This study validated wind speed (WS) and significant wave height (SWH) retrievals from the Sentinel-3A/3B and Jason-3 altimeters for the period of data beginning 31 October 2019 (to 18 September 2019 for Jason-3) using moored buoy data and satellite Meteorological Operational Satellite Program (MetOp-A/B) Advanced Scatterometer (ASCAT) data. The spatial and temporal scales of the collocated data were 25 km and 30 min, respectively. The statistical metrics of root mean square error (RMSE), bias, correlation coefficient (R), and scatter index (SI) were used to validate the WS and SWH accuracy. Validation of WS against moored buoy data indicated errors of 1.19 m/s, 1.13 m/s and 1.29 m/s for Sentinel-3A, Sentinel-3B and Jason-3, respectively. The accuracy of Sentinel-3A/3B WS is better than that of Jason-3. All three altimeters underestimated WS slightly in comparison with the buoy data. Errors in WS at different speeds or SWHs increased slightly as WS or SWH increased. Over time, the accuracy of the Jason-3 altimeter-derived WS improved, whereas that of Sentinel-3A showed no temporal dependence. The WSs of the three altimeters were compared with ASCAT wind data for validation purposes over the global ocean without in situ measurements. On average, the WSs of the three altimeters were lower in comparison with the ASCAT data. The accuracy of the three altimeters was found to be consistent and stable at low/medium speeds but it decreased when the WS exceeded 15 m/s. Validations of SWH against buoy wave data indicated that the accuracy of Jason-3 SWH was better than that of Sentinel-3A/3B. However, the accuracy of all three altimeters decreased when the SWH exceeded 4 m. The accuracy of Sentinel-3A and Jason-3 SWH was temporally stable, whereas that of Sentinel-3B SWH improved over time. Analyses of SWH accuracy as a function of wave period showed that the Jason-3 altimeter was better than the Sentinel-3A/3B altimeters for long-period ocean waves. Generally, the accuracy of WS and SWH data derived by the Sentinel-3A/3B and Jason-3 altimeters satisfies their mission requirements. Overall, the accuracy of WS (SWH) derived by Sentinel-3A/3B (Jason-3) is better than that retrieved by Jason-3 (Sentinel-3A/3B).

This study investigated the statistics of eddy splitting and merging in the global oceans based on 23 years of altimetry data. Multicore structures were identified using an improved geometric closed-contour algorithm of sea surface height. Splitting and merging events were discerned from continuous time series maps of sea level anomalies. Multicore structures represent an intermediate stage in the process of eddy evolution, similar to the generation of multiple nuclei in a cell as a preparatory phase for cell division. Generally, splitting or merging events can substantially change (by a factor of 2 or more) the eddy scale, amplitude, and eddy kinetic energy. Specifically, merging (splitting) generally causes an increase (decrease) of eddy properties. Multicore eddies were found to tend to split into two eddies with different intensities. Similarly, eddy merging is not an interaction of two equal-intensity eddies, and it tends to manifest as a strong eddy merging with a weaker one. A hybrid tracking strategy based on the eddy overlap ratio, considering both multicore and single-core eddies, was used to confirm splitting and merging events globally. The census revealed that eddy splitting and merging do not always occur most frequently in eddy-rich regions; e.g., their frequencies of occurrence in the Antarctic Circumpolar Current and western boundary currents were found to be greater than in midlatitude regions (20–35^∘) to the north and south. Eddy splitting and merging are caused primarily by an unstable configuration of multicore structures due to obvious current– or eddy–topography interaction, strong current variation, and eddy–mean flow interaction.

This paper presents an innovative approach to enhance the assimilation of high-resolution simulated observations, specifically targeting Surface Water Ocean Topography (SWOT) Ka-band Radar Interferometer Sea Surface Height (SSH) products, within the Regional Ocean Modeling System (ROMS). Responding to the demand for improved assimilation techniques, we developed a multi-scale Four-Dimensional Variational Data Assimilation (4DVAR) system, building upon validated fine-scale correction capabilities from prior studies. The multi-scale strategy was extended to the ROMS-4DVAR system, providing a comprehensive solution for assimilating high-resolution observations. Leveraging the Observing System Simulation Experiment (OSSE) framework, we conducted a twin experiment comprising a nature run and a free run case. Subsequently, synthetic SWOT SSH measurements were decomposed, considering the model configuration resolution. These components, derived from dense SSH observations, were integrated into a two-step 4DVAR assimilation scheme. The first cycle targets large-scale features for model field correction, and the updated analysis serves as the background for the second assimilation step, addressing fine-scale observation components. Comparisons with the primitive ROMS-4DVAR using a single-scale scheme highlight the superiority of the multi-scale strategy in reducing gaps between the model and the SSH observations. The Root Mean Squared Error (RMSE) is halved, and the Mean Absolute Percentage Error (MAPE) decreases from 2.237% to 0.93%. The two-step assimilation procedure ensures comprehensive multi-scale updates in the SSH field simulation, enhancing fine-scale features in the analysis fields. The quantification of three-dimensional-model dynamic fields further validates the efficiency and superiority of the multi-scale 4DVAR approach, offering a robust methodology for assimilating high-resolution observations within the ROMS.

Doppler mis-registrations in azimuth can lead to ocean waves shorter than a specific wavelength being undetectable by SAR. In order to evaluate the actual ocean wave observation ability, the accuracy of Sentinel-1 SAR ocean wave spectra from January 2016 to December 2021 is evaluated by comparisons to NDBC buoys, ERA5 wave height, and CMEMS buoys. The results compared with NDBC show that the spectral shape of Sentinel-1 SAR ocean wave spectra is accurate, while the spectral values need to be improved. The wave spectra of Sentinel-1 have the best observations in season autumn. The comparison results of total wave height show the RMSE and bias are 0.91 m and −0.52 m for the comparisons to NDBC buoy wave spectra data, 0.93 m and −0.68 m for the comparison to ERA5 wave height data, and 0.9 m and −0.35 m for the comparisons to CMEMS buoy data. The comparison results of wave height in different wind speeds and areas shows that the accuracy of Sentinel-1 wave mode data is relatively good in the open ocean located in middle and low latitude area under the medium wind speed, while those are relatively poor in high latitude areas or the areas with excessively high or low wind speed.

Based on satellite altimetry data spanning over 26 years in combination with Argo profile data or three-dimensional (3D) reprocessed thermohaline fields, the eddy synthesis method was used to construct vertical temperature and salinity structures of eddies in the Bay of Bengal, and the seasonal thermohaline properties of eddies and the heat and salt transport by eddies were analyzed. Analysis revealed that mesoscale eddy activities and the vertical thermohaline structures in the Bay of Bengal have evident seasonal variation. Temperature anomalies caused by eddies are usually between ±1 and ±3 ^∘C (positive for anticyclonic eddies (AEs) and negative for cyclonic eddies (CEs)), and the magnitude varies seasonally. Salinity anomalies caused by eddies are small and disturbance signals in the southern bay due to the small vertical gradient of salinity there; salinity anomalies in the northern bay are generally between ±0.2 and ±0.3 psu, negative for AEs and positive for CEs. Owing to seasonal changes in both the eddy activity and the vertical thermohaline structure in the Bay of Bengal, the eddy-induced heat and salt transport in different seasons also changes substantially. Generally, high heat and salt transport is concentrated in eddy-rich regions, e.g., the western, northwestern, and eastern parts of the bay, the seas to the east of Sri Lanka, and the region to the southeast outside of the bay. The southern part of the bay shows weak salt transport owing to the inconsistent salinity signal within eddies. The result of the divergence of eddy heat transport illustrates that the 10–20 W m⁻² value of the eddy-induced heat flux is comparable in magnitude with the annual mean air–sea net heat flux in the Bay of Bengal. Compared with the large-scale net heat flux and freshwater flux at the surface, the eddy-induced heat/freshwater transport can contribute substantially to regional and basin-scale heat/freshwater variability. This work provides data that could support further research on the heat and salt balance of the entire Bay of Bengal.

Vigorous mesoscale eddies are broadly distributed in the Kuroshio Extension and can generally be identified from sea surface height (SSH) and sea surface temperature (SST) fields. Nevertheless, the changes in SSH and SST caused by mesoscale eddies and their seasonal correlation in the Kuroshio Extension are not clear, as well as the difference between identified eddy results from the two data. Combining in situ Argo float profiles data, the correlation between SSH anomaly (SSHA) and SST anomaly (SSTA) signals in mesoscale eddies are analyzed. The result shows that SSTA–SSHA signals inside eddies are generally more correlated in winter than in summer. Argo subsurface temperature anomalies θ′ and SSHA signals inside eddies show a high correlation, with a regression coefficient θ′/SSHA of about 7 °C·m⁻¹, while correlations of Argo θ′–SSTA inside eddies are low. Generally, the lifetime and propagation distance of SSTA-based eddies are shorter and smaller than those of SSHA-based eddies, which may be related to the rapid changes in SSTA field and the interference of small-scale oceanic signal in the SST field. Comparing with SSHA-based eddies, which exist primarily around the region of the Kuroshio mainstream (33°–36°N), SSTA-based eddies are concentrated in the Oyashio Extension (39°–42°N), where SST gradient is large, and changes in SST fields caused by mesoscale eddies are more obvious and more likely to be captured by satellites there. In addition, the geographical distributions of SSHA- and SSTA-based eddy amplitudes are consistent with the absolute dynamic topography and SST gradient.