Search Results (351)

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

Under harsh sea states, the dynamic characteristics of ocean mesoscale eddies (OMEs) become significantly more complex, posing substantial challenges to their accurate detection and identification. In this study, we propose an artificial intelligence detection method for OMEs based on the domain adaptation technique to accurately perform pixel-level segmentation and ensure its effectiveness under harsh sea states. The proposed model (LCNN) utilizes large kernel convolution to increase the model’s receptive field and deeply extract eddy features. To deal with the pronounced cross-domain distribution shifts induced by harsh sea states, an adversarial learning framework (ADF) is introduced into LCNN to enforce feature alignment between the source (normal sea states) and target (harsh sea states) domains, which can also significantly improve the segmentation performance in our constructed dataset. The proposed model achieves an accuracy, precision, and Mean Intersection over Union of 1.5%, 6.0%, and 7.2%, respectively, outperforming the existing state-of-the-art technologies. Full article

Conventional altimeter satellites, such as TOPEX/Poseidon and Jason series, can identify ocean mesoscale eddies (MEs) but cannot effectively distinguish submesoscale eddies (SMEs) due to horizontal resolution limitations. The emergence of the Surface Water and Ocean Topography (SWOT) satellite has enabled the resolution (or detection) of SMEs. At present, Data Unification and Altimeter Combination System (DUACS) (MEs-resolving) and SWOT (SMEs-resolving) satellites operate concurrently in orbit, however a systematic comparison and analysis of their observational outputs has yet to be conducted. Using a closed-contour scalar analysis method, this study identifies SMEs in the tropical western Pacific Ocean and compares the results with those from the dataset. The latitude-dependent Rossby deformation radius is employed to differentiate MEs from SMEs. For MEs, SWOT detects 176 per 10.5-day sub-cycle, while DUACS detects 162, which are roughly equivalent. For SMEs, SWOT identifies 273 per sub-cycle, far exceeding the 13 detected by DUACS. For amplitudes, DUACS measures 5.22 cm and 3.67 cm for MEs and SMEs, respectively, while the values reported by the SWOT satellite are 6.13 cm and 4.49 cm. In both datasets, cyclonic eddies are more prevalent in all cases except for the SMEs detected by SWOT, where anticyclonic eddies slightly outnumber cyclonic eddies. Additionally, during the trial operation and scientific orbit phases, SWOT is able to resolve 29 SMEs per orbit. The results indicate that high-resolution data can distinguish phenomena that conventional satellite altimeters cannot capture, providing valuable references for the analysis and application of SME characteristics. 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 spatial and seasonal characteristics of submesoscales in the Northwest Pacific Subtropical Ocean are thoroughly investigated here using a submesoscale-permitting model within a localized multiscale energetics framework, in which three scale windows termed background, mesoscale, and submesoscale are decomposed. It is found that submesoscale energetics are highly geographically inhomogeneous. In the Luzon Strait, baroclinic and barotropic instabilities are the primary mechanisms for generating submesoscale available potential energy (APE) and kinetic energy (KE), and they exhibit no significant seasonal variations. Although buoyancy conversion experiences pronounced seasonal cycles and serves as the main sink of submesoscale APE in winter and spring, its contribution to submesoscale KE is negligible. The major sinks of submesoscale KE are advection, horizontal pressure work, and dissipation. In the Western Boundary Current transition and Subtropical Countercurrent (STCC) interior open ocean zone, submesoscales undergo significant seasonality, with large magnitudes in winter and spring. In spring and winter, baroclinic instability dominates the generation of submesoscale APE via forward cascades, while KE is mainly energized by buoyancy conversion and dissipated by the residual term. Meanwhile, in summer and autumn, submesoscales are considerably weak. Additionally, submesoscale energetics in the Western Boundary Current transition zone are slightly greater than those in the STCC interior open ocean zone, which is attributed to the strengthened straining of the Western Boundary Current and mesoscale eddies. Full article

This study investigated the vertical structure of an anticyclonic eddy (AE) in the northern South China Sea (SCS) in August 2017 and its response to Typhoon Hato using underwater glider and satellite altimeter data. Additionally, comparative experiments with and without typhoon forcing were conducted using the Regional Ocean Modeling System (ROMS) for supplementary analysis. The observational results reveal that the maximum temperature and salinity differences between the center and edge of the AE did not occur at the sea surface but near the 100 m depth. The typhoon caused a significant temperature decrease above 200 m, with the maximum cooling (~2 °C) occurring near 50 m. Near this depth, salinity initially increased due to upwelling but later decreased due to surface mixing. The most pronounced cooling and salinity changes occurred one day after the typhoon passage, followed by a gradual deepening of the mixed layer over the next four days, with conditions below the mixed layer largely returning to pre-typhoon states. Numerical modeling quantitatively assessed the typhoon’s impacts. Upwelling rapidly intensified during the typhoon’s passage, the typhoon’s wind stress decreased kinetic energy at the AE site, and the input of positive vorticity reduced absolute vorticity, disrupting the surface AE structure. The flow field adjusted faster than temperature and salinity, with surface currents and the AE structure largely recovering within two days after the typhoon’s passage. These findings highlight the multifaceted impacts of typhoons on AEs and provide critical insights for predicting the evolution of mesoscale oceanic structures under extreme weather events. Full article

Mesoscale eddies have a significant influence on primary productivity and upper-ocean variability, particularly in stratified and monsoon-driven basins like the Bay of Bengal (BoB). This study analyzes mesoscale eddies in the BoB from January 2010 to March 2020 using post-processed and gridded daily sea surface height anomaly (SLA) data from the Copernicus Marine Environment Monitoring Service. We used a hybrid detection method combining the Okubo–Weiss parameter and SLA contour analysis to identify 1880 anticyclonic and 1972 cyclonic eddies. Cyclonic eddies were mainly found in the western BoB along the east Indian coast, while anticyclonic eddies were less frequent in this area. Analysis of eddy lifespans revealed that short-lived (1-week) eddies were nearly equally distributed between anticyclonic (48.81%) and cyclonic (51.19%) types. However, for longer-lived eddies, cyclonic eddies became more prevalent, comprising 83.33% of 30-week eddies. A notable, consistent eddy presence was observed east of Sri Lanka, influencing the East India Coastal Current. Most eddies (91%) propagated west/southwestward along the western slope of the Andaman Archipelago, likely influenced by ocean currents and coastal topography, with concentrations in the Andaman Sea and central BoB. These patterns suggest significant interactions between eddies, coastal upwelling zones, and boundary currents, impacting nutrient transport and marine ecosystem productivity. This study contributes valuable insights into the dynamics of ocean circulation and the impacts of eddies, which can inform fisheries management strategies, advance climate resilience measures, expand scientific knowledge, and guide policies related to conservation and sustainable resource utilization. Full article

The LICOM Forecast System (LFS), a global eddy-resolving ocean forecasting system, provides 1–15-day forecasts of ocean mesoscale eddies (OMEs). This study conducts a comparative analysis of the forecast results against observational data, thereby evaluating the performance of the LFS. Results show that LFS underestimates the number of eddies by ~10% and their amplitude by ~30%, while overestimating eddy radius by ~5% and velocity by ~25%. Forecasted eddies are matched on a one-to-one basis with observed eddies based on distance, ensuring that those forecasted eddies that can locate corresponding counterparts in the observational dataset yield accurate forecasts. The outcomes reveal that the LFS successfully forecasts 63% of the eddies in the NWP. The characteristics of these accurately forecasted eddies are delineated. The findings indicate that eddies with greater amplitudes are more likely to be accurately predicted. Additionally, we further scrutinized the correlation between eddy attributes and forecast performance, revealing that with an increase in amplitude or a decrease in velocity, the LFS produces forecasts with improved locational accuracy. The mean forecast error in eddy position is 79.94 km for a 1-day lead time, which decreases to 70.97 km for eddies with amplitudes exceeding 1 cm and velocities below 1 km/day. Full article

The direct fitting of sea level anomaly (SLA) using satellite along-track data provides a critical approach for monitoring mesoscale ocean dynamics. While bicubic quasi-uniform B-spline surface fitting has demonstrated feasibility in localized sea areas, its applicability to basin-scale regions remains underexplored. This study focuses on the northern Atlantic Ocean, employing B-spline surface fitting to derive SLA fields from satellite along-track data. The results show strong agreement with in situ measurements, yielding a mean absolute error (MAE) of 1.89 cm and a root mean square error (RMSE) of 3.02 cm. Comparative analysis against the Copernicus Marine Environment Monitoring Service (CMEMS) Level-4 gridded SSH data reveals nearly equivalent accuracy (MAE: 1.95 cm; RMSE: 3.06 cm). The relationship between the order of fitting and the spatial extent of the fitting domain is also examined. Furthermore, the influence of the coastline on the fitting results is investigated in detail. As the coastline area expanded, the MAE and RMSE for the entire region increased. But the maximum increase in MAE was only 1.20 cm, and the maximum increase in RMSE was only 2.49 cm. Notably, there was no upward trend in MAE and RMSE in the mesoscale vortex dense area, which highlights the advantage of B-spline’s local support. Geostrophic flow and vertical component of relative vorticity are computed from the satellite along-track SLA data, with results showing agreement with Level-4 gridded geostrophic flow and vertical component of relative vorticity data. Full article

Satellite sea surface salinity (SSS) products suffer from coarse spatiotemporal resolution, limiting their utility for mesoscale ocean monitoring. To address this, we proposed the Transformer-based satellite SSS super-resolution (SR) model (TSR) coupled with a progressive transfer learning (PTL) strategy. TSR improved the resolution of the salinity satellite SMOS from 1/4° and 10 days to 1/12° and daily. Leveraging Transformer, TSR captured long-range dependencies critical for reconstructing fine-scale structures. PTL effectively balanced structural detail acquisition and local accuracy correction by combining the gridded reanalysis products with scattered in situ observations as training labels. Validated against independent in situ measurements, TSR outperformed existing L3 salinity satellite products, as well as convolutional neural network and generative adversarial network-based SR models, particularly reducing the root mean square error (RMSE) by 33% and the mean bias (MB) by 81% compared to the SMOS input. More importantly, TSR demonstrated an enhanced capability in resolving mesoscale eddies, which were previously obscured by noise in salinity satellite products. Compared to training with a single label type or switching label types non-progressively, PTL achieved a 3%–66% lower RMSE and a 73–92% lower MB. TSR enables higher-resolution satellite monitoring of SSS, contributing to the study of ocean dynamics and climate change. Full article

As economically important sympatric species in the Northwest Pacific, the Japanese sardine (Sardinops melanostictus) and Chub mackerel (Scomber japonicus) exhibit significant biological interactions. Understanding the impact of interspecies competition on their habitat dynamics can provide crucial insights for the sustainable development and management of these interconnected species resources. This study utilizes fisheries data of S. melanostictus and S. japonicus from the Northwest Pacific, collected from June to November between 2017 and 2020. We integrated various environmental parameters, including temperature at different depths (0, 50, 100, 150, and 200 m), eddy kinetic energy (EKE), sea surface height (SSH), chlorophyll-a concentration (Chl-a), and the oceanic Niño index (ONI), to construct interspecific competition species distribution model (icSDM) for both species. We validated these models by overlaying the predicted habitats with fisheries data from 2021 and performing cross-validation to assess the models’ reliability. Furthermore, we conducted correlation analyses of the habitats of these two species to evaluate the impact of interspecies relationships on their habitat dynamics. The results indicate that, compared to single-species habitat models, the interspecific competition species distribution model (icSDM) for these two species exhibit a significantly higher explanatory power, with R² values increasing by up to 0.29; interspecific competition significantly influences the habitat dynamics of S. melanostictus and S. japonicus, strengthening the correlation between their habitat changes. This relationship exhibits a positive correlation at specific stages, with the highest correlations observed in June, July, and October, at 0.81, 0.80, and 0.88, respectively; interspecific competition also demonstrates stage-specific differences in its impact on the habitat dynamics of S. melanostictus and S. japonicus, with the most pronounced differences occurring in August and November. Compared to S. melanostictus, interspecific competition is more beneficial for the expansion of the optimal habitat (HIS ≥ 0.6) for S. japonicus and, to some extent, inhibits the habitat expansion of S. melanostictus. The variation in migratory routes and predatory interactions (with larger individuals of S. japonicus preying on smaller individuals of S. melanostictus) likely constitutes the primary factors contributing to these observed differences. Full article

Mesoscale coastal eddies are key components of ocean circulation, mediating the transport of heat, nutrients, and marine debris. The Surface Water and Ocean Topography (SWOT) mission provides high-resolution sea surface height data, offering a novel opportunity to improve the observation and characterization of these features, especially in coastal regions where conventional altimetry is limited. In this study, we investigate a mesoscale anticyclonic coastal eddy observed southwest of Mallorca Island, in the Balearic Sea, to assess the impact of SWOT-enhanced altimetry in resolving its structure and dynamics. Initial eddy identification is performed using satellite ocean color imagery, followed by a qualitative and quantitative comparison of multiple altimetric datasets, ranging from conventional nadir altimetry to wide-swath products derived from SWOT. We analyze multiple altimetric variables—Sea Level Anomaly, Absolute Dynamic Topography, Velocity Magnitude, Eddy Kinetic Energy, and Relative Vorticity—highlighting substantial differences in spatial detail and intensity. Our results show that SWOT-enhanced observations significantly improve the spatial characterization and dynamical depiction of the eddy. Furthermore, Lagrangian transport simulations reveal how altimetric resolution influences modeled transport pathways and retention patterns. These findings underline the critical role of SWOT in advancing the monitoring of coastal mesoscale processes and improving our ability to model oceanic transport mechanisms. Full article

The precise forecasting of mesoscale eddy trajectories holds significant importance for understanding their mechanisms in driving global oceanic mass and heat transport. However, mesoscale eddies are influenced by numerous stochastic and uncertain factors, leading to substantial fluctuations in their attribute variables. Additionally, the trajectories of eddies are related to historical trends and interact with surrounding eddies. These render the accurate forecasting of mesoscale eddy trajectories a formidable challenge. This study proposes a novel dynamic forecasting framework for eddies’ trajectories, termed EddyGnet, a dual graph neural network framework that synergistically models the complex multivariable association and the spatiotemporal eddy association. In this framework, the dynamic association among eddy attribute variables is first explored by a multivariable association graph (MAG) learning module. Subsequently, the spatial and temporal association among eddies are concurrently analyzed using a spatiotemporal eddy association graph (STEAG) learning module. Finally, a decayed volatility loss function is designed to properly handle the complex and variable data features and improve the forecasting performance. The experimental results on the eddy dataset verify the effectiveness of our proposed EddyGnet, demonstrating superior predictive accuracy and stability compared with existing classical methods. The findings advance the mechanistic understanding of eddy dynamics and provide a transferable paradigm for geoscientific spatiotemporal modeling. Full article

This study focused on the carbonate system dynamics and air–sea CO₂ fluxes in the open-ocean waters of the Madeira–Tore Seamount Complex during August 2024. Surface water properties revealed pronounced latitudinal gradients in sea surface temperature (21.9–23.1 °C), salinity (36.2–36.7), and dissolved oxygen (228–251 µmol Kg⁻¹), influenced by mesoscale eddies and topographically driven upwelling. Despite oligotrophic conditions, distinct phytoplankton assemblages were observed, with coccolithophores dominating southern seamounts and open-ocean stations, and green algae and diatoms indicating episodic nutrient input. Surface total alkalinity (TA: 2236–2467 µmol Kg⁻¹), dissolved inorganic carbon (DIC: 2006–2183 µmol Kg⁻¹), and pCO₂ (467–515 µatm) showed spatial variability aligned with water mass characteristics and biological activity. All stations exhibited positive air–sea CO₂ fluxes (2.8–11.5 mmol m⁻² d⁻¹), indicating the region is a CO₂ source during summer. Calcite and aragonite saturation states were highest in stratified, warmer waters. Principal Component Analysis highlighted the role of physical mixing, carbonate chemistry, and biological uptake in structuring regional variability. Our findings emphasize and contribute to the complex interplay of physical and biogeochemical drivers in modulating carbon cycling and ecosystem structure across Atlantic seamounts. Full article

Marine heatwaves (MHWs) and Marine cold spells (MCSs) are oceanic events characterized by prolonged periods of anomalously warm or cold sea surface temperatures, which pose significant ecological and socio-economic threats on a global scale. These extreme temperature events exhibit an asymmetric trend under ongoing climate change in recent decades: MHWs have increased markedly in both frequency and intensity, whereas MCSs have shown an overall decline. Among the potential drivers, mesoscale eddies play a critical role in modulating sea surface temperature anomalies (SSTAs). Anticyclonic eddies (AEs) promote downwelling, generating positive SSTAs that potentially favor MHWs, while cyclonic eddies (CEs) enhance upwelling and negative anomalies that are potentially related to MCSs. In this paper, we investigate the relationship between mesoscale eddies and MHWs/MCSs using global satellite-derived datasets from 2010 to 2019. By analyzing the spatial overlap and intensity correlation between eddies and MHWs/MCSs, it is found that 12.2% of MHWs are accompanied by AEs, and 13.4% of MCSs by CEs, with a high degree of spatial containment where approximately 90.2% of MHW events are found within the mean eddy contour of AEs, and about 93.1% of MCS events fall inside the mean eddy contour of CEs. Stronger eddies tend to be associated with more intense MHWs/MCSs. This study provides new insights into the role of mesoscale eddies in regulating extreme oceanic temperature events, offering valuable information for future predictions in the context of climate change. Full article