suggesting imminent and possibly severe deceleration, recent observational research presents a more cautious view. These data analysis studies acknowledge changes, but highlight the robustness of the AMOC, particularly in its upper arm within the Gulf Stream system. While it cannot be entirely dismissed that the AMOC may reach its tipping point within this century, an analysis of data concerning the decadal variability in the AMOC’s upper arm indicates that a collapse is unlikely within this timeframe, although significant weakening remains quite possible. Furthermore, deceleration of the AMOC’s upper arm could lead to less stable and more vulnerable North Atlantic Ocean climate patterns over extended periods. Full article

Protactinium-231 (²³¹Pa), a particle-reactive radionuclide derived from ²³⁵U decay, serves as a pivotal tracer in marine geochemistry and paleoceanography, offering unique insights into particle scavenging, deep ocean circulation, and sedimentary processes. This review synthesizes significant advances in ²³¹Pa research. A core application lies in utilizing the ²³¹Pa/²³⁰Th ratio as a sensitive proxy for reconstructing past Atlantic Meridional Overturning Circulation (AMOC) intensity, with compelling evidence indicating a substantially weakened AMOC during the Last Glacial Maximum compared to the Holocene. Major technological breakthroughs, particularly the advent of high-precision ICP-MS and TIMS methodologies, have revolutionized the quantification of ²³¹Pa in both dissolved and particulate phases, enabling spatial and temporal resolution. Looking forward, the integration of high-resolution sediment core analyses—featuring refined ²³¹Pa/²³⁰Th chronologies—with advanced climate models offers a powerful pathway to significantly enhance our mechanistic understanding of the ocean’s role in global climate regulation. This synergistic approach will help constrain the dynamics of oceanic overturning circulation and its critical functions in carbon sequestration and heat redistribution across past, present, and future climate scenarios. Full article

Hydrothermal vents are “oases” of biological productivity and endemicity on the seafloor. Chemosynthetic communities at deep-sea hydrothermal vents are characterized by high abundance and endemism. The distribution of species among these isolated habitats supports regional biodiversity and stability, so understanding the fundamental processes is a key target of conservation. Larval dispersal resulting from deep-ocean circulations is one of the major factors influencing the diversity and distributions of vent animals. By combining a biophysical model with biological larvae traits, we quantify potential larval dispersal of vent species via ocean circulation in the Azores Triple Junction. Here we present results from a biophysical model of larval dispersal run for the hydrothermal vent benthic mussel Bathymodiolus azoricus. Several scenarios were implemented, based on similar data sets, although changing values for one or two parameters, such as swimming behaviour and planktonic larvae duration. Results showed that larvae retention is the most common pattern from the Azores Triple Junction vent fields mussel. The Rainbow vent field is rather isolated, being the sink population of the Menez Gwen and Lucky Strike but with a very low number of larvae exchange. Results are discussed in the framework of spatial management to maintain the populations after an impact by natural or human disturbance. Full article

We evaluated the impact of environmental variability on lobster Panulirus argus and Panulirus laevicauda resources in the waters off Brazil and southern Cuba. This study also covered aspects of larval recruitment associated with the availability of fishing resources in the Southern and Northern Hemispheres. Satellite-generated environmental data were sampled from 18 stations, 6 of which were in the sea off southern Cuba, 6 of which were in the coastal region of Brazil, and 6 of which were offshore near Brazil, covering important lobster fishing grounds and phyllosoma-rich areas of ocean surface circulation along the offshore boundary. The Southern Oscillation Index (SOI) was used to quantify the global ocean–atmosphere variability. Other environmental parameters included in the analysis were the monthly coastal sea levels, surface temperature (SST), salinity, wind/current speed, chlorophyll-a (Chl-a) concentrations, rainfall (RF), and Amazon River discharge (ARD). Variations in the level of puerulus settlement, juveniles, and population harvest in the coastal region of Brazil and Cuba were used to better understand the impact of environmental variability on organisms in their larval stages and their subsequent recruitment to fisheries. The surface temperature, chlorophyll-a concentration, and wind/current patterns were significantly associated with the variability in puerulus settlement. Larger-scale processes (as proxied by the SOI) affected RF, ARD, and sea levels, which reached a maximum during La Niña. As for Brazil, the full-year landings prediction model included Chl-a concentration, SST, RF, and ARD and their association with lobster landings (LLs). The landing predictions for Cuba were based on fluctuations in the Chl-a concentration and SST. Full article

Using multiple reanalysis datasets, this study investigates the decadal variability in the relationship between Northeast Pacific Sea surface temperature (SST) and Arctic stratospheric ozone (ASO), with a focus on the role of atmospheric dynamics in mediating this connection. A significant decadal shift is identified around the year 2000, characterized by a weakening of the previously strong negative correlation between January–February SST anomalies and February–March ASO. Prior to 2000 (1980–2000), warm SST in the northeastern Pacific suppressed upward planetary wave propagation, resulting in decreased stratospheric wave activity and a weakened Brewer–Dobson circulation. The weakened BD circulation reduced poleward transport of tropical ozone and heat, yielding a colder, ozone-poor polar vortex. The strong relationship enabled skillful seasonal predictability of ASO using SST precursors in a linear regression model. However, post-2000 (2001–2022), the weakened planetary wave response to SST anomalies resulted in a breakdown of this relationship, yielding non-significant predictive skill. The findings highlight the non-stationary nature of ocean-stratosphere coupling and underscore the importance of accounting for such decadal shifts in climate models to improve projections of Arctic ozone recovery and its surface climate impacts. Full article

The Beibu Gulf’s ocean circulation system regulates regional marine ecosystems, sediment transport, and coastal geomorphology while also supporting vital economic activities. This study integrates one-year current observations from four in-situ current observation stations (B1−B4) with simulations using the Regional Ocean Modeling System (ROMS) to characterize circulation dynamics in the gulf. Observations show persistent northward subtidal currents west of Hainan Island year-round, primarily sustained by tidal-induced residual currents. These currents briefly reverse southward during strong northerly wind events, whereas subtidal currents in the northern Beibu Gulf are more wind-dependent, showing pronounced seasonal variations. Numerical results confirm that winter circulation is dominated by a basin-wide cyclonic gyre driven by northeasterly monsoons. In summer, circulation in the northern gulf is cyclonic under southeasterly winds, but turns anticyclonic when southwesterly winds prevail, indicating strong sensitivity to summer monsoon wind direction. By combining multi-station observations and numerical simulations, this study provides a systematic characterization of the seasonal circulation of the oceanic system in the Beibu Gulf, offering new insights into its dynamic mechanisms. Full article

Due to global warming, extreme temperature events have become increasingly prevalent, posing significant threats to both socioeconomic development and human safety. While previous studies have extensively examined the influence of individual climatic circulation systems on extreme temperature, the combined effects of multiple concurrent circulation patterns remain poorly understood. Using daily temperature data from 29 meteorological stations in Chongqing (1960–2019), this study employs linear trend analysis, correlation analysis, and random forest (RF) models to analyze spatiotemporal variations in the intensity and frequency of extreme temperature. We selected 21 climate indicators from three categories—atmospheric circulation, sea surface temperature (SST), and sea-level pressure (SLP)—to identify the primary drivers of extreme temperatures and quantify their respective contributions. The key findings are as follows: (1) All extreme intensity indices exhibited an increasing trend, with the TXx (annual maximum daily maximum temperature) showing the higher trend (0.03 °C/year). The northeastern region experienced the most pronounced increases. (2) Frequency indices also displayed an upward trend. This was particularly evident for the TD35 (number of days with maximum temperature ≥35 °C), which increased at an average rate of 0.16 days/year, most notably in the northeast. (3) The Western Pacific Subtropical High Ridge Position Index (GX) and Asia Polar Vortex Area Index (APV) were the dominant climate factors driving intensity indices, with cumulative contributions of 26.0% to 33.4%, while the Western Pacific Warm Pool Strength Index (WPWPS), Asia Polar Vortex Area Index (APV), North Atlantic Subtropical High Intensity Index (NASH), and Indian Ocean Warm Pool Strength Index (IOWP) were the dominant climate factors influencing frequency indices, with cumulative contributions of 46.4 to 49.5%. The explanatory power of these indices varies spatially across stations, and the RF model effectively identifies key circulation factors at each station. In the future, more attention should be paid to urban planning adaptations, particularly green infrastructure and land use optimization, along with targeted heat mitigation strategies, such as early warning systems and public health interventions, to strengthen urban resilience against escalating extreme temperatures. Full article

The Surface Water and Ocean Topography (SWOT) mission provides unprecedented high-resolution observations of sea-surface height. However, their direct use in ocean circulation studies is complicated by the presence of small-scale unbalanced motion signals and instrumental noise, which hinder accurate estimation of geostrophic velocities. To address these limitations, we developed an adaptive convolutional neural network (CNN)-based filtering technique that refines SWOT-derived sea-level observations. The network includes multi-head attention layers to exploit information on concurrent wind fields and standard altimetry interpolation errors. We train the model with a custom loss function that accounts for the differences between geostrophic velocities computed from SWOT sea-surface topography and simultaneous in-situ drifter velocities. We compare our method to existing filtering techniques, including a U-Net-based model and a variational noise-reduction filter. Our adaptive-filtering CNN produces accurate velocity estimates while preserving small-scale features and achieving a substantial noise reduction in the spectral domain. By combining satellite and in-situ data with machine learning, this work demonstrates the potential of an adaptive CNN-based filtering approach to enhance the accuracy and reliability of SWOT-derived sea-level and velocity estimates, providing a valuable tool for global oceanographic applications. Full article