Ocean Circulation Research Articles

Synergistic Utilization of Spaceborne SAR Observations for Monitoring the Baltic Sea Flow Through the Danish Straits

AbstractSynthetic aperture radar (SAR) has emerged as a key instrument in oceanography due to its high spatial resolution and sensitivity to ocean surface dynamics. The main limitation of a single spaceborne SAR is the long repeat cycle (e.g., 12 days for Sentinel‐1), which hinders its capability to monitor the temporal evolution of oceanic processes. The principal objective of this study is to demonstrate the potential of spaceborne SAR to monitor the temporal variation of ocean surface circulation. This is assessed using the Baltic Sea flow through the Danish strait Fehmarn Belt as a case study. In order to overcome the temporal sampling limitation, data from three satellites are combined, namely Sentinel‐1A, Sentinel‐1B and TanDEM‐X. The average revisit time achieved by combining the three satellites is 1.2 days. Two months of opportunistic SAR data (June and July 2020) covering the Fehmarn Belt are used. The radial surface current derived from SAR is compared to ocean model and in situ data. It is shown that the dominant processes that govern the circulation in the Fehmarn Belt exhibit time scales larger than 2 days. Subsequently, it is demonstrated that SAR effectively captures the synoptic‐scale features (time scales larger than 2 days) of the Baltic Sea circulation, thereby enabling monitoring the temporal variations of flow dynamics. Comparison of the SAR‐derived radial surface current against in situ measurements yields comparable bias (0.08 m/s) and correlation coefficient (R 0.75) but lower standard deviations and rms errors (0.15 m/s) than those exhibited by the ocean model (0.31 m/s).

Future increase in extreme El Niño supported by past glacial changes

El Niño events, the warm phase of the El Niño–Southern Oscillation (ENSO) phenomenon, amplify climate variability throughout the world1. Uncertain climate model predictions limit our ability to assess whether these climatic events could become more extreme under anthropogenic greenhouse warming2. Palaeoclimate records provide estimates of past changes, but it is unclear if they can constrain mechanisms underlying future predictions3–5. Here we uncover a mechanism using numerical simulations that drives consistent changes in response to past and future forcings, allowing model validation against palaeoclimate data. The simulated mechanism is consistent with the dynamics of observed extreme El Niño events, which develop when western Pacific warm pool waters expand rapidly eastwards because of strongly coupled ocean currents and winds6,7. These coupled interactions weaken under glacial conditions because of a deeper mixed layer driven by a stronger Walker circulation. The resulting decrease in ENSO variability and extreme El Niño occurrence is supported by a series of tropical Pacific palaeoceanographic records showing reduced glacial temperature variability within key ENSO-sensitive oceanic regions, including new data from the central equatorial Pacific. The model–data agreement on past variability, together with the consistent mechanism across climatic states, supports the prediction of a shallower mixed layer and weaker Walker circulation driving more frequent extreme El Niño genesis under greenhouse warming.

Performance of the Earth Explorer 11 SeaSTAR Mission Candidate for Simultaneous Retrieval of Total Surface Current and Wind Vectors

Interactions between ocean surface currents, winds and waves at the atmosphere-ocean interface are key controls of lateral and vertical exchanges of water, heat, carbon, gases and nutrients in the global Earth System. The SeaSTAR satellite mission concept proposes to better quantify and understand these important dynamic processes by measuring two-dimensional fields of total surface current and wind vectors with unparalleled spatial and temporal resolution (1 × 1 km2 or finer, 1 day) and unmatched precision over one continuous wide swath (100 km or more). This paper presents a comprehensive numerical analysis of the expected performance of the Earth Explorer 11 (EE11) SeaSTAR mission candidate in the case of idealised and realistic 2D ocean currents and wind fields. A Bayesian framework derived from satellite scatterometry is adapted and applied to SeaSTAR’s bespoke inversion scheme that simultaneously retrieves total surface current vectors (TSCV) and ocean surface vector winds (OSVW). The results confirm the excellent performance of the EE11 SeaSTAR concept, with Root Mean Square Errors (RMSE) for TSCV and OSVW at 1 × 1 km2 resolution consistently better than 0.1 m/s and 0.4 m/s, respectively. The analyses highlight some performance degradation in some relative wind directions, particularly marked at near range and low wind speeds. Retrieval uncertainties are also reported for several variations around the SeaSTAR baseline three-azimuth configuration, indicating that RMSEs improve only marginally (by ∼0.01 m/s for TSCV) when including broadside Radial Surface Velocity or broadside dual-polarisation data in the inversion. In contrast, our results underscore a) the critical need to include broadside Normalised Radar Cross Section data in the inversion; b) the rapid performance degradation when broadside incidence angles become steeper than 20° from nadir; and c) the benefits of maintaining ground squint angle separation between fore and aft lines-of-sight close to 90°. The numerical results are consistent with experimental performance estimates from airborne data and confirm that the EE11 SeaSTAR concept satisfies the requirements of the mission objectives.

Regulation of Ocean Surface Currents and Seasonal Sea Ice Variations on the Occurrence and Transport of Organophosphate Esters in the Central Arctic Ocean.

Organophosphate esters (OPEs) have been observed in the remote Arctic Ocean, yet the influence of hydrodynamics and seasonal sea ice variations on the occurrence and transport of waterborne OPEs remains unclear. This study comprehensively examines OPEs in surface seawater of the central Arctic Ocean during the summer of 2020, integrating surface ocean current and sea ice concentration data. The results confirm significant spatiotemporal variations of the OPEs, with the total concentration of seven major OPEs averaging 780 ± 970 pg/L. Chlorinated OPEs, particularly tris(1-chloro-2-propyl) phosphate (TCPP), were dominant. The significant impact of hydrodynamics on the OPE transport is demonstrated by higher OPE concentrations in regions with strong surface currents, especially at the edge of the Beaufort Gyre and the confluence of the Beaufort Gyre and the Transpolar Drift. Furthermore, OPE levels were generally higher in drifting-ice-covered regions compared to ice-free regions, attributed to the volatilization of dissolved OPEs formerly trapped below the sea ice or newly released from melting snow and sea ice. Notably, TCPP decreased by only 19% in the ice-free area, while the more volatile triphenyl phosphate decreased by 63% compared with the partial ice region.

Scattering of water waves by thick porous breakwater placed over sloped rigid seabed in the presence of ocean current

Scattering of water waves by thick porous breakwater placed over sloped rigid seabed in the presence of ocean current

Visualization Method for Mesoscale Eddies Characteristics in Ocean Flow Fields Based on Variable Particle Systems

Visualization of ocean flow fields is a major area of interest in marine science. Existing visualization methods based on randomly generated particles tend to exhibit a uniform distribution. While this approach effectively represents ocean flow fields, it inadequately conveys the characteristic structures within the flow in an intuitive manner. Ocean eddies, as crucial components of ocean dynamics (Patrizio & Thompson, 2021), are key features in visualizing ocean flow fields. Mesoscale eddies, which contain 90% of the ocean's kinetic energy, play a vital role in transporting this energy. These eddies significantly influence local marine environments and are instrumental in understanding the kinetic energy of ocean flow fields, providing valuable insights for fields such as oceanography, meteorology, and climate research. The aim of this study is to establish a method based on variable particle systems. Initially, a feature set for mesoscale eddies and a parameter set for variable particles are defined. By mapping the feature set to the parameter set, we express the characteristic structure of mesoscale eddies dynamically. Using ocean flow field data, we demonstrate the method's ability to effectively highlight the characteristic structures of mesoscale eddies within the flow field through qualitative and quantitative evaluation metrics. By analyzing and visualizing ocean flow fields, we can gain a deeper understanding of their spatiotemporal evolution, thereby uncovering the patterns and regularities of their movement. This research approach not only facilitates the effective development, utilization, and sustainable management of marine resources but also aligns with the demands of digital ocean technology for visualizing marine spatial information.

Hierarchical decision-making approach for the task planning of the BWBUG cluster with three-dimensional time-varying ocean currents

This study concerns the task planning problem for a Blended-Wing-Body Underwater Glider (BWBUG) cluster with three-dimensional, time-varying ocean currents. The objective is to achieve task allocation and three-dimensional glide path planning for the BWBUG cluster in a manner that ensures safety and cost-effectiveness. First, the task planning problem for the BWBUG cluster is analyzed, detailing the task requirements and operational space. Next, a hierarchical decision-making approach is proposed, which comprises an upstream planner and a downstream planner. The upstream planner aims to determine a feasible task space for the BWBUG cluster while satisfying task constraints. The downstream planner fully considers the impact of ocean currents on BWBUG movement, as well as the safety and kinematic constraints of BWBUGs. It optimizes the three-dimensional movement trajectories of each BWBUG with the objective of minimizing energy consumption. Inspired by the nest-seeking behavior of bees, a novel heuristic algorithm called the Bee Nesting Optimization Algorithm (BNOA) is proposed to solve both upstream and downstream planning problems. The results of the simulations demonstrate the efficacy of the hierarchical decision-making approach developed in this study. Additionally, the proposed BNOA is highly competitive, offering reasonable task allocations and optimal three-dimensional glide paths for the BWBUG cluster.

A lie group PMP approach for optimal stabilization and tracking control of autonomous underwater vehicles

AbstractIn this research, we explore a finite horizon optimal stabilization and tracking control scheme for the dynamical model of a 6‐DOF Autonomous Underwater Vehicle (AUV). Dynamical equations of the AUV are represented in a Lie group () framework, encompassing both translational and rotational motions. Utilizing a left Lie group action on , we define error function for velocities via a right transport map to effectively address optimal trajectory tracking. The optimal control objective is formulated as a trade‐off problem, aiming to minimize both errors and control effort simultaneously. Left action on yields the left trivialized Hamiltonian function from which the concomitant state and costate dynamical equations are derived using Pontryagin's Minimum Principle (PMP). Consequently, the resulting two‐point boundary value problem is solved to obtain optimal trajectories. We demonstrate the optimality of the resulting solution obtained from the derived control law. For ensuring boundedness in the presence of small disturbances, this study incorporates the effects of internal parametric uncertainties associated with added mass and inertia components, along with the influence of external disturbances induced by ocean currents. Through simulation validations, we confirm the alignment of our results with the theoretical developments, demonstrating that the proposed control law effectively mitigates both parametric uncertainties and ocean current disturbances.

Revisiting the connection between variations in the Tsushima Warm Current and winter rainfall along the coast of Japan

AbstractEnhanced autumn transport via the Tsushima Warm Current (TWC) has been reported to increase winter rainfall along Japan’s northern coast. However, observations reveal a significantly weakened correlation after 2006. Although enhanced transport via the Eastern channel of the Tsushima Strait affects rainfall by enhancing latent heat flux along Japan’s northern coast, the role of oceanic flows in varying sea-surface temperatures has weakened since 2006. Stronger northwesterly winds co-occur with enhanced surface heat loss that overwhelms the impact of the TWC. Our findings imply that atmospheric conditions should be considered when using TWC transport as a precursor for winter rainfall.

An analytical solution to the soil’s dynamic response induced by wave interaction with a marine current characterized by a non-uniform vertical profile

In this work, we obtain an analytical solution to the soil’s dynamic response induced by wave interaction with a marine current with a prescribed non-uniform vertical profile. The control volume used to analyze the present problem is divided into a water region and another composed of a poroelastic soil region. The governing equations for the water hydrodynamics are presented in its dimensionless version and they are simplified for the limit of linear water waves. The velocity field in the water region is determined from the continuity equation and the “inviscid Orr-Sommerfeld linear equation”. We obtain a dispersion equation for wave-current interaction. For modeling the soil’s dynamics response, we adopt the u-p approximation. Considering a characteristic criterion for soil liquefaction, the maximum liquefaction depth is obtained as an eigenvalue problem. The analytical estimations, valid for the limit of linear water waves, provided by the present analysis show that, marine currents traveling in the same direction to the wave propagation induces larger values of the liquefaction depth than those obtained for currents opposite to wave propagation. As a first approximation, the present analysis may help understand the dynamic response of poroelastic soil induced by the wave-non-uniform marine current interaction.

Oceanographical-driven dispersal and environmental variation explain genetic structure in an upwelling coastal ecosystem

The seascape comprises multiple environmental variables that interact with species biology to determine patterns of spatial genetic variation. The environment imposes spatially variable selective forces together with homogenizing and diverging drivers that facilitate or restrict dispersal, which is a complex, time-dependent process. Understanding how the seascape influences spatial patterns of genetic variation remains elusive, particularly in coastal upwelling systems. Here, we combine genome-wide SNP data, Lagrangian larval dispersal simulated over a hydrodynamic model, and ocean environmental information to quantify the relative contribution of ocean circulation and environmental heterogeneity as drivers of the spatial genetic structure of two congeneric intertidal limpets, Scurria scurra and S. araucana, along the central coast of Chile. We find that a genetic break observed in both limpet species coincides with a break in connectivity shown by the Lagrangian dispersal, suggesting that mean ocean circulation is an important seascape feature, in particular for S. scurra. For S. araucana, environmental variation appears as a better predictor of genetic structure than ocean circulation. Overall, our study shows broad patterns of seascape forcing on genetic diversity and contributes to our understanding of the complex ecological and evolutionary interactions along coastal upwelling systems.

Enhanced ocean heat storage efficiency during the last deglaciation

Proxy reconstructions suggest that increasing global mean sea surface temperature (GMSST) during the last deglaciation was accompanied by a comparable or greater increase in global mean ocean temperature (GMOT), corresponding to a large heat storage efficiency (HSE; ∆GMOT/∆GMSST). An increased GMOT is commonly attributed to surface warming at sites of deepwater formation, but winter sea ice covered much of these source areas during the last deglaciation, which would imply an HSE much less than 1. Here, we use climate model simulations and proxy-based reconstructions of ocean temperature changes to show that an increased deglacial HSE is achieved by warming of intermediate-depth waters forced by mid-latitude surface warming in response to greenhouse gas and ice sheet forcing as well as by reduced Atlantic meridional overturning circulation associated with meltwater forcing. These results, which highlight the role of surface warming and oceanic circulation changes, have implications for our understanding of long-term ocean heat storage change.

Atmospheric blocking slows ocean-driven melting of Greenland’s largest glacier tongue

Mass loss from the Greenland ice sheet has contributed to global sea-level rise over the past 20 years. Yet direct observations from the 79 North Glacier (79NG) calving front reveal decreasing Atlantic Intermediate Water (AIW) temperatures below the ice tongue from 2018 to 2021, leading to reduced ocean heat transport. This is linked to a concurrent decrease in basal melt and thinning rates at the grounding line. The origin of this AIW cooling is traced to a slowdown of the large-scale ocean circulation in the Nordic Seas, driven by European atmospheric blocking that strengthens cold air advection from the central Arctic through the Fram Strait. Blocking has driven major ocean cooling events over the last 50 years and will remain crucial in affecting Northeast Greenland’s glaciers.

Ocean Currents Velocity Hindcast and Forecast Bias Correction Using a Deep-Learning Approach

Today’s prediction of ocean dynamics relies on numerical models. However, numerical models are often unable to accurately model and predict real ocean dynamics, leading to a lack of fulfillment of a range of services that require reliable predictions at various temporal and spatial scales. Indeed, a numerical model cannot fully resolve all the physical processes in the ocean due to various reasons, including biases in the initial field and calculation errors in the numerical solution of the model. Thus, bias-correcting methods have become crucial to improve the dynamical accuracy of numerical model predictions. In this study, we present a machine learning-based three-dimensional velocity bias correction method derived from historical observations that applies to both hindcast and forecast. Our approach is based on the modification of an existing deep learning model, called U-Net, designed specifically for image segmentation analysis in the biomedical field. U-Net was modified to create a Transform Model that retains the temporal and spatial evolution of the differences between the model and observations to produce a correction in the form of regression weights that evolves spatially and temporally with the model both forward and backward in time, beyond the observation period. Using daily ocean current observations from a 2.5-year current meter array deployment, we show that significant bias corrections can be conducted up to 50 days pre- or post-observations. Using a 3-year-long virtual array, valid bias corrections can be conducted for up to one year.

Refined Estimates of Global Ocean Deep and Abyssal Decadal Warming Trends

AbstractDeep and abyssal layer decadal temperature trends from the mid‐1980s to the mid‐2010s are mapped globally using Deep Argo and historical ship‐based Conductivity‐Temperature‐Depth (CTD) instrument data. Abyssal warming trends are widespread, with the strongest warming observed around Antarctic Bottom Water (AABW) formation regions. The warming strength follows deep western boundary currents transporting abyssal waters north and decreases with distance from Antarctica. Abyssal cooling trends are found in the North Atlantic and eastern South Atlantic, regions primarily ventilated by North Atlantic Deep Water (NADW). Deep warming trends are prominent in the Southern Ocean south of about 50°S, the Greenland‐Iceland‐Norwegian (GIN) Seas and the western subpolar North Atlantic, with cooling in the eastern subpolar North Atlantic and the subtropical and tropical western North Atlantic. Globally integrated decadal heat content trends of 21.6 (±6.5) TW in the deep and 12.9 (±1.8) TW in the abyssal layer are more certain than previous estimates.

Vertical transport of anthropogenic lead by reversible scavenging in the South Atlantic Ocean

Stable lead (Pb) isotopes have been regarded as tracers of ocean circulation, both in the present time and geological past. Here we present a new dataset of seawater Pb concentrations and isotope compositions for ten depth profiles from the South Atlantic Ocean (GEOTRACES cruises GA02 and GA10). By comparing Pb isotope data collected on the two cruises, and by modelling the distribution of Pb with an extended optimum multiparameter analysis, we find evidence of vertical transport of anthropogenic Pb pollution due to reversible scavenging. Surface to depth transfer of polluted Pb is aided by high suspended particulate matter loads at the Brazil – Malvinas Confluence and along ∼40°S in the South Atlantic. Overall, our findings caution the use of Pb isotope ratios as ventilation tracers in the South Atlantic and emphasize the importance of particle-seawater interaction for biogeochemical cycles.

Near‐surface wind variability in Prydz Bay and Amery Ice Shelf region, East Antarctica: A four‐decade SOM analysis

AbstractNear‐surface wind fields in the Prydz Bay and Amery Ice Shelf region of East Antarctica play a crucial role in the formation and variability of Antarctic Bottom Water, a cold, dense water mass that sinks and spreads across the deep ocean basins influencing ocean circulation and modulating earth's climate system. This study investigates the primary modes of variability of these wind fields using the self‐organizing map (SOM) method and data from the latest version of the European Centre for Medium‐Range Weather Forecasts (ECMWF) ReAnalyses (ERA5), spanning four decades from 1979 to 2020. While the wind field climatology, characterized by small seasonal variation, is dominated by katabatic and large‐scale forcing, the spatial patterns of the primary variability modes are mainly influenced by synoptic system activities. The overall trend in annual wind speed anomalies is positive across the study region, with the exception of the southwestern part and central Prydz Bay. However, significant trends are observed in only two out of nine SOM nodes (nodes 4 and 9), which collectively explain less than 30% of the averaged trends over the region. The interannual variability in the seasonal occurrences of certain nodes is linked to several well‐known climate modes, including the El Niño–Southern Oscillation, the Southern Annular Mode and Zonal Wavenumber 3. Our results provide a reference for forecasting the occurrence frequency of specific patterns, which could help mitigate the impact of extreme wind events through improved forecasting.

Predicting particle catchment areas of deep-ocean sediment traps using machine learning

Abstract. The ocean's biological carbon pump plays a major role in climate and biogeochemical cycles. Photosynthesis at the surface produces particles that are exported to the deep ocean by gravity. Sediment traps, which measure deep-carbon fluxes, help to quantify the carbon stored by this process. However, it is challenging to precisely identify the surface origin of particles trapped thousands of meters deep due to the influence of ocean circulation on the sinking path of carbon. In this study, we conducted a series of numerical Lagrangian experiments in the Porcupine Abyssal Plain region of the North Atlantic and developed a machine learning approach to predict the surface origin of particles trapped in a deep-ocean sediment trap. Our numerical experiments support the predictive performance of the machine learning approach, and surface conditions appear to provide valuable information for accurately predicting the source area, suggesting a potential application with satellite data. We also identify factors that potentially affect prediction efficiency, and we show that the best predictions are associated with low kinetic energy and the presence of mesoscale eddies above the trap. This new tool could provide a better link between satellite-derived sea surface observations and deep-ocean sediment trap measurements, ultimately improving our understanding of the biological-carbon-pump mechanism.

From fringe to basin: unravelling the survival strategies of Calanus hyperboreus and C. glacialis in the Arctic Ocean

The large calanoids Calanus hyperboreus and C. glacialis dominate the zooplankton biomass in the central Arctic Ocean (CAO), but the absence of early life stages has raised speculation whether they complete their life cycle there, or whether they represent expatriates advected from adjacent regions. Our study, conducted across 2 transects of the CAO during fall 2011, focused on the distribution, stage composition, dry weight, individual lipid content, and egg production of these species. Although reproductive activity and early developmental stages were observed only on the fringes of the deep basins, late-stage copepodite and adult female abundances remained steady across the study area for C. glacialis and increased away from the shelves for C. hyperboreus. We found no decline in lipid content or dry weight in adult C. glacialis away from productive regions and only a minor reduction in adult C. hyperboreus. However, the lipid content and dry weight in C5 copepodites significantly decreased away from the shelf break, particularly in C. hyperboreus. This suggests that although early life stages struggle to survive in the resource-limited conditions of the deep CAO and even subadults remain vulnerable to starvation, adults have the resilience to survive long enough to be eventually transported by ocean currents to more favourable regions for reproduction. As such, we suggest that both species of Calanus are neither ‘residents’ nor ‘expatriates’ in the Arctic basins, but rather ontogenetic migrants that take advantage of different habitats within the Arctic Ocean to maximise their survival and reproductive success.

Calibration of a hybrid sea ice model during an expedition to the Arctic

AbstractWe describe the acquisition and evaluation of data during the ArcWatch II expedition into the Arctic Ocean on board of the icebreaker Polarstern. The data is used to calibrate a hybrid sea ice model that focuses on modeling the marginal ice zone, which is the transition zone between pack ice and the open ocean. We describe the experimental setup used to track the motion of individual ice floes as well as the measurement of the wind and the ocean current. In the literature, the motion of an ice floe in the free‐drift regime is often estimated by Nansen's rule of thumb, which assumes the sea ice drifts at of the wind speed, deflected up to in clockwise direction. Analyzing the first datasets, we noticed that observed small ice floes in free drift often have a larger relative angle to the wind direction. Based on numerical simulation we quantify that these larger angles are related to the geometry of larger sea ice floes in the vicinity of the observed ice floe. These large icefloes influence the ocean current, which in turn, impacts the motion of the small ice floes in the surrounding.