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Monthly climatology data for salinity fronts in the South Atlantic have been created from satellite SMOS sea surface salinity (SSS) measurements taken from 2011–2019, processed at the Barcelona Expert Center of Remote Sensing (BEC), and provided as high-resolution (1/20°) daily SSS data. The SSS fronts have been identified with narrow zones of enhanced horizontal gradient magnitude (GM) of SSS, computed using the Belkin–O'Reilly algorithm (BOA). The SSS gradient fields generated by the BOA have been log-transformed to facilitate feature recognition. The log-transformation of SSS gradients markedly improved the visual contrast of gradient maps, which in turn allowed new features to be revealed and previously known features to be documented with a monthly temporal resolution and a mesoscale (~100 km) spatial resolution. Monthly climatologies were generated and analyzed for large-scale open-ocean SSS fronts and for low-salinity regions maintained by the Rio de la Plata discharge, Magellan Strait outflow, Congo River discharge, and Benguela Upwelling. A 2000 km-long triangular area between Africa and Brazil was found to be filled with regular quasi-meridional mesoscale striations that form a giant ripple field with a 100 km wave length. South of the Tropical Front, within the subtropical high-salinity pool, a trans-ocean quasi-zonal narrow linear belt of meridional SSS maximum (Smax) was documented. The meridional Smax belt shifts north–south seasonally while retaining its well-defined linear morphology, which is suggestive of a yet unidentified mechanism that maintains this feature. The Subtropical Frontal Zone (STFZ) consists of two tenuously connected fronts, western and eastern. The Brazil Current Front (BCF) extends SE between 40 and 45°S to join the subantarctic front (SAF). The STFZ trends NW–SE across the South Atlantic, seemingly merging with the SAF/BCF south of Africa to form a single front between 40 and 45°S. In the SW Atlantic, the Rio de la Plata plume migrates seasonally, expanding northward in winter (June–July) from 39°S into the South Brazilian Bight, up to Cabo Frio (23°S) and beyond. The inner Plata front moves in and out seasonally. Farther south, the Magellan Strait outflow expands northward in winter (June–July) from 53°S up to 39–40°S to nearly join the Plata outflow. In the SE Atlantic, the Congo River plume spreads radially from the river mouth, with the spreading direction varying seasonally. The plume is often bordered from the south by a quasi-zonal front along 6°S. The diluted Congo River water spreads southward seasonally down to the Angola–Benguela Front at 16°S. The Benguela Upwelling is delineated by a meridional front, which extends north alongshore up to 20°S, where the low-salinity Benguela Upwelling water forms a salinity front, which is separate from the thermal Angola–Benguela Front at 16°S. The high-salinity tropical water ("Angola water") forms a wedge between the low-salinity waters of the Congo River outflow and Benguela Upwelling. This high-salinity wedge is bordered by salinity fronts that migrate north–south seasonally. [ABSTRACT FROM AUTHOR]

Typhoons can greatly alter the hydrodynamic and nutrient supply in coastal oceans. However, due to the complex conditions of typhoons, such as their intensity, even slight changes may cause substantial changes in hydrodynamics and nutrient supply, which needs to be better understood. In this study, we conducted two cruises before and after Typhoon Talim (2023) to quantitatively investigate changes in hydrodynamics and nutrient supply in Zhanjiang Bay using dual water isotopes. Before the typhoon, strong stratification occurred in the bay. However, the strong external force of the typhoon destroyed the stratification and substantially changed the water mixing in the bay after the typhoon. In the upper bay, massive freshwater input remarkably decreased the salinity during the post-typhoon period (freshwater increased by 18%). In contrast, the salinity variation in the lower bay was minimal, mainly due to massive seawater intrusion from the outer bay induced by the typhoon; the seawater mixed with freshwater columns from the upper bay, forming a strong ocean front. The intensity of ocean fronts induced by typhoons directly depended on the typhoon intensity landing in Zhanjiang Bay, as stronger typhoons will cause more intrusion of high-salinity seawater from the outer bay. Due to the formation of the ocean front, freshwater and terrestrial nutrients from the upper bay are prevented from being transported downwards, resulting in a large amount of accumulated pollutants within the bay. By contrast, due to the impact of high-salinity seawater intrusion, the contribution of seawater from the outer bay has increased, thereby diluting the nutrients in the lower bay. This study provides a new insight into the responses of coastal marine eco-environment systems to typhoons. [ABSTRACT FROM AUTHOR]

Recent findings showed that midlatitude oceanic fronts in the Kuroshio‐Oyashio Extension (KOE) region may significantly influence the overlying atmosphere on the decadal timescale. However, the exact mechanism and the combined effects of both the Kuroshio Extension Front (KEF) and the Oyashio Extension Front (OEF) are still largely unknown. Here we use front‐resolving ERA5 reanalysis data to investigate the characteristics and mechanisms of the atmospheric response to decadal fluctuations of the KEF and OEF in a consistent way. It is found that the atmospheric response is equivalent barotropic with upper‐level intensification in terms of both basic flow and storm track. The geopotential height and storm track responses over western subpolar North Pacific are of opposite signs driven by intensifying KEF and OEF. Diagnosis showed that eddy vorticity feedback is responsible for the basic flow response at upper levels, whereas direct linear response to surface thermal forcing dominates at lower levels. The upper‐level eddy response is realized by midlevel diabatic conversion which is forced by changes of near‐surface background baroclinicity. In total, the decadal modulation by the KEF and OEF explains 19% (12%) of the variance of geopotential height (storm track) variability at 250 hPa (500 hPa), which is much higher than found in previous studies, presumably due to the higher resolution and the consideration of both fronts. Plain Language Summary: The Kuroshio and Oyashio Extensions currents are associated with sharp gradients of sea surface temperature (SST), known as the Kuroshio Extension Front (KEF) and Oyashio Extension Front (OEF). These two fronts vary on a period of about one decade, both strengthening while moving northward, but with a delay time of 2.5 years. Such decadal variability has the potential to change the mean state of the overlying atmosphere, and can also cause changes in the atmosphere's storm statistics known as the storm track. It has been difficult to precisely describe the ocean fronts' influence because they are too narrow to be recognized from atmospheric models. Here we use a data set that can better resolve the ocean fronts, and quantitatively examine the combined influence of the two fronts. Results show that the decadal variability of the two fronts can explain 19% of the variance of mid‐troposphere pressure variations. They impact the atmosphere through the same mechanism: first change the instability of the lower atmosphere, thereby drive more storms in the mid‐levels, which in turn force the circulation to change, maximizing in the upper troposphere. The intensification of the two fronts, however, drive mostly opposite responses due to their different SST anomaly patterns. Key Points: KEF and OEF drive significant atmospheric circulation and storm track responsesThe atmospheric response is a combination of the transient eddy feedback and direct thermal response to SST anomaliesConsidering the combined impacts of the two fronts and using high‐resolution data set are crucial [ABSTRACT FROM AUTHOR]

The ocean front has a non-negligible role in global ocean–atmosphere interactions, marine fishery production, and the marine military. Hence, obtaining the positions of the ocean front is crucial in oceanic research. At present, the positioning method of recognizing an ocean front has achieved a breakthrough in the mean dice similarity coefficient (mDSC) of above 90%, but it is difficult to use to achieve rapid extraction in emergency scenarios, including marine fisheries and search and rescue. To reduce the its dependence on machines and apply it to more requirements, according to the characteristics of an ocean front, a multi-scale model SQNet (Simple and Quick Net) dedicated to ocean front position recognition is designed, and its perception domain is expanded while obtaining current scale data. In experiments along the coast of China and the waters of the Gulf of Mexico, it was not difficult to find that SQNet exceedingly reduced running time while ensuring high-precision results (mDSC of higher than 90%). Then, after conducting intra-model self-comparison, it was determined that expanding the perceptual domain and changing the weight ratio of the loss function could improve the accuracy and operational efficiency of the model, which could be better applied in ocean front recognition. [ABSTRACT FROM AUTHOR]

As one of the widespread physical phenomena in the global ocean system, the ocean front has a very important influence on underwater sound propagation. Firstly, this paper systematically reviews several methods for the detection of ocean fronts in the past decades, including traditional oceanographic methods, artificial intelligence methods, and acoustic methods, highlighting the advantages and disadvantages of each method. Next, some modeling studies of ocean fronts are reported in this paper. Based on the above research, we pay more attention to research progress on the acoustic effects of ocean fronts, including simulation analysis and experimental research, which has also been the focus of underwater acousticians for a long time. In addition, this paper looks forward to the future development direction of this field, which can provide good guidance for the study of ocean fronts and their acoustic effects in the future. [ABSTRACT FROM AUTHOR]

Long-term sea surface salinity (SSS) in the East China Sea (ECS) was estimated based on Ocean Color Climate Change Initiative (OC-CCI) data using machine learning during the summer season (June to September) from 1997 to 2021. Changjiang diluted water (CDW) in the ECS propagates northeastward and forms longitudinally-oriented ocean fronts. To determine the CDW's distribution, three fronts were investigated: (1) a CDW front based on chlorophyll-a concentration (Chl), SSS, and sea surface temperature (SST); (2) a CDW front based on sea surface density (SSD); and (3) a CDW front for nutrient distribution. The Chl fronts matched well with the SSS fronts, suggesting that Chl variation in the ECS is highly correlated with the CDW. Furthermore, the SSD fronts spatially matched well with nitrogen concentration. Sea level anomaly (SLA) variation with SSD was also detected, indicating that CDW had sufficiently large effects on SLA so that they may be detectable by altimeter measurements. This result suggests that the influence of steric height changes and the inflow from rivers are significant in the ECS. Additionally, the continuous long-term SSD developed in this study enables researchers to detect the CDW front and its influence on the ECS marine environment. [ABSTRACT FROM AUTHOR]

Copyright of Hydrographic Surveying & Charting / Haiyang Cehui is the property of Hydrographic Surveying & Charting Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Ocean fronts are mostly determined according to the horizontal temperature gradient, and various selection criteria may lead to different frontal zones. This study proposes a frontal zone delineation method based on sound speed profile. In this paper, the sound speed profile of the Kuroshio intrusion front in the Luzon Strait is classified via fuzzy cluster analysis based on transitive closure and fuzzy C-means algorithm. At the same time, considering that ocean fronts affect sound propagation, we verify the effectiveness of the two algorithms in terms of sound transmission loss. The results show that in different depth ranges, the effectiveness of the two algorithms differs in identifying the frontal zone. At depth below 300 m, the sound speed profile changes drastically, and fuzzy cluster analysis based on the transitive closure is more effective. At 300–700 m depth where the sound speed profile tends to be stable, the fuzzy C-means algorithm is more effective. At 700–1000 m depth near the SOFAR axis (the depth of the minimum sound speed), fuzzy cluster analysis based on the transitive closure is more effective. Finally, based on the sound speed profile, we combine both algorithms for the first time to obtain a three-layer geometric optimized structure of the Kuroshio intrusion front in the Luzon Strait. The classification of sound speed profiles via the two fuzzy cluster algorithms provides a new way to judge the frontal zone in different depth ranges and reconstruct geometric models of ocean fronts.

Ocean fronts can cause the accumulation of nutrients and affect the propagation of underwater sound, so high-precision ocean front detection is of great significance to the marine fishery and national defense fields. However, the existing ocean front detection methods either have low detection accuracy or regard it as a binary classification problem to only detect where the ocean front occurs and cannot identify and distinguish various categories of ocean fronts with different behavior characteristics in different times and regions. In order to solve the above problems, we propose a semantic segmentation network called location and seasonality enhanced network (LSENet) for multiclass ocean fronts detection at pixel level. In this network, we first design a channel supervision unit (CSU) structure, which integrates the seasonal characteristics of the ocean front itself and the contextual information to improve the detection accuracy. We also introduce a location attention (LA) mechanism to adaptively assign attention weights to the fronts according to their frequently occurred sea area, which can further improve the accuracy of multiclass ocean front detection. Compared with other semantic segmentation methods and current representative ocean front detection method at Offshore China and Gulf of Mexico, the experimental results demonstrate convincingly that our method is more effective. The source code and datasets are released and publicly available via https://github.com/lliusha1155/LSENET. [ABSTRACT FROM AUTHOR]

Sea surface temperature (SST) can be measured from space using infrared sensors on Earth-observing satellites. However, the tradeoff between spatial resolution and swath size (and hence revisit time) means that SST products derived from remote sensing measurements commonly only have a moderate resolution (>1 km). In this article, we adapt the design of a super-resolution neural network architecture [specifically very deep super-resolution (VDSR)] to enhance the resolution of both top-of-atmosphere thermal images of sea regions and bottom-of-atmosphere SST images by a factor of 5. When tested on an unseen dataset, the trained neural network yields thermal images that have an RMSE $2-3\times $ smaller than interpolation, with a 6–9 dB improvement in PSNR. A major contribution of the proposed neural network architecture is that it fuses optical and thermal images to propagate the high-resolution information present in the optical image to the restored thermal image. To illustrate the potential benefits of using super-resolution (SR) in the context of oceanography, we present super-resolved SST images of a gyre and an ocean front, revealing details and features otherwise poorly resolved by moderate resolution satellite images. [ABSTRACT FROM AUTHOR]

Ocean fronts have an important influence on global ocean–atmosphere interactions and marine fishery. Hence, it is of great significance to obtain the positions of the ocean fronts. However, current ocean front detection research confronts two challenges: scarcity of labeled data and limitations of ocean front detection algorithms. To address these two problems, we have collected and labeled an ocean front data set and proposed a new deep learning model for ocean front detection. For concreteness, due to the weak edge property of the ocean fronts, we formulate ocean front detection as a weak edge identification problem and propose the weak edge identification network (WEIN) for ocean front detection. WEIN consists of four convolutional blocks. Each block has a side output layer used to detect front edges at a specific image representation level. The side outputs are then fused to predict (detect) the locations of the ocean fronts. In this work, we adopt two metrics to measure the experimental results, i.e., the $F_{1}$ -score and intersection over union (IoU). The experimental results with comparison to traditional and deep learning approaches demonstrate the superiority of WEIN for ocean front detection. [ABSTRACT FROM AUTHOR]

Ocean currents in the southern East China Sea (ECS) are complex and have long lacked systematic observational data. Observations from coastal radars in northern Taiwan, along with several drifters and satellite data, reveal a detailed ECS surface flow structure and thermal front. Drifter trajectories followed the seasonal flow field and were oscillatory and trapped due to strong tidal currents. Three drifters crossed the oceanic front off the northern coast of Taiwan following the tidal motion with a rapid change in the sea surface temperature by 2.5°C, which was recorded within a small distance of 500 m. A significant seasonal water mass exchange cycle occurred in the southern ECS. Starting in October, the Kuroshio Current intrudes onto the ECS shelf, causing the formation of a southwestward Northern Taiwan Coastal Current that mixes with the China Coastal Current to form a southward flow in the northern Taiwan Strait. Beginning in March, the ocean current off northwestern Taiwan shifts northward and then gradually flows eastward into the Kuroshio region. With satellite‐derived and model‐simulated surface currents contradicting each other over long periods of time, hourly coastal radar data have not only successfully explained the spatiotemporal variations in the sea surface temperature, salinity, and chlorophyll concentration observed by satellites but have also resolved the long‐standing disputes over the surface currents in the southern ECS. Plain Language Summary: In the southern East China Sea (ECS), the ocean surface currents observed by satellite altimeters and estimated based on numerical models have considerably differed for a long time, especially in winter. The data observed by shore‐based high‐frequency radar have yielded new discoveries. Beginning in October, the Kuroshio Current intrudes onto the ECS shelf and pushes Kuroshio waters with high temperatures, high salinities, and low chlorophyll concentrations to the west, causing the current from northern Taiwan to flow southwestward into the Taiwan Strait (TS). Then, starting in March, ocean currents off northwestern Taiwan turn northward, and the water off northern Taiwan is pushed eastward back to the Kuroshio region. These flow field variations cause a significant oceanic front in the 121°E−122°E area in the southern ECS. We deployed four surface velocity program (SVP) drifters to observe the ocean flow and used virtual drifters to simulate the distribution probability of the track in each month. The drifters basically followed the movement direction of the seasonal flow field but could have been affected by the significant tidal currents and become trapped. With this study, we aim to better understand the southern ECS environment from a geophysical perspective. Key Points: Coastal radar data and long‐term multisatellite data are used to observe the formation of oceanic fronts driven by ocean currentsThe Kuroshio Current's intrusion of the shelf causes the Northern Taiwan Coastal Current to flow southward along western Taiwan in winterVirtual drifter experiments present the possible trajectories of and seasonal changes in near‐surface ocean currents [ABSTRACT FROM AUTHOR]

As one of the widespread physical phenomena in the global ocean system, the ocean front has a very important influence on underwater sound propagation. Firstly, this paper systematically reviews several methods for the detection of ocean fronts in the past decades, including traditional oceanographic methods, artificial intelligence methods, and acoustic methods, highlighting the advantages and disadvantages of each method. Next, some modeling studies of ocean fronts are reported in this paper. Based on the above research, we pay more attention to research progress on the acoustic effects of ocean fronts, including simulation analysis and experimental research, which has also been the focus of underwater acousticians for a long time. In addition, this paper looks forward to the future development direction of this field, which can provide good guidance for the study of ocean fronts and their acoustic effects in the future.

Copyright of Atmosphere -- Ocean (Taylor & Francis Ltd) is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this study, synthetic aperture radar (SAR) imaging of waves across ocean fronts was investigated using C-band Sentinel-1 VV-polarized SAR imagery collected over the Yangtze and the Zhujiang estuaries. The presence of ocean fronts in the study area was confirmed by collocated sea surface temperature (SST) data provided by the Advanced Very High Resolution Radiometer (AVHRR) and sea surface current information from the National Ocean Partnership Program (NOPP) based on the HYbrid Coordinate Ocean Model (HYCOM). The experimental results revealed that as the current speed increased, the cut-off wavelength (λc) increased as well. The effect of the increasing azimuth cut-off wavelength, however, was relatively weak in terms of variations of the normalized radar cross-section (NRCS), i.e., it was within 2 dB for λc ≤ 60 m. Hence, it was weaker than the NRCS variation related to SST. Larger NRCS variations (i.e., within 5 dB) occurred for λc values up to 120 m. In addition, the experimental results also demonstrated that the parameterized first-guess spectrum method (PFSM) wave retrieval performance was affected by ocean fronts. In particular, overestimations occurred when ocean fronts were present and λc was < 100 m. [ABSTRACT FROM AUTHOR]

The rate of ocean heat uptake depends on the mechanisms that transport heat between the surface and the ocean interior. A recent study found that the vertical heat transport driven by motions with scales smaller than 0.5° (submesoscales) and frequencies smaller than 1 day−1 is upward. This transport competes with the other major components of the global heat transport, namely, the downward heat transport explained by the large‐scale wind‐driven vertical circulation and vertical diffusion at small scales and the upward heat transport associated with mesoscale eddies (50‐ to 300‐km size). The contribution from motions with small spatial scales (<0.5°) and frequencies larger than 1 day−1, including internal gravity waves, has never been explicitly estimated. This study investigates this high‐frequency (subdaily) submesoscale contribution to the global heat transport. The major result of this study, based on the analysis of a high‐resolution ocean model, is that including this high‐frequency contribution surprisingly doubles the upward heat transport due to submesoscales in winter in the global ocean. This contribution typically concerns depths down to 200–500 m and can have a magnitude of up to 500 W m−2 in terms of wintertime heat fluxes at 40‐m depth, which causes a significant upward heat transport of ~7 PW when integrated over the global ocean. Thus, such submesoscale heat transport, which is not resolved by climate models, impacts the heat uptake in the global ocean. The mechanisms involved in these results still need to be understood, which should be the scope of future work. Key Points: Ocean heat flux is large at high frequencySuch high‐frequency flux is generated at submesoscaleSuch heat flux is a key component of global heat budget [ABSTRACT FROM AUTHOR]

Sea surface roughness is affected by surface current gradients, which provides a means of monitoring from satellite sharp oceanic fronts. This paper is the second report of an experiment designed to compare observations of sea surface roughness and surface currents at an unprecedented accuracy, owing to the conjunction of numerous deployed drifters and roughness instruments. About 200 drifters sampled a thin 10 km elongated submesoscale front, also monitored by a high density of roughness instruments: satellite synthetic aperture radar, satellite, and airborne multiangle sunglint radiometers. The first paper focused on the retrieval of the current gradient direction (convergence and cyclonic vorticity) at the front, using roughness observations at multiple angle from airplane. This second paper focuses on the retrieval of the current gradient magnitude and scale, using roughness observations at different scales, from airplane and from satellite. Two main results are obtained: (i) Trajectories of selected drifters show that the front is only 50 m wide and unambiguously exhibits convergence and cyclonic vorticity up to 100f (with f the Coriolis frequency). This far exceeds previously documented values for submesoscale deep ocean fronts. (ii) Correct estimation of such extreme current gradients using surface roughness hinges on instruments with sufficiently high spatial resolution. Lower‐resolution roughness sensors can still detect the front, as demonstrated from observations and a simplified model, but cannot properly estimate the current gradient magnitude and the frontal width. Those results provide guidelines for monitoring intense current gradients from space using sea surface roughness. Plain Language Summary: Ocean surface currents are not uniform horizontally but involve structures of many different sizes. After focusing on large‐scale currents (about 1,000 km) and eddies (about 100 km), attention is nowadays turning toward fine‐scale (about 1 km) fronts and filaments. Those fine structures are indeed particularly important for the exchanges between ocean surface and deeper ocean, for the accumulation of drifting pollution, and for the concentration of biological production and marine predators. Fishermen well know that oceanic fronts can be revealed by visual inspection of the ocean surface roughness. Exploring this idea, this paper investigates how oceanic fronts can be monitored using images of sea surface roughness. Images from satellites and airplanes were taken during an experiment where hundreds of surface drifters were released and got caught within an intense front. Two new lessons are learned from those observations: (1) The front was only 50 m wide, which is much sharper than commonly assumed for fronts of this type. (2) The front is thus associated with extreme current shear, which can only be detected by roughness sensors with sufficiently high spatial resolution. Those are important findings to improve monitoring of intense oceanic fronts from satellite. Key Points: Sea surface roughness induced by a submesoscale oceanic front is measured from satellite and airplane during a drifter release experimentDrifters unambiguously show extreme frontal sharpness with extreme current gradients, including both convergence and cyclonic vorticityAccurate monitoring of such sharp front using surface roughness is demonstrated and hinges on the availability of high‐resolution sensors [ABSTRACT FROM AUTHOR]

Red tide is a marine phenomenon caused by the excessive growth of microscopic algae in the ocean. This study aims to analyze the development trends of red tides in the past 20 years and the dynamic external causes that induce red tides based on existing satellite remote sensing and numerical simulation data. And the changes in dominant species of red tides in different seasons are analyzed. The results show significant temperature fluctuations within the week before the red tide occurs, with an average increase of 1.42 °C. In contrast, the change in salinity is relatively small. Meanwhile, ocean fronts are areas in the ocean where different water masses meet and form boundaries. The average strength of ocean fronts increased by 3.7%, indicating enhanced ocean mixing over a short period of time. Under the combined influence of these factors, the probability of a red tide outbreak in the East China Sea increases rapidly. Therefore, this study has important reference value for further research on the causes of red tides and their response to ocean dynamic changes. • Study analyzes 20-year trend of red tides and their dynamic causes. • Before a red tide, average temperature rises by 1.42 °C; salinity changes little. • Increased ocean front strength by 3.7% boosts East China Sea red tide risk. [ABSTRACT FROM AUTHOR]

Cross-front transport is a vital process in the offshore transport of terrestrial materials. The factors influencing cross-front transport are multifaceted and exhibit regional variability. As important factors regulating material transport patterns in the shelf seas of eastern China, the East Asian Winter Monsoon (EAWM) and Kuroshio current (including its branches) vary on multiple time scales, yet their role in controlling offshore transport is not fully understood. In this paper, cross-front offshore transport in the North Yellow Sea is chosen to investigate the aforementioned issue using numerical simulation. By excluding other potential processes for offshore transport, frontal instability is identified as the primary mechanism for offshore transport, which is triggered by winter storms (bursts of the EAWM); hence, the intensity of offshore transport is highly associated with the strength of winter storms on synoptic scales. However, on the inter-annual scale, the intensity of offshore transport is more likely regulated by the strength of the Kuroshio current, and a warming Kuroshio facilitates offshore transport. Although the role of each factor in controlling the intensity of offshore transport is delineated, the interactive effects of the EAWM and Kuroshio current on offshore transport are quite intricate, and how to quantitatively estimate their roles on multiple time scales remains a challenge using modelling. The results obtained from this study can be applied to analyse cross-front transport throughout the eastern China seas and bear significant implications for future studies on pollutant diffusion, nutrient distribution, and sediment transport in the coastal area. • Cross-front transport around the Shandong Peninsula was revealed using a numerical model. • EAWM and Kuroshio affect the strength of cross-front transport on different time scales. • With global warming, the temperature of Kuroshio might gradually become the primary control of cross-front transport. [ABSTRACT FROM AUTHOR]

As one of the most common mesoscale phenomena in the ocean, the ocean front is defined as a narrow transition zone between two water masses with obviously different properties. In this study, we proposed an ocean front reconstruction method based on the K-means algorithm iterative hierarchical clustering sound speed profile (SSP). This method constructed the frontal zone from the perspective of SSP. Meanwhile, considering that acoustic ray tracing is a very sensitive tool for detecting the location of ocean fronts because of the strong dependence of the transmission loss (TL) on SSP structure, this paper verified the feasibility of the method from the perspective of the TL calculation. Compared with other existing methods, this method has the key step of iterative hierarchical clustering according to the accuracy of clustering results. The results of iterative hierarchical clustering of the SSP can reconstruct the ocean front. Using this method, we reconstructed the ocean front in the Gulf Stream-related sea area and obtained the three-dimensional structure of the Gulf Stream front (GSF). The three-dimensional structure was divided into seven layers in the depth range of 0–1000 m. Iterative hierarchical clustering SSP by K-means algorithm provides a new method for judging the frontal zone and reconstructing the geometric model of the ocean front in different depth ranges.

Oceanic fronts are dynamically active regions of the global ocean that support upwelling and downwelling with significant implications for phytoplankton production and export. However (on time scales  ≳ the inertial time scale), the vertical velocity is 103–104 times weaker than the horizontal velocity and is difficult to observe directly. Using intensive field observations in conjunction with a process study ocean model, we examine vertical motion and its effect on phytoplankton fluxes at multiple spatial horizontal scales in an oligotrophic region in the Western Mediterranean Sea. The mesoscale ageostrophic vertical velocity (∼10 m/day) inferred from our observations shapes the large‐scale phytoplankton distribution but does not explain the narrow (1–10 km wide) features of high chlorophyll content extending 40–60 m downward from the deep chlorophyll maximum. Using modeling, we show that downwelling submesoscale features concentrate 80% of the downward vertical flux of phytoplankton within just 15% of the horizontal area. These submesoscale spatial structures serve as conduits between the surface mixed layer and pycnocline and can contribute to exporting carbon from the sunlit surface layers to the ocean interior. Key Points: High‐resolution observations and numerical simulations of mesoscale and submesoscale features at an intense oceanic frontVertical velocities associated with submesoscale features are significantly higher than on the mesoscaleDownwelling submesoscale features concentrate 80% of downward flux of phytoplankton within 15% of the surface area [ABSTRACT FROM AUTHOR]

This paper provides a concise review of the remote sensing of ocean fronts in marine ecology and fisheries, with a particular focus on the most popular front detection algorithms and techniques, including those proposed by Canny, Cayula and Cornillon, Miller, Shimada et al., Belkin and O’Reilly, and Nieto et al.. A case is made for a feature-based approach that emphasizes fronts as major structural and circulation features of the ocean realm that play key roles in various aspects of marine ecology.

Ocean front plays an important role in marine fishery production and biogeochemical cycling. This letter proposes a multiscale deep framework to meet the need for automatic ocean front detection and fine-grained location. The framework mainly focuses on bringing a well-trained deep learning model into front detection and location on the global satellite sea surface temperature image. First, a multiscale scanner is designed to divide the ocean into small areas of different scales. Then, we introduce the deep model to determine that a front has occurred, and translate the global image into binary ones of various grained. Here, an overlapping scanning way is suggested to locate the front in a small region. Finally, all the binary images are scale-weighted fused into one image, which presents the center and periphery with different brightness levels. Experimental illustrations on three typical areas of the ocean are featured with six scanning scales to show the effectiveness and practical use of the proposed framework. Moreover, the comparison experiments with the traditional method also show its advantages. [ABSTRACT FROM AUTHOR]

The Kuroshio Extension Front (KEF) is one of the most representative mesoscale dynamic processes in the Northwest Pacific, particularly the subsurface KEF that has a substantial influence on the marine environment. Based on the JCOPE2M reanalysis data and WOA23 climatological mean data, this study proposed the Ocean Front Fit Degree (OFFD) as an evaluation criterion for extracting the front lines. For the extraction of the KEF front line, an approach combining isotherms and meridians with the highest temperature gradient was employed. The absolute gradient method and wavelet variance were used for analyzing the spatiotemporal characteristics of the subsurface KEF strength and position. Considering the variations in the KEF characteristics at different time scales, a KEF prediction model based on VMD-LSTM was constructed. The results demonstrated that: (1) The front-line recognition and optimization method proposed in this study is applicable across all water depths and areas with interference and weak fronts, yielding accurate KEF prediction results; (2) The KEF strength and position can be decomposed into trend changes, periodic changes, and irregular wave changes. The factors that may contribute to the low-frequency variations in subsurface KEF include the meridional movement of the Aleutian Low and the Pacific Decadal Oscillation (PDO); (3) The combined VMD-LSTM model predicts the KEF strength with high accuracy, indicating excellent prediction performance and high potential application value compared to individual LSTM model. • Proposed an evaluation criterion, Ocean Front Fit Degree (OFFD), to recognize the front line of the Kuroshio Extension Front (KEF). • Analyzed KEF intensity and position using absolute gradient method and wavelet variance, considering changes in different time scales. • Decomposed KEF intensity and position into trend, periodic, and irregular wave changes. Identified factors leading to low-frequency variations in KEF. • Developed a VMD-LSTM-based KEF prediction model with high accuracy and superior performance compared to the single LSTM model. [ABSTRACT FROM AUTHOR]

Oceanic fronts are key habitats for a diverse range of marine predators, yet how they influence fine-scale foraging behaviour is poorly understood. Here, we investigated the dive behaviour of northern gannets Morus bassanus in relation to shelf-sea fronts. We GPS (global positioning system) tracked 53 breeding birds and examined the relationship between 1901 foraging dives (from time-depth recorders) and thermal fronts (identified via Earth Observation composite front mapping) in the Celtic Sea, Northeast Atlantic. We (i) used a habitat-use availability analysis to determine whether gannets preferentially dived at fronts, and (ii) compared dive characteristics in relation to fronts to investigate the functional significance of these oceanographic features. We found that relationships between gannet dive probabilities and fronts varied by frontal metric and sex. While both sexes were more likely to dive in the presence of seasonally persistent fronts, links to more ephemeral features were less clear. Here, males were positively correlated with distance to front and cross-front gradient strength, with the reverse for females. Both sexes performed two dive strategies: shallow V-shaped plunge dives with little or no active swim phase (92% of dives) and deeper U-shaped dives with an active pursuit phase of at least 3 s (8% of dives). When foraging around fronts, gannets were half as likely to engage in U-shaped dives compared with V-shaped dives, independent of sex. Moreover, V-shaped dive durations were significantly shortened around fronts. These behavioural responses support the assertion that fronts are important foraging habitats for marine predators, and suggest a possible mechanistic link between the two in terms of dive behaviour. This research also emphasizes the importance of cross-disciplinary research when attempting to understand marine ecosystems.

Four end members were inverted from surface sediment grain size data from the South Yellow Sea by using the end member (EM) model. The sediment provenance and hydrodynamic meanings of each EM were discussed based on the frequency and spatial distributions of the EMs. EM1 and EM2 reflect the dynamic transport and sorting processes of the terrigenous sediment, and EM3 and EM4 reflect the modification of relic sand. The ocean front mainly affected transport of relatively coarse terrigenous sediment in the South Yellow Sea, and the fine terrigenous sediments were generally unaffected by the ocean front. Fine sediment could pass through the ocean front and deposit in the central South Yellow Sea under weak tidal condition to form most part of the Central Yellow Sea Mud (CYSM). The CYSM extended toward northwest and southwest. The sediment in the north part of the CYSM mainly consisted of sediment from the Yellow River (Huanghe) in the northwest, and the sediment in the southwest part of CYSM mainly consisted of Subei coastal sediments from both the Yangtze River (Changjiang) and the Yellow River. Compared to the traditional method of sediment grain size analysis, the EM model can determine the EMs and provide better explanations of the sediment provenance and dynamic regional sedimentary environment in the study area. [ABSTRACT FROM AUTHOR]

Identifying priority areas for marine vertebrate conservation is complex because species of conservation concern are highly mobile, inhabit dynamic habitats and are difficult to monitor., Many marine vertebrates are known to associate with oceanographic fronts - physical interfaces at the transition between water masses - for foraging and migration, making them important candidate sites for conservation. Here, we review associations between marine vertebrates and fronts and how they vary with scale, regional oceanography and foraging ecology., Accessibility, spatiotemporal predictability and relative productivity of front-associated foraging habitats are key aspects of their ecological importance. Predictable mesoscale (10s-100s km) regions of persistent frontal activity ('frontal zones') are particularly significant., Frontal zones are hotspots of overlap between critical habitat and spatially explicit anthropogenic threats, such as the concentration of fisheries activity. As such, they represent tractable conservation units, in which to target measures for threat mitigation., Front mapping via Earth observation ( EO) remote sensing facilitates identification and monitoring of these hotspots of vulnerability. Seasonal or climatological products can locate biophysical hotspots, while near-real-time front mapping augments the suite of tools supporting spatially dynamic ocean management., Synthesis and applications. Frontal zones are ecologically important for mobile marine vertebrates. We surmise that relative accessibility, predictability and productivity are key biophysical characteristics of ecologically significant frontal zones in contrasting oceanographic regions. Persistent frontal zones are potential priority conservation areas for multiple marine vertebrate taxa and are easily identifiable through front mapping via EO remote sensing. These insights are useful for marine spatial planning and marine biodiversity conservation, both within Exclusive Economic Zones and in the open oceans. [ABSTRACT FROM AUTHOR]

The subarctic–subtropical transition area of the western North Pacific is an important summer feeding grounds of sei whales. The oceanographic structure and circulation of this area are largely determined by strong oceanic fronts and associated geostrophic currents, namely the Polar Front (PF), Subarctic Front (SAF) and Kuroshio Extension Front (KEF). The relationship between the distribution of sei whales and oceanographic fronts was investigated using a generalized additive model (GAM), and the cetacean sighting survey data and oceanographic observations in July from 2000 to 2007 were used in the analysis. The number of individual sei whales was used as the response variable while the distances from the PF, SAF, and KEF to the whales were used as explanatory variables along with the longitude values. Sei whales were concentrated north and south of the SAF and the areas from 250 to 300 km north and from 100 to 200 km south of the SAF were estimated as high-density areas of sei whales. The entire inter-frontal zone between the PF and SAF featured an elevated concentration of sei whales, and the area south of the PF and along the SAF was identified as an important feeding ground of sei whales in July from 2000 to 2007. [ABSTRACT FROM AUTHOR]

Two predominant currents, the warm Kuroshio Current and the cold Oyashio Current, meet in the Northwest Pacific Ocean. The dynamics of physical oceanographic structures in this region, including frontal zones and meandering eddies, result in a highly productive habitat that serves as a favorable feeding ground for various commercially important species. Neon flying squid, Ommastrephes bartramii, is an important oceanic squid, which is widely distributed in the North Pacific Ocean. Based on the catch data collected by Chinese squid jigging fleets and relevant environmental data, including sea surface temperature (SST) and fronts (represented by gradients of SST and thermocline) during 1998-2009, the variations of oceanic fronts and their influence on the fishing grounds of O. bartramii were evaluated, and the differences in distribution of fishing grounds of O. bartramii in 2000 and 2002 were compared by describing the differences in vertical temperature between 0-300 m. It was found that the preferred horizontal temperature gradient of SST for O. bartramii tended to be centered at 0.01-0.02°C/nm, which attracted nearly 80% of the total fishing effort, and the preferred horizontal temperature gradients at the 50 m and 105 m layers were mainly located at 0.01-0.03°C/nm, which accounted for more than 70% of the total fishing effort during August-October. The preferred vertical temperature gradient within the 0-50 m layer for O. bartramii tended to be centered at 0.15-0.25°C/m during August and September and at 0.10-0.15°C/m in October, implying that the mixed surface layer was distributed at depths of 0-50 m. It was concluded that the vertical temperature gradient was more important than the horizontal temperature gradient in playing a role in forming the fishing ground. The results improved our understanding of the spatial dynamics of the O. bartramii fishery. [ABSTRACT FROM AUTHOR]