Chaojie Zhou

Oceanic submesoscale dynamics play a critical role in energy cascades and vertical tracer transport. The Surface Water and Ocean Topography (SWOT) mission, through its high-resolution wide-swath sea surface height (SSH) observations, provides an unprecedented capability for resolving these processes. While this enhanced spatial coverage represents a major advance over conventional nadir altimetry, it also introduces new challenges for constructing dynamically consistent gridded Level-4 products. To address these challenges, a range of data fusion and reconstruction approaches have been developed to incorporate SWOT observations into next-generation SSH mapping systems. This study presents a comparative evaluation of three SWOT-derived Level-4 products (MIOST, 4DvarQG, and 4DvarNET) over the North Atlantic (25–50° N, 80–10° W). The assessment combines Eulerian metrics of mapping accuracy, Lagrangian trajectory prediction skill based on surface drifter observations, and diagnostics of dynamical structures using Rossby number ( R _o ) and finite-size Lyapunov exponent (FSLE) fields, with SWOT Level-3 data as a reference. The results reveal a pronounced scale dependence in product performance. In mesoscale-dominated regimes such as the Gulf Stream, 4DvarQG achieves the highest velocity reconstruction accuracy and improves short-term (0–4 d) Lagrangian prediction skill, reflecting the benefits of quasi-geostrophic dynamical constraints. In contrast, 4DvarNET shows greater sensitivity to smaller-scale variability, characterized by sharper SSH gradients, elevated R _o , and more filamentary strain structures, indicating an enhanced representation of fine-scale features. However, the physical realism of these intensified small-scale signals requires further validation against higher-resolution or less-filtered observations. MIOST demonstrates stable and consistent performance across a wide range of spatial scales for global ocean mapping. These results highlight inherent trade-offs between dynamical consistency and small-scale variability representation among current SWOT-based Level-4 products. Future developments may therefore benefit from hybrid approaches that integrate data-driven flexibility with explicit physical constraints.

Oceanic submesoscale dynamics play a critical role in energy cascades and vertical tracer transport. The Surface Water and Ocean Topography (SWOT) mission, through its high-resolution wide-swath sea surface height (SSH) observations, provides an unprecedented capability for resolving these processes. While this enhanced spatial coverage represents a major advance over conventional nadir altimetry, it also introduces new challenges for constructing dynamically consistent gridded Level-4 products. To address these challenges, a range of data fusion and reconstruction approaches have been developed to incorporate SWOT observations into next-generation SSH mapping systems. This study presents a comparative evaluation of three SWOT-derived Level-4 products (MIOST, 4DvarQG, and 4DvarNet) over the North Atlantic (25° N–50° N, 80° W–10° W). The assessment combines Eulerian metrics of mapping accuracy, Lagrangian trajectory mprediction skill based on surface drifter observations, and diagnostics of dynamical structures using Rossby number (R_o) and finite-size Lyapunov exponent (FSLE) fields, with SWOT Level-3 data as a reference. The results reveal a pronounced scale dependence in product performance. In mesoscale-dominated regimes such as the Gulf Stream, 4DvarQG achieves the highest velocity reconstruction accuracy and improves short-term (0–4 days) Lagrangian prediction skill, reflecting the benefits of quasi-geostrophic dynamical constraints. In contrast, 4DvarNet shows greater sensitivity to smaller-scale variability, characterized by sharper SSH gradients, elevated R_o, and more filamentary strain structures, indicating an enhanced representation of fine-scale features. However, the physical realism of these intensified small-scale signals requires further validation against higher-resolution or less-filtered observations. MIOST demonstrates stable and consistent performance across a wide range of spatial scales for global ocean mapping. These results highlight inherent trade-offs between dynamical consistency and small-scale variability representation among current SWOT-based Level-4 products. Future developments may therefore benefit from hybrid approaches that integrate data-driven flexibility with explicit physical constraints.

Oceanic submesoscale dynamics play a critical role in energy cascades and vertical tracer transport. The Surface Water and Ocean Topography (SWOT) mission, through its high-resolution wide-swath sea surface height (SSH) observations, provides an unprecedented capability for resolving these processes. While this enhanced spatial coverage represents a major advance over conventional nadir altimetry, it also introduces new challenges for constructing dynamically consistent gridded Level-4 products. To address these challenges, a range of data fusion and reconstruction approaches have been developed to incorporate SWOT observations into next-generation SSH mapping systems. This study presents a comparative evaluation of three SWOT-derived Level-4 products (MIOST, 4DvarQG, and 4DvarNet) over the North Atlantic (25° N–50° N, 80° W–10° W). The assessment combines Eulerian metrics of mapping accuracy, Lagrangian trajectory mprediction skill based on surface drifter observations, and diagnostics of dynamical structures using Rossby number (R_o) and finite-size Lyapunov exponent (FSLE) fields, with SWOT Level-3 data as a reference. The results reveal a pronounced scale dependence in product performance. In mesoscale-dominated regimes such as the Gulf Stream, 4DvarQG achieves the highest velocity reconstruction accuracy and improves short-term (0–4 days) Lagrangian prediction skill, reflecting the benefits of quasi-geostrophic dynamical constraints. In contrast, 4DvarNet shows greater sensitivity to smaller-scale variability, characterized by sharper SSH gradients, elevated R_o, and more filamentary strain structures, indicating an enhanced representation of fine-scale features. However, the physical realism of these intensified small-scale signals requires further validation against higher-resolution or less-filtered observations. MIOST demonstrates stable and consistent performance across a wide range of spatial scales for global ocean mapping. These results highlight inherent trade-offs between dynamical consistency and small-scale variability representation among current SWOT-based Level-4 products. Future developments may therefore benefit from hybrid approaches that integrate data-driven flexibility with explicit physical constraints.

Oceanic submesoscale dynamics play a critical role in energy cascades and vertical tracer transport. The Surface Water and Ocean Topography (SWOT) mission, through its high-resolution wide-swath sea surface height (SSH) observations, provides an unprecedented capability for resolving these processes. While this enhanced spatial coverage represents a major advance over conventional nadir altimetry, it also introduces new challenges for constructing dynamically consistent gridded Level-4 products. To address these challenges, a range of data fusion and reconstruction approaches have been developed to incorporate SWOT observations into next-generation SSH mapping systems. This study presents a comparative evaluation of three SWOT-derived Level-4 products (MIOST, 4DvarQG, and 4DvarNet) over the North Atlantic (25° N–50° N, 80° W–10° W). The assessment combines Eulerian metrics of mapping accuracy, Lagrangian trajectory mprediction skill based on surface drifter observations, and diagnostics of dynamical structures using Rossby number (R_o) and finite-size Lyapunov exponent (FSLE) fields, with SWOT Level-3 data as a reference. The results reveal a pronounced scale dependence in product performance. In mesoscale-dominated regimes such as the Gulf Stream, 4DvarQG achieves the highest velocity reconstruction accuracy and improves short-term (0–4 days) Lagrangian prediction skill, reflecting the benefits of quasi-geostrophic dynamical constraints. In contrast, 4DvarNet shows greater sensitivity to smaller-scale variability, characterized by sharper SSH gradients, elevated R_o, and more filamentary strain structures, indicating an enhanced representation of fine-scale features. However, the physical realism of these intensified small-scale signals requires further validation against higher-resolution or less-filtered observations. MIOST demonstrates stable and consistent performance across a wide range of spatial scales for global ocean mapping. These results highlight inherent trade-offs between dynamical consistency and small-scale variability representation among current SWOT-based Level-4 products. Future developments may therefore benefit from hybrid approaches that integrate data-driven flexibility with explicit physical constraints.

Oceanic submesoscale dynamics play a critical role in energy cascades and vertical tracer transport. The Surface Water and Ocean Topography (SWOT) mission, through its high-resolution wide-swath sea surface height (SSH) observations, provides an unprecedented capability for resolving these processes. While this enhanced spatial coverage represents a major advance over conventional nadir altimetry, it also introduces new challenges for constructing dynamically consistent gridded Level-4 products. To address these challenges, a range of data fusion and reconstruction approaches have been developed to incorporate SWOT observations into next-generation SSH mapping systems. This study presents a comparative evaluation of three SWOT-derived Level-4 products (MIOST, 4DvarQG, and 4DvarNet) over the North Atlantic (25° N–50° N, 80° W–10° W). The assessment combines Eulerian metrics of mapping accuracy, Lagrangian trajectory mprediction skill based on surface drifter observations, and diagnostics of dynamical structures using Rossby number (R_o) and finite-size Lyapunov exponent (FSLE) fields, with SWOT Level-3 data as a reference. The results reveal a pronounced scale dependence in product performance. In mesoscale-dominated regimes such as the Gulf Stream, 4DvarQG achieves the highest velocity reconstruction accuracy and improves short-term (0–4 days) Lagrangian prediction skill, reflecting the benefits of quasi-geostrophic dynamical constraints. In contrast, 4DvarNet shows greater sensitivity to smaller-scale variability, characterized by sharper SSH gradients, elevated R_o, and more filamentary strain structures, indicating an enhanced representation of fine-scale features. However, the physical realism of these intensified small-scale signals requires further validation against higher-resolution or less-filtered observations. MIOST demonstrates stable and consistent performance across a wide range of spatial scales for global ocean mapping. These results highlight inherent trade-offs between dynamical consistency and small-scale variability representation among current SWOT-based Level-4 products. Future developments may therefore benefit from hybrid approaches that integrate data-driven flexibility with explicit physical constraints.

Oceanic submesoscale dynamics play a critical role in energy cascades and vertical tracer transport. The Surface Water and Ocean Topography (SWOT) mission, through its high-resolution wide-swath sea surface height (SSH) observations, provides an unprecedented capability for resolving these processes. While this enhanced spatial coverage represents a major advance over conventional nadir altimetry, it also introduces new challenges for constructing dynamically consistent gridded Level-4 products. To address these challenges, a range of data fusion and reconstruction approaches have been developed to incorporate SWOT observations into next-generation SSH mapping systems. This study presents a comparative evaluation of three SWOT-derived Level-4 products (MIOST, 4DvarQG, and 4DvarNet) over the North Atlantic (25° N–50° N, 80° W–10° W). The assessment combines Eulerian metrics of mapping accuracy, Lagrangian trajectory mprediction skill based on surface drifter observations, and diagnostics of dynamical structures using Rossby number (R_o) and finite-size Lyapunov exponent (FSLE) fields, with SWOT Level-3 data as a reference. The results reveal a pronounced scale dependence in product performance. In mesoscale-dominated regimes such as the Gulf Stream, 4DvarQG achieves the highest velocity reconstruction accuracy and improves short-term (0–4 days) Lagrangian prediction skill, reflecting the benefits of quasi-geostrophic dynamical constraints. In contrast, 4DvarNet shows greater sensitivity to smaller-scale variability, characterized by sharper SSH gradients, elevated R_o, and more filamentary strain structures, indicating an enhanced representation of fine-scale features. However, the physical realism of these intensified small-scale signals requires further validation against higher-resolution or less-filtered observations. MIOST demonstrates stable and consistent performance across a wide range of spatial scales for global ocean mapping. These results highlight inherent trade-offs between dynamical consistency and small-scale variability representation among current SWOT-based Level-4 products. Future developments may therefore benefit from hybrid approaches that integrate data-driven flexibility with explicit physical constraints.

Oceanic submesoscale dynamics play a critical role in energy cascades and vertical tracer transport. The Surface Water and Ocean Topography (SWOT) mission, through its high-resolution wide-swath sea surface height (SSH) observations, provides an unprecedented capability for resolving these processes. While this enhanced spatial coverage represents a major advance over conventional nadir altimetry, it also introduces new challenges for constructing dynamically consistent gridded Level-4 products. To address these challenges, a range of data fusion and reconstruction approaches have been developed to incorporate SWOT observations into next-generation SSH mapping systems. This study presents a comparative evaluation of three SWOT-derived Level-4 products (MIOST, 4DvarQG, and 4DvarNet) over the North Atlantic (25° N–50° N, 80° W–10° W). The assessment combines Eulerian metrics of mapping accuracy, Lagrangian trajectory mprediction skill based on surface drifter observations, and diagnostics of dynamical structures using Rossby number (R_o) and finite-size Lyapunov exponent (FSLE) fields, with SWOT Level-3 data as a reference. The results reveal a pronounced scale dependence in product performance. In mesoscale-dominated regimes such as the Gulf Stream, 4DvarQG achieves the highest velocity reconstruction accuracy and improves short-term (0–4 days) Lagrangian prediction skill, reflecting the benefits of quasi-geostrophic dynamical constraints. In contrast, 4DvarNet shows greater sensitivity to smaller-scale variability, characterized by sharper SSH gradients, elevated R_o, and more filamentary strain structures, indicating an enhanced representation of fine-scale features. However, the physical realism of these intensified small-scale signals requires further validation against higher-resolution or less-filtered observations. MIOST demonstrates stable and consistent performance across a wide range of spatial scales for global ocean mapping. These results highlight inherent trade-offs between dynamical consistency and small-scale variability representation among current SWOT-based Level-4 products. Future developments may therefore benefit from hybrid approaches that integrate data-driven flexibility with explicit physical constraints.

Using satellite-observed data and reanalysis data, we studied the spatiotemporal variation characteristics and dynamic mechanisms of thermal fronts in the Beibu Gulf (TFIBG). TFIBG occur in December, reach their strongest point in January in the following year, and then gradually weaken until they completely disappear in May. Their formation is related to the bathymetry of the Beibu Gulf. In winter, the seawater in shallow-water areas (deep-water areas) cools down more (less), and Ekman currents concurrently transport warm water from the central basin of the Beibu Gulf to the west coast, which results in the formation of a thermal front at the junction of cold and warm water. The interannual variation in TFIBG intensity is related to the northeast monsoon. The strengthened (weakened) Ekman current caused by the northeast monsoon transports more (less) warm water from the central basin of the Beibu Gulf to the west coast, forming a strong (weak) thermal front at the junction of cold and warm water on an interannual scale. The upward trend of TFIBG intensity may be related to the regional heterogeneity of climate warming. This research systematically studied TFIBG, which will help improve people’s understanding of the thermal front in the South China Sea (SCS).

High-quality merged altimetry sea level products have been instrumental in analyzing oceanic dynamics, spanning global and regional sea level trends, and capturing interannual signals, but effectively characterizing mesoscale features remains a persistent issue. The essence of addressing this challenge lies in the selection of highly correlated data sources for fusion, within the confines of limited discrete observations from sea surface altimeters. To tackle this challenge, we propose a refined method focused on reducing the suboptimal interpolation window size and optimizing the mapping process, particularly emphasizing the enhancement of Kuroshio Extension (KE) characterization. By scrutinizing the spatial and temporal evolution of sea surface temperature (SST) fields, we have devised a modified strategy for selecting altimetry along-track data. This strategic approach facilitates the acquisition of more precise observations on a finer time scale, thereby circumventing the inclusion of altimetry observations with low correlation. To validate the efficacy of this approach, we performed a case study of sea surface height (SSH) data fusion in the KE region. As a result, the portrayal of KE intricacies, encompassing its axis and meandering, has markedly improved in the refined SSH gridded maps. A comparative analysis against drifter observations underscores the efficacy of the refined method. Velocity biases have been substantially reduced from −0.21 to 0.05 m s⁻¹, while the correlation coefficient has surged from 0.64 to 0.90. Concurrently, the root-mean-square error has plummeted from 0.42 to 0.21 m s⁻¹. These improvements signify significant strides toward more accurate and reliable characterizations of oceanic mesoscale features, particularly evident in the nuanced depiction of the KE. Significance Statement: Accurately characterizing the mesoscale dynamical features of gridded sea surface height (SSH) products remains a significant challenge in oceanographic research. Previous studies have often employed a fixed configuration of critical mapping parameters, limiting the reduction of reconstruction errors. In this study, we address this challenge by proposing a refined method aimed at enhancing the characterization of mesoscale features. Our approach involves modifying the expression of the space–time correlation function and adjusting the size of the suboptimal interpolation window. We achieve this by carefully analyzing the spatial and temporal evolution of sea surface temperature (SST) fields. Through this refined methodology, we aim to improve the portrayal of details within the Kuroshio Extension (KE) region. A comparative analysis against drifter trajectories highlights the substantial benefits of our refined approach. The refined SSH map more accurately captures the interaction between mesoscale eddies and the KE, leading to a more comprehensive depiction of oceanic dynamics in this critical region.

Oceanic mesoscale eddies are a kind of typical geostrophic dynamic process which can cause vertical movement in water bodies, thereby changing the temperature, salinity, density, and chlorophyll concentration of the surface water in the eddy. Based on multisource remote sensing data and Argo profiles, this study analyzes and compares the mesoscale eddy properties in four major western boundary current regions (WBCs), i.e., the Kuroshio Extension (KE), the Gulf Stream (GS), the Agulhas Current (AC), and the Brazil Current (BC). The 30-year sea surface height anomaly (SSHA) data are used to identify mesoscale eddies in the four WBCs. Among the four WBCs, the GS eddies have the largest amplitude and the BC eddies have the smallest amplitude. Combining the altimeter-detected eddy results with the simultaneous observations of sea surface temperature, sea surface salinity, sea surface density, and chlorophyll concentration, the local impacts of eddy activities in each WBCs are analyzed. The eddy surface temperature and salinity signals are positively correlated with the eddy SSHA signals, while the eddy surface density and chlorophyll concentrations are negatively correlated with eddy SSHA signals. The correlation analysis of eddy surface signals in the WBCs reveals that eddies have regional differences in the surface signal changes of eddy activities. Based on the subsurface temperature and salinity information provided by Argo profiles, the analysis of the vertical thermohaline characteristics of mesoscale eddies in the four WBCs is carried out. Eddies in the four WBCs have deep influence on the vertical thermohaline characteristics of water masses, which is not only related to the strong eddy activities but also to the thick thermocline and halocline of water masses in the WBCs.