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Ocean eddies affect large‐scale circulation and induce a kinetic energy cascade through their non‐linear interactions. However, since global observations of eddy dynamics come from satellite altimetry maps that smooth eddies and distort their geometry, the strength of this cascade is underestimated. Here, we use deep learning to improve observational estimates of global surface geostrophic currents and explore the implications for the cascade. By synthesizing multi‐modal satellite observations of sea surface height (SSH) and temperature, we achieve up to a 30% improvement in spatial resolution over the community‐standard SSH product. This reveals numerous strongly interacting eddies that were previously obscured by smoothing. In many regions, these newly resolved eddies lead to nearly an order‐of‐magnitude increase in the upscale kinetic energy cascade that peaks in spring and is strong enough to drive the seasonality of large mesoscale eddies. Our study suggests that deep learning can be a powerful paradigm for satellite oceanography. Plain Language Summary: We developed a deep learning method to estimate global maps of surface ocean currents from satellite observations with significantly improved resolution and accuracy compared to existing methods. These maps dramatically improve our ability to observe eddy dynamics and the impact of eddies on the transfer of energy between scales in the ocean. Our study suggests that deep learning can be a powerful paradigm for satellite oceanography. Key Points: We develop the first deep learning global estimates of surface ocean currents from multi‐modal satellite observationsOur deep learning method is able to map surface currents with state‐of‐the‐art resolution and accuracyThe diagnosed kinetic energy cascade is an order of magnitude higher compared to conventional altimetry products [ABSTRACT FROM AUTHOR]

Harnessing ocean kinetic energy has emerged as a promising renewable energy solution in recent years. However, identifying optimal locations for extracting this energy remains a significant challenge. This study presents a novel scheme to estimate the total surface current (TSC) as permanent surface current by integrating geodetic data and in-situ measurements. The TSC is typically a combination of the geostrophic current, derived from dynamic topography, and the Ekman current. We utilize NOAA's Ekman current data to complement the geostrophic current and obtain the TSC. To further enhance the accuracy of the TSC estimates, we employ a 3DVAR data assimilation method, incorporating local current meter observations. The results are verified against two control current meter stations. The data-assimilation process resulted in an improvement of 4 to 15 cm/s in the precision of calculated TSC. Using the assimilated TSC data, we then assess the kinetic energy potential and identify six regions with the most significant promise for marine kinetic energy extraction. This innovative approach can assist researchers and policymakers in targeting the most suitable locations for harnessing renewable ocean energy. [ABSTRACT FROM AUTHOR]

The recurring occurrence of green tides as an ecological disaster has been reported annually in the Yellow Sea. While remote sensing technology effectively tracks the scale, extent, and duration of green tide outbreaks, there is limited research on the underlying driving mechanisms of green tide drift transport and the determination of the leeway coefficient. This study investigates the green tide transport mechanism and evaluates the feasibility of estimating the leeway coefficient by analyzing green tide drift velocities obtained from Geostationary Ocean Color Imager-II (GOCI-II) images using the maximum cross-correlation (MCC) technique and leeway method across various time intervals alongside ocean current and wind speed data. The results reveal the following: (1) Significant spatial variations in green tide movement, with a distinct boundary at 34°40′N. (2) Short-term green tide transport is primarily influenced by tidal forces, while wind and ocean currents, especially the combined Ekman and geostrophic current component, predominantly govern net transport. (3) Compared to 1, 3, and 7 h intervals, estimating the leeway coefficient with a 25 h interval is feasible for moderate-resolution geostationary images, yielding values consistent with previous studies. This study offers new insights into exploring the transport mechanisms of green tides through remote sensing-driven velocity. [ABSTRACT FROM AUTHOR]

We analyze the feasibility of so-called radial surface currents as derived from Sentinel-1 Wave mode Doppler shift observations to support the geodetic estimation of the mean dynamic topography (MDT). Broadly defined as subtracting the geoid from the mean sea surface, this separation problem suffers from data inhomogeneities and usually requires strong prior assumptions about the MDT's smoothness. Recent advancements in calibration and current retrieval methodology for Sentinel-1 data give reason to assess potential gains from this observation type, which can be linked to the gradient of the MDT under geostrophic approximation. Due to current lack of long time-series, we synthesize 10 years of observations from daily surface currents grids and include these in a parametric least-squares adjustment of the MDT. Our results utilizing the synthetic data in place of smoothness constraints are promising, showing 2 cm RMS agreement with a state-of-the-art MDT model. [ABSTRACT FROM AUTHOR]

By decomposing the total sea surface current into its geostrophic and ageostrophic components, we examined the contribution of each to the long-term variability of the total sea surface current. Our findings demonstrate the importance of geostrophic currents in Baltic Sea gyre formations. Additionally, ageostrophic currents contribute significantly to the flow across the region. Quantifying the difference between total sea surface current fields has revealed two dominant general sea surface circulation patterns in the Baltic Sea, whose characteristics correspond to the monthly mean climatology of sea surface current fields in May and December. Subsequently, a machine learning technique was employed to effectively detect the types of sea surface circulation patterns using wind vectors and sea level anomaly fields. This underscored the combined influence of sea level anomaly-driven and wind-driven components in shaping surface current vectors in the Baltic Sea, consistent with geostrophic and ageostrophic decompositions. [ABSTRACT FROM AUTHOR]

In order to address the issue of limited common coverage and high cost in mapping ocean surface vector current by two (or more) high-frequency surface wave radars, this paper proposes a single-station surface wave radar vector current inversion algorithm. The feasibility of this algorithm has been validated in the Taiwan Strait. Based on the ocean dynamic characteristics of the Taiwan Strait, the algorithm utilizes the radial current obtained from a high-frequency surface wave radar (HFSWR) in Fujian Province to invert the ocean surface vector current. The surface vector current can be decomposed into three primary dynamic components: tidal currents, wind-driven currents, and geostrophic currents. Firstly, tidal current forecasting models and Ekman and Stokes theories are used to calculate the tidal and wind-driven currents in the Taiwan Strait, respectively. Subsequently, the directions of geostrophic currents in the Taiwan Strait are determined with sea surface height data, and the magnitudes of the geostrophic currents are constrained using the radial current from the single HFSWR. Finally, the three components are added together to obtain the vector current. Comparative results demonstrate that the efficacy of the algorithm has been validated through field experiments (with two HFSWRs and two drifting buoys) conducted in the southwestern of the Taiwan Strait. Further research is needed on the applicability of this algorithm to other sea areas and monitoring systems. [ABSTRACT FROM AUTHOR]

A shift of El Niño onset location from eastern Pacific (EP) to western Pacific (WP) occurred around 1970. It was accompanied by a faster mean sea surface temperature (SST) warming in WP and a change of precursory SST and wind anomaly patterns. The eigenvalue analysis of a simple coupled model shows that an SST anomaly (SSTA) in WP may grow under the post-1970 mean condition but cannot under the pre-1970 mean condition. As a result, a warm SSTA appeared in WP accompanying to a preceding La Niña condition in EP after 1970, whereas such a warming was rarely seen before 1970. The preceding SSTA patterns led to distinctive zonal wind responses in EP, favoring El Niño onset in EP prior to 1970. For the post-1970 El Niño onset, an initial warming in WP was induced by anomalous downward solar radiation in association with atmospheric meridional overturning circulation or anomalous horizontal advection associated with thermocline induced eastward geostrophic currents. [ABSTRACT FROM AUTHOR]

In the northwestern Barents Sea the warm and salty Atlantic Water meets the cold and fresh Polar Water, forming a distinct thermohaline front, the Barents Sea Polar Front. Here we present the structure of the front, its variability and associated mixing using observations from two cruises conducted in October 2020 and February 2021 during the Nansen Legacy project in the region between the Hopen Trench and the Olga Basin. Ocean stratification, currents and turbulence data were obtained during seven ship transects across the Polar Front near 77° N, 30° E. These transects are complemented by four missions using ocean gliders, one of which was equipped with microstructure sensors to measure turbulence. Across the front, we observe warm (> 1 °C) and salty (> 35.0 g kg -1) Atlantic Water intruding below the colder (< 0 °C) and fresher (< 34.6 g kg -1) Polar Water, setting up a baroclinic front and geostrophic currents reaching 25 cm s -1 , with estimated eastward transport of 0.2±0.6 Sv (1 Sv =1×106 m 3 s -1). We observe anomalous warm- and cold-water patches on the cold and warm side of the front, respectively, colocated with enhanced turbulence, where dissipation rates of turbulent kinetic energy range between 10-8 and 10-7 W kg -1. Short-term variability below the surface mixed layer arises from tidal currents and mesoscale eddies. While the effects of tidal currents are mainly confined to the bottom boundary layer, eddies induce significant shifts in the position of the front and alter the isopycnal slopes and the available potential energy of the front. Substantial water mass transformation is observed across the front, likely a result of eddy-driven isopycnal mixing. Despite the seasonal changes in the upper layers of the front (0–100 m) influenced by atmospheric forcing, sea ice formation and brine rejection, the position of the front beneath 100 m depth remained relatively unperturbed. [ABSTRACT FROM AUTHOR]

Based on satellite-observed and reanalysis data, this study investigates a thermal front east of the Gulf of Thailand (TFEGT) during the winter from 1982 to 2021. TFEGT exhibits distinct seasonal and interannual variation, emerging in December, peaking in February, gradually diminishing in March, and completely dissipating in April. Notably, the occurrence probability, area, and intensity of the thermal front are significantly higher in January and February compared with December and March. Through the application of a mixed temperature equation, we identify that geostrophic advection, driven by windinduced western boundary current in the South China Sea (SCS), plays a crucial role in the formation of the TFEGT. In winter, the prevailing northeast monsoon propels the western boundary current through wind stress curl, causing the southward transport of cold water from north to south. This cold water encountered warm water within the Gulf of Thailand (GoT), leading to the formation of TFEGT. Furthermore, the interannual variation of TFEGT is closely associated with the El Niño-Southern Oscillation (ENSO). In El Niño (La Niña) years, the northeast monsoon weakens (enhances), resulting in a weaker (stronger) western boundary current, ultimately influencing the weakening (enhancement) of TFEGT. [ABSTRACT FROM AUTHOR]

Exceptional precision and excellent resolution reconstruction of sea surface currents are beneficial for exploring complex oceanic dynamic processes. Normally, this required physical inversion models for global or regional oceans are constructed to reconstruct oceanic currents. These models are based on the analysis of sea surface geostrophic and Ekman currents derived from satellite observations of sea level and wind stress fields. Nevertheless, the presence of various typical dynamic processes in marine environments, such as mesoscale eddies and small-scale waves, continues to pose challenges in accurately reconstructing oceanic currents. Meanwhile, any product of surface current that neglects the contribution of wave motion would, at best, be incomplete. Therefore, in this paper, we introduce an accurate sea surface current product at a depth of 15 m, named GEST (Geostrophic-Ekman-Stokes-Tide). This product is produced by a multi-scale dynamics-informed neural network that learns the intricate representation of concealed characteristics in Ekman, geostrophic currents, wave-induced Stokes drift, and TPXO9 tidal currents. Its structure design is predicated upon the intricate coupling relationships between various ocean surface components and the veritable currents discerned by the deployment of drift buoys, with each ocean surface component correlating to discrete physical processes. Compared with the prevailing product, the GEST confers an elevation in precision by approximately 9.2 cm/s over the traditional multinomial fitting method, 10.4 cm/s beyond the OSCAR, and 8.81 cm/s surpassing GlobCurrent. [ABSTRACT FROM AUTHOR]

Satellite altimetry offers a unique approach for direct sea surface current observation, but it is limited to measuring the surface‐constrained geostrophic component. Ageostrophic dynamics, prevalent at horizontal scales below 100 km and time scales below 10 days, are often underestimated by ocean reanalyzes employing data assimilation schemes. To address this limitation, we introduce a novel deep learning scheme, rooted in a variational data assimilation formulation with trainable observations and a priori terms, that harnesses the synergies between satellite‐derived sea surface observations, namely sea surface height (SSH) and sea surface temperature (SST), to enhance sea surface current reconstruction. Numerical experiments, conducted using realistic simulations, in a case study area of the Gulf Stream, demonstrate the potential of the proposed scheme to capture ageostrophic dynamics at time scales of 2.5–3.0 days and horizontal scales of 0.5°–0.7°. The analysis of diverse observation configurations, encompassing nadir along‐track altimetry, wide‐swath SWOT (Surface Water and Ocean Topography) altimetry, and SST data, highlights the pivotal role of SST features in retrieving a significant portion of the ageostrophic dynamics (approximately 47%). These findings underscore the potential of deep learning and 4DVarNet schemes in improving ocean reanalyzes and enhancing our understanding of ocean dynamics. Plain Language Summary: Satellite altimetry provides a unique means for direct observation of sea surface currents, but it is confined to the geostrophic component, limiting the recovery of a substantial portion of mesoscale sea surface currents in operational products. To address this limitation, we present a novel deep learning framework, rooted in a variational data assimilation paradigm, that unlocks new avenues for leveraging the synergistic relationships between satellite‐derived sea surface observations, namely sea surface height and sea surface temperature. This innovative scheme demonstrates its remarkable potential to enhance sea surface current reconstruction and recover a substantial portion of the elusive ageostrophic dynamics. Numerical experiments, employing realistic simulations, in a case study area along the Gulf Stream, underscore the efficacy of our proposed approach. These findings support the pivotal role of physics‐informed deep learning in maximizing the utilization of available multimodal observation data sets and numerical simulations to elucidate partially observed sea surface dynamics. Key Points: We present end‐to‐end deep learning schemes to improve the reconstruction of total sea surface currents from satellite‐derived observationsExperiments in a region of the Gulf Stream support the synergistic analysis of sea surface temperature and sea surface height dataThe strain of sea surface dynamics is a proxy of the uncertainty of the retrieved estimation [ABSTRACT FROM AUTHOR]

For the past 20 years, Global Navigation Satellite System reflectometry (GNSS-R) technology has successfully shown its potential for remote sensing of the Earth's surface, including ocean and land surfaces. It is a multistatic radar that uses the GNSS signals reflected from the Earth's surface to extract land and ocean characteristics. Because of its numerous advantages such as low cost, multiple signal sources, and all-day/weather and high-spatiotemporal-resolution observations, this new technology has attracted the attention of many researchers. One of its most promising applications is GNSS-R ocean altimetry, which can complement existing techniques such as tide gauging and radar satellite altimetry. Since this technology for ocean altimetry was first proposed in 1993, increasing progress has been made including diverse methods for processing reflected signals (such as GNSS interferometric reflectometry, conventional GNSS-R, and interferometric GNSS-R), different instruments (such as an RHCP antenna with one geodetic receiver, a linearly polarized antenna, and a system of simultaneously used RHCP and LHCP antennas with a dedicated receiver), and different platform applications (such as ground-based, air-borne, or space-borne). The development of multi-mode and multi-frequency GNSS, especially for constructing the Chinese BeiDou Global Navigation Satellite System (BDS-3), has enabled more free signals to be used to further promote GNSS-R applications. The GNSS has evolved from its initial use of GPS L1 and L2 signals to include other GNSS bands and multi-GNSS signals. Using more advanced, multi-frequency, and multi-mode signals will bring new opportunities to develop GNSS-R technology. In this paper, studies of GNSS-R altimetry are reviewed from four perspectives: (1) classifications according to different data processing methods, (2) different platforms, (3) development of different receivers, and (4) our work. We overview the current status of GNSS-R altimetry and describe its fundamental principles, experiments, recent applications to ocean altimetry, and future directions. [ABSTRACT FROM AUTHOR]

This study presents a generalised characterisation of the surface circulation over the northern shelf of the Gulf of Cadiz, based on 4 years of high-resolution satellite altimetry data from Sentinel-3A and wind model data. The altimetry-based surface zonal currents, adjusted for bottom-drag and wind effects, are compared with a generic CMEMS product and validated against in-situ ADCP measurements. The proposed altimetry product demonstrates superior performance than the CMEMS product, accurately reflecting surface circulation direction compared to in-situ measurements (r = 0.77, RMSE = 0.10 m/s, bias = 0.01 m/s). The use of the bottom-drag and wind-corrected/uncorrected altimetry product for spatiotemporal analysis of the shelf circulation revealed the distinct contributions of wind-driven and geostrophic components in different basin sectors. The results show that over the western basin, positive (eastward) surface currents were predominantly driven by westerly winds, while only occasionally, westward flows coincided with easterly winds, suggesting a higher control of the geostrophic component over the westward flows. In contrast, over the eastern basin, both eastward and westward flows were found to be primarily driven by favourable winds. Additionally, the analysis of Absolute Dynamic Topography (ADT) values along the whole basin showed the presence of ADT gradients both along-shore and cross-shore over the shelf, contributing to geostrophic flows. Finally, the seasonal analysis showed that eastward circulation tends to dominate during the spring and summer months, related to the upwelling season in the Gulf of Cadiz and associated westerly winds. Westward flows prevail during the winter months, related to easterly winds and the rebalancing of the along-shore sea level gradient during relaxed upwelling conditions. The findings demonstrate a significant improvement in the use of satellite altimetry data to study complex oceanographic dynamics in coastal areas, where both spatial and temporal variability are high. Moreover, the similarity of our results to those obtained from in-situ systems supports the use of altimetry data and publicly available wind models to support oceanographic studies in remote or resource-limited areas. [ABSTRACT FROM AUTHOR]

Accurate prediction of ocean surface currents is important for marine safety, ship routing, tracking of pollutants and in coupled forecasting. Presently, velocity observations are not routinely assimilated in global ocean forecasting systems, largely due to the sparsity of the observation network. Several satellite missions are now being proposed with the capability to measure Total Surface Current Velocities (TSCV). If successful, these would substantially increase the coverage of ocean current observations and could improve accuracy of ocean current forecasts through data assimilation. In this paper, Observing System Simulation Experiments (OSSEs) are used to assess the impact of assimilating TSCV in the Met Office's global ocean forecasting system. Synthetic observations are generated from a high-resolution model run for all standard observation types (sea surface temperature, profiles of temperature and salinity, sea level anomaly and sea ice concentration) as well as TSCV observations from a Sea surface KInematics Multiscale monitoring (SKIM) like satellite. The assimilation of SKIM like TSCV observations is tested over an 11 month period. Preliminary experiments assimilating idealised single TSCV observations demonstrate that ageostrophic velocity corrections are not well retained in the model. We propose a method for improving ageostrophic currents through TSCV assimilation by initialising Near Inertial Oscillations with a rotated incremental analysis update (IAU) scheme. The OSSEs show that TSCV assimilation has the potential to significantly improve the prediction of velocities, particularly in the Western Boundary Currents, Antarctic Circumpolar Current and in the near surface equatorial currents. For global surface velocity the analysis root-mean-squareerrors (RMSEs) are reduced by 23% and there is a 4-day gain in forecast RMSE. There are some degradations to the subsurface in the tropics, generally in regions with complex vertical salinity structures. However, outside of the tropics, improvements are seen to velocities throughout the water column. Globally there are also improvements to temperature and sea surface height when TSCV are assimilated. The TSCV assimilation largely corrects the geostrophic ocean currents, but results using the rotated IAU method show that the energy at inertial frequencies can be improved with this method. Overall, the experiments demonstrate significant potential benefit of assimilating TSCV observations in a global ocean forecasting system. [ABSTRACT FROM AUTHOR]

The coastal ocean off western Patagonia is one of the main coastal regions with high freshwater inputs from rivers, rain, and glaciers in the Southern Hemisphere. This study conducts an analysis of the seasonal and interannual variations in sea surface salinity and meridional geostrophic transports, specifically focusing on the Cape Horn Current, using improved satellite-derived data of sea surface salinity (SSS) and geostrophic velocities spanning an ∼11-year period (September 2011–August 2022). Our results reveal a clear salinity minimum in a coastal band between 42–54°S associated with the highest freshwater content. The average geostrophic currents are stronger south of 49°S, in line with the location of the Cape Horn Current. The average salinity minimum tends to disappear south of 54°S, with salinity values increasing slightly southward. The seasonal cycle of salinity shows the most pronounced minimum in summer (∼33.2–33.4). The greatest variability in salinity (standard deviation of salinity fields) occurs in the southern region of the Cape Horn Current. Hovmöller plots reveal two cores of minimum salinity observed in spring and summer (∼33.3–33.4). The freshwater off the Gulf of Penas contributes to the northern core. The meridional geostrophic transport differs between the northern and southern sections, with transports predominantly towards the Equator (Pole) north (south) of about 47–48°S during spring–summer. There is a marked seasonal variability in the magnitude and northern limit of the southward-flowing Cape Horn Current, being extended further north during winter and with a maximum average magnitude during summer–fall (about − 2 × 10 4 m2 s−1). On the interannual scale, a major drop in surface salinity occurred off northern and central Patagonia during 2018–2019. Finally, a potential long-term freshening trend is observed in the coastal area off southern Patagonia (south of 52°S), although prolonged data records are essential to confirm this pattern. [ABSTRACT FROM AUTHOR]

The ocean regulates the Earth's climate by transporting heat from the equator to the poles. Here, we use satellite‐based sea surface observations of air‐sea heat fluxes and eddy detection to investigate the mesoscale heat transport. "Mesoscale" refers to both the Eulerian perspective as the spatio‐temporal scales of ∼100 km and ∼1 month, as well as the Lagrangian aspect as isolated vortices identified from the dynamic topography. Paradoxically, there are a considerable number of mesoscale eddies inconsistent between their surface thermal and dynamic signals, that is, cold‐core anticyclones and warm‐core cyclones are globally prevalent. On account of such inconsistency, we show that the mesoscale meridional heat transport carried by geostrophic components is 10 times larger than (and opposite in direction to) that of the wind‐driven Ekman components. An offset between SSH‐SST coherent and incoherent eddies in the Ekman heat transport is apparent, whereas the geostrophic heat transport is contained within coherent eddies. Plain Language Summary: Rotating water masses in the ocean, termed as mesoscale eddies, are dynamically important features because they can transport nutrients and displace heat in the Earth's climate system. In the same manner as the atmospheric weather systems that are associated with high or low pressures, mesoscale eddies are accompanied by sea level anomalies and therefore can be observed by satellite images. Conventionally, anticyclonic eddies detected as clockwise vortices in the Northern Hemisphere display warm temperature anomalies at the center. However, recent studies have found that the sea surface temperature signal of an eddy might be uncertain and even contradictory to their dynamical circulation patterns. In this study, we combine sea surface observations of temperature and velocity fields to determine the patterns of global ocean heat transport associated with mesoscale eddies. Key Points: The geostrophic component of meridional heat transport (MHT) at the mesoscale is 10 times larger than the Ekman componentSSH‐SST coherent eddies dominate the spatial patterns of MHT at the mesoscaleThough incomparable in magnitude with the large scale MHT, mesoscale eddies can still transport 30 TW of heat near sea surface [ABSTRACT FROM AUTHOR]

Realistic representation of monthly sea level anomalies in coastal regions has been a challenge for global ocean reanalyses. This is especially the case in coastal regions where sea levels are influenced by western boundary currents such as near the U.S. Atlantic Coast and the Gulf of Mexico. For these regions, most ocean reanalyses compare poorly to observations. Problems in reanalyses include errors in data assimilation and horizontal resolutions that are too coarse to simulate energetic currents like the Gulf Stream and Loop Current System. However, model capabilities are advancing with improved data assimilation and higher resolution. Here, we show that some current-generation ocean reanalyses produce monthly sea level anomalies with improved skill when compared to satellite altimetry observations of sea surface heights. Using tide gauge observations for coastal verification, we find the highest skill associated with the GLORYS12 and HYCOM ocean reanalyses. Both systems assimilate altimetry observations and have eddy-resolving horizontal resolutions (1/12°). We found less skill in three other ocean reanalyses (ACCESS-S2, ORAS5, and ORAP6) with coarser, though still eddy-permitting, resolutions (1/4°). The operational reanalysis from ECMWF (ORAS5) and their pilot reanalysis (ORAP6) provide an interesting comparison because the latter assimilates altimetry globally and with more weight, as well as assimilating ocean observations over continental shelves. We find these attributes associated with improved skill near many tide gauges. We also assessed an older reanalysis (CFSR), which has the lowest skill likely due to its lower resolution (1/2°) and lack of altimetry assimilation. ACCESS-S2 likewise does not assimilate altimetry, although its skill is much better than CFSR and only somewhat lower than ORAS5. Since coastal flooding is influenced by sea level anomalies, the recent development of skilful ocean reanalyses on monthly timescales may be useful for better understanding the physical processes associated with flood risks. [ABSTRACT FROM AUTHOR]

We present a study on the ocean surface currents reconstruction by merging Level-4 (L4, gap-free) altimeter-derived geostrophic currents and satellite sea surface temperature. Building upon past studies on the multi-variate reconstruction of geostrophic currents from satellite observations, we regionalized and optimized an algorithm to improve the altimeter-derived surface circulation estimates in the North Atlantic Ocean. A ten-year-long time series (2010–2019) is presented and validated by means of in situ observations. The newly optimized algorithm allowed us to improve the currents estimate along the main axis of the Gulf Stream and in correspondence of well-known upwelling areas in the North Eastern Atlantic, with percentage improvements of around 15% compared to standard operational altimetry products. [ABSTRACT FROM AUTHOR]

We present a study on the ocean surface currents reconstruction by merging Level-4 (L4, gap-free) altimeter-derived geostrophic currents and satellite sea surface temperature. Building upon past studies on the multi-variate reconstruction of geostrophic currents from satellite observations, we regionalized and optimized an algorithm to improve the altimeter-derived surface circulation estimates in the North Atlantic Ocean. A ten-year-long time series (2010–2019) is presented and validated by means of in situ observations. The newly optimized algorithm allowed us to improve the currents estimate along the main axis of the Gulf Stream and in correspondence of well-known upwelling areas in the North Eastern Atlantic, with percentage improvements of around 15% compared to standard operational altimetry products.

Satellite-based observations and a pan-Arctic coupled sea ice-ocean model are utilized to study the effect of ocean geostrophic currents on large-scale sea ice circulation in the Canada Basin, Arctic Ocean. We find that surface winds primarily drive sea ice drifts in the west–east direction, while the geostrophic currents in the Beaufort Gyre promote north–south ice drifts. Wind fluctuations can create variable ice drifts, yet geostrophic currents respond more slowly due to their larger vertical scale, serving as a slowly-evolving conveyor belt for maintaining the anticyclonic ice circulation. It is further demonstrated that the bathymetry can regulate the movement of sea ice via constraining the expansion of ocean circulation. This mechanism is indirect in the sense that the ice is far from the seafloor. Our research underscores the necessity of considering the bathymetry-constrained geostrophic currents in understanding Arctic sea ice dynamics. With the rapid retreat of Arctic sea ice, the multi-scale interactions between ice drifts and ocean currents may have significant implications for the Arctic ecosystem, climate, and shipping corridors.