Eddy Radius Research Articles

An integrative machine learning approach to understanding South Pacific Ocean albacore tuna habitat features

Abstract This study employs a random forest model combined with interpretable machine learning techniques to analyze the habitat preferences of South Pacific albacore tuna, incorporating a broad range of marine environmental variables. Among these, several factors derived from mesoscale eddy structures, including eddy polarity, eddy radius, and eddy kinetic energy, are integrated to further enhance the characterization of mesoscale eddy features. Interpretable methods were applied to provide intuitive visualizations of albacore tuna habitat preferences, with a focus on the most influential factors, including seawater temperature, dissolved oxygen concentration, and normalized mesoscale eddy radius. Seawater temperature and oxygen concentration are directly linked to the physiological needs of albacore tuna, while mesoscale eddy characteristics influence foraging and behavior by altering water column properties. This study provides a comprehensive perspective on the characteristics of albacore tuna habitat and the mechanisms driving its oceanographic variables, providing valuable insights for developing location-based, practical science-based management strategies for fishery resources.

Detecting Ocean Eddies with a Lightweight and Efficient Convolutional Network

As a ubiquitous mesoscale phenomenon, ocean eddies significantly impact ocean energy and mass exchange. Detecting these eddies accurately and efficiently has become a research focus in ocean remote sensing. Many traditional detection methods, rooted in physical principles, often encounter challenges in practical applications due to their complex parameter settings, while effective, deep learning models can be limited by the high computational demands of their extensive parameters. Therefore, this paper proposes a new approach to eddy detection based on the altimeter data, the Ghost Attention Deeplab Network (GAD-Net), which is a lightweight and efficient semantic segmentation model designed to address these issues. The encoder of GAD-Net consists of a lightweight ECA+GhostNet and an Atrous Spatial Pyramid Pooling (ASPP) module. And the decoder integrates an Efficient Attention Network (EAN) module and an Efficient Ghost Feature Integration (EGFI) module. Experimental results show that GAD-Net outperforms other models in evaluation indices, with a lighter model size and lower computational complexity. It also outperforms other segmentation models in actual detection results in different sea areas. Furthermore, GAD-Net achieves detection results comparable to the Py-Eddy-Tracker (PET) method with a smaller eddy radius and a faster detection speed. The model and the constructed eddy dataset are publicly available.

A submesoscale eddy identification dataset in the northwest Pacific Ocean derived from GOCI I chlorophyll a data based on deep learning

Abstract. This paper presents a dataset on the identification of submesoscale eddies, derived from high-resolution chlorophyll a data captured by GOCI I in the northwest Pacific Ocean. Our methodology involves a combination of digital image processing, filtering, and object detection techniques, along with a specific chlorophyll a image enhancement procedure to extract essential information about submesoscale eddies. This information includes their time, polarity, geographical coordinates of the eddy center, eddy radius, coordinates of the upper left and lower right corners of the prediction box, area of the eddy's inner ellipse, and confidence score. The dataset spans eight time intervals, ranging from 00:00 to 08:00 (UTC) daily, covering the period from 1 April 2011 to 31 March 2021. A total of 19 136 anticyclonic eddies and 93 897 cyclonic eddies were identified, with a minimum confidence threshold of 0.2. The mean radius of anticyclonic eddies is 24.44 km (range 2.5 to 44.25 km), while that of cyclonic eddies is 12.34 km (range 1.75 to 44 km). This unprecedented hourly resolution dataset on submesoscale eddies offers valuable insights into their distribution, morphology, and energy dissipation. It significantly contributes to our understanding of marine environments, ecosystems, and the improvement of climate model predictions. The dataset is available at https://doi.org/10.5281/zenodo.13989785 (Wang and Yang, 2023).

An automatic eddy detection algorithm based on quadrant angle of velocity vector and its application

ABSTRACT Eddies assume a pivotal role in both the oceanic heat cycle and marine dynamic processes. The development of real-time satellite observations, coupled with advancements in computer intelligence, has propelled automatic eddy detection algorithms to the forefront of ocean remote sensing research. Nevertheless, target omissions and accuracy degradations are inevitable for multiple detection algorithms due to strong morphological variations in ocean eddies. This paper proposes an automatic detection algorithm based on the quadrant angle of the velocity vector in the flow field. Firstly, a rectangular search box is established, and the corresponding quadrant angles at the four vertices are calculated. Secondly, the centres and types of eddies are determined according to the cumulative sum and variety rules of quadrant angles. Then the outermost boundary is identified by regularity of quadrant angles in eight directions expanding outward from the centre of the eddy using the stream function equation. The new algorithm is assessed and verified using geostrophic flow data derived from the CMEMS standard gridded sea level anomaly product. Furthermore, its detection capabilities are demonstrated through a comparative analysis with several other algorithms. All methods exhibit consistent efficacy in detecting the majority of eddies with similar spatial distributions. In cases where the new algorithm identifies a specific eddy not detected by the FF15 and ND10 algorithms, sea surface temperature data is employed for verification. The sea surface temperature distribution map, along with the obtained results, illustrates the superiority of the new algorithm and its adaptability to products with varying resolutions. Additionally, the results undergo verification through a manual detection method, revealing that the new algorithm achieves SDR of 91.73% and an EDR of 3.54%. This percentage significantly surpasses the lower acceptable limit of 80% for the SDR parameter. The new algorithm is applied to study eddies with lifetimes exceeding ten days, spanning from March 2022 to February 2023, within the East China Sea and the South China Sea. The radius of SCS eddies is generally larger than that of ECS eddies, both cyclonic and anticyclonic. This further confirms the significant influence of regional ocean dynamics on the structure of eddies in different regions. Finally, the algorithm is applied to SWOT data to test the adaptability of the algorithm to non-regular grid data. The results show that the algorithm can effectively analyse SWOT data within 60° latitudes.

Improved identification and tracking of three-dimensional eddies in the Southern Ocean utilizing 3D-U-Res-Net

Oceanic mesoscale eddies are prevalent throughout the global ocean, playing a critical role in material and energy transport while significantly influencing climate change. Accurate characterization of their three-dimensional structures and movement is essential for a quantitative analysis of their transport processes. Traditional eddy detection algorithms have lower successful detection rate and with more limitations, so they fall short in the complex and dynamic ocean environment. The rising trend of applying artificial intelligence (AI) algorithms, due to their efficiency, precision, and automation, addresses this challenge. This study employs the 3D-U-Res-Net algorithm to identify the three-dimensional structures of mesoscale eddies in the Southern Ocean using GLORYS12V1 data from 2011 to 2020. A vector geometry-based eddy detection algorithm (VG) initially identified 1587292 eddy snapshots in the Southern Ocean (2011–2019), which were used for training the 3D-U-Res-Net algorithm. Data from 2020 served as the ground truth and validation set. The successful detection rate of 3D-U-Res-Net algorithm is 100%, which means that it identified all 135734 eddy snapshots from the VG dataset in 2020. For eddy tracking, the VG algorithm counted 18168 eddy tracks, whereas the 3D-U-Res-Net counted 18559, reflecting a 2.15% bias. To reduce uncertainty, eddies with lifespans shorter than two weeks were excluded. The average lifespans and traveling distances for eddies detected by the 3D-U-Res-Net (VG) algorithm were 29.35 (29.61) days and 77.78 (37.60) km, respectively, with the 3D-U-Res-Net identifying eddies with longer traveling distances. The mean radius of eddies detected by the VG algorithm was 43.16 km, while the 3D-U-Res-Net detected eddies with a mean radius of 43.74 km, a 0.58 km increase. We categorized eddies into four three-dimensional structures: bowl-shaped, cone-shaped, lens-shaped, and cylindrical. The VG algorithm identified these structures in proportions of 32%, 31%, 25%, and 12%, respectively, whereas the 3D-U-Res-Net algorithm found 19.48%, 19.58%, 0.04%, and 60.9%, respectively. The 3D-U-Res-Net identified more cylindrical eddies and was approximately ten times faster than the VG algorithm. Overall, this algorithm has good performance and higher efficiency. It is an attempt of using AI for oceanic research, and more works can be carried out in the future.

Spatiotemporal characteristics of mesoscale eddies in the South China Sea and the influence mechanism of Eddy Kinetic Energy

This paper uses 28 years of satellite altimeter fusion data from 1993 to 2020 to identify and track the mesoscale eddies in the South China Sea based on the Sea Level Anomaly (SLA) closed contour method, with the goal of improving our overall understanding of mesoscale eddy activities in the South China Sea and further investigating the ocean dynamic processes in the region, so as to provide fundamental data for climate change studies. The study examined the spatiotemporal distribution, generation and demise, and movement trajectories of the eddies. Furthermore, key parameters including velocity, vortex radius, amplitude and Eddy Kinetic Energy (EKE) were analyzed, with a particular emphasis on the seasonal changes and mechanisms that influence EKE in two areas of the South China Sea with high energy values. The South China Sea has more cyclonic eddies than anticyclonic eddies, according to the study, and its eastern region is primarily home to high-frequency generating areas. However, the majority of the vortices will eventually dissipate in the western and central areas of the South China Sea. Furthermore, vortices usually flow farther to the west. With decreasing latitude, the eddy radius and EKE distribution gradually increase, whereas the amplitude is contrary. EKE is caused by the interaction of factors including wind field driving, seawater movement, and circulation. Seasonal changes in the EKE occur near the Luzon Strait, and the sea area east of the south in Vietnam exhibits clear characteristics.

Generation of inflow turbulence using an improved synthetic eddy method

The generation of turbulent inflow conditions is a key issue in large eddy simulation (LES) or direct numerical simulation (DNS). In this paper, an improved synthetic eddy method (SEM) is proposed to generate inflow turbulence for LES and DNS. The improvements about SEM focus on the eddy radius and eddy distributions. First, the eddy radius is improved to reduce the nonphysical vortex structure on the wall caused by overestimation of the radius. Second, a sampling method using Gaussian distribution is proposed to improve the distribution of eddies, which accurately captures the randomness of turbulent structure size and is close to the actual flow field. The improved method is applied to the direct numerical simulation of the supersonic turbulent boundary layer at Mach 2.7 and the 24° compression ramp. Results indicate that the predictions yielded by the improved method are in good agreement with both DNS and experimental data. Compared to the original method, the improved method exhibits a more rapid recovery of the friction coefficient and effectively shortens the development distances. The improved SEM has enhanced the efficiency and accuracy of generating inlet turbulence, which can provide inlet turbulence boundary conditions for LES and DNS.

Evaporation Duct Anomalies Caused by Mesoscale Eddies in the Kuroshio Extension

AbstractEvaporation duct anomalies are always present above various oceanic processes, and their response to ubiquitous mesoscale eddies in the Kuroshio Extension region is quantitatively analyzed for the first time in this study using a synthetic analysis method based on reanalysis data sets and eddy trajectory data sets. The results indicated that the spatial distribution of evaporation duct anomalies is characterized by a monopole pattern, mainly modulated by the amplitude of anticyclonic eddies (AEs) and by the radius of cyclonic eddies (CEs). For AEs, the coupling strength is 0.7 m (2.9 M) per meter increase in amplitude, while for CEs, the coupling strength is 0.2 m (0.6 M) per 100 km increase in radius for the average evaporation duct height anomalies (evaporation duct strength anomalies) within the radius range. The modulation of evaporation duct anomalies by eddies is further examined.

Mesoscale eddy variability over the Bay of Bengal in response to the contrasting phases of extreme Indian Ocean Dipole events

The present study is aimed to investigate the mesoscale eddy variability in response to the two contrasting phases of extreme Indian Ocean Dipole (IOD) events, the 2016 (negative mode) and 2019 (positive mode). A quantification of the eddy characteristics was done by estimating the number of eddies, eddy radius, eddy amplitude, and eddy rotation speed for each of the contrasting events. It is found from the analysis, that the phase of IOD has a significant impact on the spatiotemporal characteristics of eddies over the bay. The number of eddies increased and a gradual shift from anti-cyclonic to cyclonic eddies was observed during the positive IOD year. Eddies formed during 2016 had an average amplitude of 0.085 m, rotation speed was around 0.345 cm/s and eddy radius, on average was found to be 81.25 km. The presence of a unique eddy feature on the east coast of Sri Lanka was observed which remained as a cyclonic eddy during the negative IOD and as an anti-cyclonic eddy during the positive IOD. The sea surface height anomaly showed a dip of −0.1 m at the core of the cyclonic eddy and a +0.4 m bulge was observed at the core of the anti-cyclonic eddy. A high negative SST anomaly of −0.5 °C was observed at the core of the cyclonic eddy. A drastic increase in the mixed layer depth was seen with the presence of the anti-cyclonic eddy. Analysis of the temperature and salinity vertical profiles showed that the anti-cyclonic eddy had a greater influence on the vertical profile than the cyclonic eddy. Both the eddies contributed significantly to upper ocean primary productivity by different mechanisms. Eddy-induced upwelling was predominant in the cyclonic eddy whereas eddy stirring was predominant in the anti-cyclonic eddy.

Eddy Detection Inverted from Argo Profiles to Surface Altimetry

Abstract Argo floats are widely used to characterize vertical structures of ocean eddies, yet their capability to invert sea surface features of eddies, especially those overlooked by available altimeters, has not been explored. In this paper, we propose an “interior-to-surface” inversion algorithm to effectively expand the capacity of eddy detection by estimating altimeter-missed eddies’ surface attributes from their Argo-derived potential density anomaly profiles, given that the interior property and surface signature of eddies are highly correlated. An altimeter-calibrated machine learning ensemble is employed for the inversion training based on the joint altimeter–Argo eddy data and shows promising performance with mean absolute errors of 5.4 km, 0.5 cm, and 14.3 cm2 s−2 for eddy radius, amplitude, and kinetic energy, respectively. Then, the trained ensemble model is applied to independently invert the properties of eddies captured by an Argo-alone detection scheme, which yields high spatiotemporal consistency with their altimeter-captured counterparts. In particular, a portion of Argo-alone eddies is ∼25% smaller than altimeter-derived ones, indicating Argo’s unique capability of profiling weaker submesoscale eddies. Sea surface temperature and chlorophyll data are further applied to validate the reliability of eddies identified and characterized by the Argo-only algorithm. This new methodology effectively complements that of altimetry in eddy detection and can be expanded to estimate other physical/biochemical eddy variables from a variety of in situ observations. Significance Statement Despite thousands of eddies being routinely identified on a daily basis, it has been recognized that a substantial portion of eddies may still be missed due to inadequate sampling of altimeter constellations. Taking advantage of eddy’s correlation between surface and interior, a considerable number of eddies are discovered for the first time through an Argo-based eddy identification scheme. Here, we propose a new methodology to independently infer these recaptured eddies’ surface properties from their vertical signals through an “interior-to-surface” inversion process. The inferred eddy properties are verified by the spatiotemporal consistency with those derived from altimetry. Since Argo is capable of profiling smaller and weaker eddies, the proposed methodology significantly complements and expands that of altimetry in eddy observation.

The Influence of Typhoon-Induced Wave on the Mesoscale Eddy

The strong wind-induced current and sea level have influences on the wave distribution in a tropical cyclone (TC). In particular, the wave–current interaction is significant in the period in which the TC passed the mesoscale eddy. In this study, the wave fields of Typhoon Chan-hom (2015) are hindcastly simulated using a coupled oceanic model that utilizes a nested triangle grid, i.e., the finite-volume community ocean model-simulating waves nearshore (FVCOM-SWAVE) model. The forcing wind field is composited from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data and the simulation using a parametric Holland model, denoted as H-E. The open boundary fields include tide data from TPOX.5 and the hybrid coordinate ocean model (HYCOM) global datasets, including sea surface temperature (SST), sea surface salinity, sea surface current, and sea level data. The simulated oceanic parameters (e.g., the significant wave height, SWH) are validated against the measurements from the Jason-2 altimeter, yielding a root mean square error (RMSE) of 0.58 m for the SWH, a correlation (COR) coefficient of 0.94, and a scatter index (SI) of 0.23. Similarly, the simulated SSTs are compared with the remote sensing products of the remote sensing system (REMSS) and the measurements from Argos, yielding an RMSE of <0.8 °C, a COR of >0.95, and an SI of <0.04. The significant zonal asymmetry of the wave distribution along the typhoon track is observed. The Stokes drift is calculated from the FVCOM-SWAVE simulation results, and then the contribution of the Stokes transport is estimated using the Ekman–Stokes numbers. It is found that the ratio of the Stokes transport to the total net transport can reach >80% near the typhoon center, and the ratio is reduced to approximately <20% away from the typhoon center, indicating that Stokes transport is an essential aspect in the water mixing during a TC. The mesoscale eddies are detected by the sea level anomalies (SLA) fusion data from AVISO. It is found that the significant wave heights, Stokes drift, and Stokes transport inside the eddy area were higher than those outside the eddy area. These parameters inside the cold mesoscale eddies were higher than t inside the warm mesoscale eddies. Otherwise, the SST mainly increased within the cold mesoscale eddies area, while decreased within the warm mesoscale eddies area. The influence of mesoscale eddies on the SST was in proportion to the eddy radius and eddy EKE.

Spatiotemporal Variation of Anticyclonic Eddies in the South China Sea during 1993–2019

Based on the absolute dynamic topography data from the Copernicus Marine Environment Monitoring Service, this paper applies the Topographic Position Index to develop a new approach for mapping the anticyclonic eddies in the South China Sea (SCS). The results show that anticyclonic eddies are active in the deep basin of SCS, and the five selected parameters (number or frequency, lifetime, kinetic energy, amplitude, and area or radius) of anticyclonic eddies have a similar temporal variation and a similar spatial distribution pattern. (1) As for monthly variations, anticyclonic eddies are active in late spring and most active in summer. (2) The El Niño–Southern Oscillation had a stronger impact on the inter-annual variations of anticyclonic eddies in the SCS before 2013, resulting in a significant transition of inter-annual variations of these five parameters in around 2004. After 2013, most of these five parameters had a minimum in 2015 and a maximum in 2017. (3) Analyses show that the eddy activities in the SCS are significantly influenced by the monsoon wind and the western boundary current like Kuroshio. Therefore, the areas southwest of Taiwan Island and east of Vietnam are the two areas where the anticyclonic eddies are most active, with much larger eddy kinetic energy and much higher eddy amplitude.

Wave and Meso-Scale Eddy Climate in the Arctic Ocean

Under global climate change, the characteristics of oceanic dynamics are gradually beginning to change due to melting sea ice. This study focused on inter-annual variation in waves and mesoscale eddies (radius > 40 km) in the Arctic Ocean from 1993 to 2021. The waves were simulated by a numerical wave model, WAVEWATCH-III (WW3), which included a parameterization of ice–wave interaction. The long-term wind data were from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA-5), and current and sea level data from the HYbrid Coordinate Ocean Model (HYCOM)were used as the forcing fields. The simulated significant wave heights (SWHs) were validated against the 2012 measurements from the Jason-2 altimeter, yielding a 0.55 m root mean square error (RMSE) with a 0.95 correlation (COR). The seasonal variation in WW3-simulated SWH from 2021 to 2022 showed that the SWH was the lowest in summer (July and August 2021) and highest in winter (November 2021 to April 2022). This result indicates that parts of the Arctic could become navigable in summer. The mesoscale eddies were identified using a daily-averaged sea level anomalies (SLA) product with a spatial resolution of a 0.25° grid for 1993−2021. We found that the activity intensity (EKE) and radius of mesoscale eddies in the spatial distribution behaved in opposing ways. The analysis of seasonal variation showed that the increase in eddy activity could lead to wave growth. The amplitude of SWH peaks was reduced when the Arctic Oscillation Index (AOI) was <−1.0 and increased when the AOI was >0.5, especially in the case of swells. The amplitude of SWH oscillation was low, and the EKE and radius of eddies were relatively small. Although the radius and EKE of eddies were almost similar to the AOI, the waves also influenced the eddies.

Cross-Slope Transport by a Mesoscale Anticyclone in the Northern South China Sea

Cross-slope eddies play an important role in the exchange of water, salt, heat, nutrients, chlorophyll, phytoplankton and other biogeochemical elements between basin and shelf in the South China Sea. The cross-slope transport process by a mesoscale anticyclonic eddy is studied by ROMS model and satellite data. The 1000 m isobath was considered as a proxy for the slope. The anticyclone shows different features at different places on the slope: (a) the volume transport at the northeast of the slope was off-slope, while at the southwest was on-slope; (b) both on and off-slope transports were greatly enhanced during the cross-slope process, and gradually weakened after crossing the slope. The total cross-slope water transport was 5.97 Sv, which was higher than the along-slope component with −0.58 Sv. The Eulerian results also showed that enhanced cross-slope transport was related to the distance between the eddy and slope, the eddy radius, and the eccentricity of the eddy. The offline passive tracer experiment showed that particles were floating up during and after the crossing process, mainly due to the strong Ekman pumping.

Near-Inertial Wave Interactions and Turbulence Production in a Kuroshio Anticyclonic Eddy

Abstract Interactions between near-inertial waves and the balanced eddy field modulate the intensity and location of turbulent dissipation and mixing. Two EM-APEX profiling floats measured near-inertial waves generated by Typhoons Mindulle, 22 August 2016, and Lionrock, 30 August 2016, near the radius of maximum velocity of a mesoscale anticyclonic eddy in the Kuroshio–Oyashio confluence east of Japan. High-vertical-wavenumber near-inertial waves exhibit energy fluxes inward toward eddy center, consistent with wave refraction/reflection at the eddy perimeter. Near-inertial kinetic energy tendencies are nearly two orders of magnitude greater than observed turbulent dissipation rates ε, indicating propagation/advection of wave packets in and out of the measurement windows. Between 50 and 150 m, ε ∼ (10−10) W kg−1, more than an order of magnitude weaker than outside the eddy, pointing to near-inertial wave breaking at different depths or eddy radii. Between 150 and 300 m, small-scale inertial-period patches of intense turbulence with near-critical Ri occur where comparable near-inertial and eddy shears are superposed. Three-dimensional ray-tracing simulations show that wave dynamics at the eddy perimeter are controlled by radial gradients in vorticity and Doppler shifting with much weaker contributions from vertical gradients, stratification, and sloping isopycnals. Surface-forced waves are initially refracted downward and inward, consistent with the observed energy flux. A turning-point shadow zone is found in the upper pycnocline, consistent with weak observed dissipation rates. In summary, the geometry of wave–mean flow interaction creates a shadow zone of weaker near-inertial waves and turbulence in the upper part while turning-point reflections amplify wave shear leading to enhanced dissipation rates in the lower part of the eddy.

Observed Near-Inertial Waves Trapped in a Propagating Anticyclonic Eddy

Abstract Near-inertial waves (NIWs) trapped in a propagating anticyclonic eddy (AE) are investigated along the eddy path at three areas spanning 660 km by using two mooring arrays and a cruise transect. In the upstream area, the reconstructed three-dimensional structure reveals that NIWs are concentrated within the eddy core with wave current amplitudes exceeding 0.2 m s−1; vertically, due to the critical layer effect caused by eddy baroclinicity, NIWs are trapped at depths around 200 and 315 m with frequencies estimated to be ω1 ≈ 0.918f and ω2 ≈ 0.985f, respectively. After the AE propagates southwestward for hundreds of kilometers, the NIWs of frequency ω1 are still detectable inside the AE, while NIWs of frequency ω2 are absent because of the equatorward migration of the AE on a beta plane. Meanwhile, the wave kinetic energy downstream is trapped closer to the eddy center in radial direction, with the wave amplitude decaying roughly in a Gaussian form along the eddy radius, and becomes more homogeneous in the azimuthal direction, showing a more regular trapping form in the three-dimensional view. Investigation on wind shows that trapped NIWs are likely to be generated by a typhoon but less affected by the wind during the eddy passage time. By an energy analysis, we find that enhanced wave dissipation near the critical layer is roughly balanced by the energy transfer from mean flows, and therefore the trapped wave kinetic energy is largely conserved during the long-distance migration.

Evaluation of HY-2 Series Satellites Mapping Capability on Mesoscale Eddies

With the launches of HY-2B, HY-2C and HY-2D, the National Satellite Ocean Application Service (NSOAS) successfully established the first batch of HY-2 constellation on 19 May 2021, dedicated to detecting the marine dynamic environment. While the validation and calibration of HY-2 series satellites have been well studied, using both in situ and cross-track measurements, further evaluation is required of HY-2 series satellites mapping capability on mesoscale eddies. In this study, we conducted two groups of pseudo-observations obtained by ocean models output at positions and times of the satellite along ground tracks. The two altimetry satellite combinations are the Jason-3+Sentinel-3A/B configuration (reference group) and the Jason-3+Sentinel-3A/B+HY-2B/C/D configuration (evaluation group). Three regions at different latitudes were selected as the study areas. Then, we gridded the satellite along ground tracks into synthetic SSH products for each satellite configuration group. Finally, the attributes of mesoscale eddies extracted from gridded products were analyzed to evaluate the mapping capability of HY-2 series satellites. Our results suggest that the gridded products of evaluation groups are more similar to model data compared to reference groups, with a maximum difference reduced by 23%. In terms of eddy identification, the evaluation groups using HY-2 series satellites can alleviate eddy incorrect estimation and add more details to the spatial distribution of eddy radius and amplitude. Additionally, the evaluation groups displayed better performance in mesoscale eddy detection, with a maximum enhancement of 14% and 16% in eddy recognition rate and accuracy.

Features of Intraseasonal Variability Observed in the Upper-Layer Current in the Northern South China Sea

This study reveals the features of the strong intraseasonal variability (ISV) of the upper-layer current in the northern South China Sea (NSCS) based on four long-time mooring observations and altimeter data. The ISV of the upper-layer current in the NSCS consists of two dominant periods of 10–65 days and 65–110 days. The ISV with period of 10–65 days is much strong in the Luzon Strait and decays rapidly westward along the slope. The ISV with the period of 65–110 days is relatively strong along the slope with two high cores at 115 and 119°E, whereas it is weak in the Luzon Strait. The 10–65-day ISV can propagate directly from the western Pacific into the NSCS for most of the time. However, due to its long wavelength, the 65–110-day ISV propagates into the NSCS indirectly, possibly similar to the wave diffraction phenomenon. The spatial differences between the two main frequency bands are primarily due to the baroclinic and barotropic instabilities. The spatial distribution of the upper-layer ISV is closely associated with the mesoscale eddy radius of the NSCS. The eddy radius is directly proportional to the strength of 65–110-day ISV, but it is inversely proportional to the strength of 10–65-day ISV.

Submesoscale Eddies in the South China Sea

AbstractSubmesoscale eddies are often seen in high‐resolution satellite‐derived ocean color images. To efficiently identify these eddies from surface chlorophyll data, here, we develop an automatic submesoscale eddy detection method and apply it to the South China Sea. The detected submesoscale eddies are found to have a radius of 13 ± 5 km and an aspect ratio of 0.5 ± 0.2, with a notable predominance of cyclones. Further investigation reveals that the surface structure of these eddies displays a unique “cat's‐eye” pattern, and the eddies become more circular with increasing eddy radius. Submesoscale eddies can strongly regulate surface chlorophyll via horizontal advection while they have less coherent signatures in sea surface temperature. These findings may help to improve submesoscale parameterizations in Earth system models.

Lagrangian Drifter to Identify Ocean Eddy Characteristics

Deterministic–stochastic empirical mode decomposition (EMD) is used to obtain low-frequency (non-diffusive; i.e., background velocity) and high-frequency (diffusive; i.e., eddies) components from a Lagrangian drifter‘s trajectory. Eddy characteristics are determined from the time series of eddy trajectories from individual Lagrangian drifters such as eddy radius, eddy velocity, eddy Rossby number, and the eddy–current kinetic energy ratio. A long-term dataset of the Sound Fixing and Ranging (RAFOS) float time series obtained near the California coast by the Naval Postgraduate School from 1992 to 2004 at depth between 150 and 600 m is used as an example to demonstrate the capability of the deterministic–stochastic EMD.