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In the modern climate, the ocean below 2 km is mainly filled by waters sinking into the abyss around Antarctica and in the North Atlantic. Paleoproxies indicate that waters of North Atlantic origin were instead absent below 2 km at the Last Glacial Maximum, resulting in an expansion of the volume occupied by Antarctic origin waters. In this study we show that this rearrangement of deep water masses is dynamically linked to the expansion of summer sea ice around Antarctica. A simple theory further suggests that these deep waters only came to the surface under sea ice, which insulated them from atmospheric forcing, and were weakly mixed with overlying waters, thus being able to store carbon for long times. This unappreciated link between the expansion of sea ice and the appearance of a voluminous and insulated water mass may help quantify the ocean’s role in regulating atmospheric carbon dioxide on glacial–interglacial timescales. Previous studies pointed to many independent changes in ocean physics to account for the observed swings in atmospheric carbon dioxide. Here it is shown that many of these changes are dynamically linked and therefore must co-occur.

All exchanges between the open ocean and the Antarctic continental shelf must cross the Antarctic Slope Current (ASC). Previous studies indicate that these exchanges are strongly influenced by mesoscale and tidal variability, yet the mechanisms responsible for setting the ASC’s transport and structure have received relatively little attention. In this study the roles of winds, eddies, and tides in accelerating the ASC are investigated using a global ocean–sea ice simulation with very high resolution (1/48° grid spacing). It is found that the circulation along the continental slope is accelerated both by surface stresses, ultimately sourced from the easterly winds, and by mesoscale eddy vorticity fluxes. At the continental shelf break, the ASC exhibits a narrow (~30–50 km), swift (>0.2 m s −1 ) jet, consistent with in situ observations. In this jet the surface stress is substantially reduced, and may even vanish or be directed eastward, because the ocean surface speed matches or exceeds that of the sea ice. The shelfbreak jet is shown to be accelerated by tidal momentum advection, consistent with the phenomenon of tidal rectification. Consequently, the shoreward Ekman transport vanishes and thus the mean overturning circulation that steepens the Antarctic Slope Front (ASF) is primarily due to tidal acceleration. These findings imply that the circulation and mean overturning of the ASC are not only determined by near-Antarctic winds, but also depend crucially on sea ice cover, regionally-dependent mesoscale eddy activity over the continental slope, and the amplitude of tidal flows across the continental shelf break.

Along various stretches of the Antarctic margins, dense Antarctic Bottom Water (AABW) escapes its formation sites and descends the continental slope. This export necessarily raises the isopycnals associated with lighter density classes over the continental slope, resulting in density surfaces that connect the near-freezing waters of the continental shelf to the much warmer circumpolar deep water (CDW) at middepth offshore. In this article, an eddy-resolving process model is used to explore the possibility that AABW export enhances shoreward heat transport by creating a pathway for CDW to access the continental shelf without doing any work against buoyancy forces. In the absence of a net alongshore pressure gradient, the shoreward CDW transport is effected entirely by mesoscale and submesoscale eddy transfer. Eddies are generated partly by instabilities at the pycnocline, sourcing their energy from the alongshore wind stress, but primarily by instabilities at the CDW–AABW interface, sourcing their energy from buoyancy loss on the continental shelf. This combination of processes induces a vertical convergence of eddy kinetic energy and alongshore momentum into the middepth CDW layer, sustaining a local maximum in the eddy kinetic energy over the slope and balancing the Coriolis force associated with the shoreward CDW transport. The resulting slope turbulence self-organizes into a series of alternating along-slope jets with strongly asymmetrical contributions to the slope energy and momentum budgets. Cross-shore variations in the potential vorticity gradient cause the jets to drift continuously offshore, suggesting that fronts observed in regions of AABW down-slope flow may in fact be transient features.

It is now well established that changes in the zonal wind stress over the Antarctic Circumpolar Current (ACC) do not lead to changes in its baroclinicity nor baroclinic transport, a phenomenon referred to as “eddy saturation.” Previous studies provide contrasting dynamical mechanisms for this phenomenon: on one extreme, changes in the winds lead to changes in the efficiency with which transient eddies transfer momentum to the sea floor; on the other extreme, structural adjustments of the ACC’s standing meanders increase the efficiency of momentum transfer. In this study the authors investigate the relative importance of these mechanisms using an idealized, isopycnal channel model of the ACC. Via separate diagnoses of the model’s time-mean flow and eddy diffusivity, the authors decompose the model’s response to changes in wind stress into contributions from transient eddies and the mean flow. A key result is that holding the transient eddy diffusivity constant while varying the mean flow very closely compensates for changes in the wind stress, whereas holding the mean flow constant and varying the eddy diffusivity does not. This implies that eddy saturation primarily occurs due to adjustments in the ACC’s standing waves/meanders, rather than due to adjustments of transient eddy behavior. The authors derive a quasigeostrophic theory for ACC transport saturation by standing waves, in which the transient eddy diffusivity is held fixed, and thus provides dynamical insights into standing wave adjustment to wind changes. These findings imply that representing eddy saturation in global models requires adequate resolution of the ACC’s standing meanders, with wind-responsive parameterizations of the transient eddies being of secondary importance.

The downslope plumes of dense shelf water (DSW) are critical for the formation of Antarctic Bottom Water (AABW), and thus to the exchange of heat and carbon between surface and abyssal ocean. Previous studies have shown that tides and overflow-forced topographic Rossby waves (TRWs) may have strong impact on the downslope transport of DSW, but it remains unclear how the combined action of these two processes influence the descent processes of DSW, and of the resulting AABW properties. Here, with a synthesis of historical in situ observations and a set of numerical model experiments, we show that tides and TRWs play comparable roles in AABW formation: they both act to accelerate DSW descent to the abyss, leading to the formation of colder and denser AABW. Yet, tides have little impact on AABW formation unless the continental slope is steep enough to suppress TRW generation. We further characterize the dynamical regimes of dense overflows around the entire Antarctic continent based on the relative importance of TRWs versus tides. These findings highlight the pervasive role of high-frequency processes, which are not well represented in the present climate models, in the formation of AABW, and thus in the global overturning circulation. This study identifies the key roles of tides and topographic waves in forming Antarctic bottom water in different regions. The Antarctic coastline is divided into four overflow dynamical regimes, providing guidance for future observations.

The exchange of water across the Antarctic continental shelf break brings warm waters towards ice shelves and glacier grounding lines. Ocean glider observations reveal that eddy-induced transport contributes significantly to this exchange. The exchange of water masses across the Antarctic continental shelf break regulates the export of dense shelf waters to depth as well as the transport of warm, mid-depth waters towards ice shelves and glacial grounding lines 1 . The penetration of the warmer mid-depth waters past the shelf break has been implicated in the pronounced loss of ice shelf mass over much of west Antarctica 2 , 3 , 4 . In high-resolution, regional circulation models, the Antarctic shelf break hosts an energetic mesoscale eddy field 5 , 6 , but observations that capture this mesoscale variability have been limited. Here we show, using hydrographic data collected from ocean gliders, that eddy-induced transport is a primary contributor to mass and property fluxes across the slope. Measurements along ten cross-shelf hydrographic sections show a complex velocity structure and a stratification consistent with an onshore eddy mass flux. We show that the eddy transport and the surface wind-driven transport make comparable contributions to the total overturning circulation. Eddy-induced transport is concentrated in the warm, intermediate layers away from frictional boundaries. We conclude that understanding mesoscale dynamics will be critical for constraining circumpolar heat fluxes and future rates of retreat of Antarctic ice shelves.

Submesoscale flows, occurring at scales of about 1–10 km, are crucial to the vertical transport of heat and other tracers in the upper ocean. These flows are energized by instabilities that extract potential energy from lateral buoyancy gradients, which are ubiquitous in the seasonal sea ice zone. Process studies have shown that submesoscale flows influence sea ice mechanics and thermodynamics. However, it is necessary to quantify the spatiotemporal distribution of submesoscale fluxes in order to upscale their impact. Here, we utilize hydrographic data from seal-borne sensors to demonstrate that the Southern Ocean seasonal ice zone can be separated into three regimes of submesoscale flux variability, which are associated with distinct dominant drivers. Furthermore, the magnitude and sign of the mean heat fluxes in these regimes differs, which dictates their influence on the upper-ocean heat budget, mixed-layer depth, and sea ice properties. The Southern Ocean seasonal ice zone can be divided into 3 dynamical regimes based on the magnitude and sign of the mean submesoscale vertical heat flux using instrumented seal data.

The oceanic Meridional Overturning Circulation (MOC) plays a key role in the climate system, and monitoring its evolution is a scientific priority. Monitoring arrays have been established at several latitudes in the Atlantic Ocean, but other latitudes and oceans remain unmonitored for logistical reasons. This study explores the possibility of inferring the MOC from globally‐available satellite measurements via machine learning (ML) techniques, using the ECCOV4 state estimate as a test bed. The methodological advantages of the present approach include the use purely of available satellite data, its applicability to multiple basins within a single ML framework, and the ML model simplicity (a feed‐forward fully connected neural network (NN) with small number of neurons). The ML model exhibits high skill in MOC reconstruction in the Atlantic, Indo‐Pacific, and Southern Oceans. The approach achieves a higher skill in predicting the model Southern Ocean abyssal MOC than has previously been achieved via a dynamically‐based approach. The skill of the model is quantified as a function of latitude in each ocean basin, and of the time scale of MOC variability. We find that ocean bottom pressure generally has the highest reconstruction skill potential, followed by zonal wind stress. We additionally test which combinations of variables are optimal. Furthermore, ML interpretability techniques are used to show that high reconstruction skill in the Southern Ocean is mainly due to (NN processing of) bottom pressure variability at a few prominent bathymetric ridges. Finally, the potential for reconstructing MOC strength estimates from real satellite measurements is discussed. Plain Language Summary The Meridional Overturning Circulation (MOC) plays a key role in the exchange of heat and chemical constituents between oceans globally, and between the atmosphere and the deep ocean. However, it is currently directly monitored only at a handful of different latitudes in the Atlantic Ocean. Using an ocean simulation constrained by available measurements, we examine the feasibility of monitoring the MOC indirectly using measurements made by satellites. We train a so‐called “neural network” to learn relations between the MOC and satellite‐observable ocean properties, such as pressure at the sea floor. These relations are used to produce reconstructions of the simulated MOC derived from the satellite‐observable ocean properties alone, and to test which satellite‐observable ocean properties and regions may be most impactful in MOC reconstruction. We find that this approach yields high skill in reconstructing the MOC over much of the ocean, suggesting that this approach could be transferred to indirectly monitor the MOC in nature. Key Points The Meridional Overturning Circulation (MOC) is a key ocean circulation pattern, which is under‐observed We use an ocean state estimate to test the feasibility of inferring the MOC based solely on satellite observations A unified machine learning methodology shows high skill in MOC reconstruction as a function of latitude and basin

The Southern Ocean connects the ocean's major basins via the Antarctic Circumpolar Current (ACC), and closes the global meridional overturning circulation (MOC). Observing these transports is challenging because three‐dimensional mesoscale‐resolving measurements of currents, temperature, and salinity are required to calculate transport in density coordinates. Previous studies have proposed to circumvent these limitations by inferring subsurface transports from satellite measurements using data‐driven methods. However, it is unclear whether these approaches can identify the signatures of subsurface transport in the Southern Ocean, which exhibits an energetic mesoscale eddy field superposed on a highly heterogeneous mean stratification and circulation. This study employs Deep Learning techniques to link the transports of the ACC and the upper and lower branches of the MOC to sea surface height (SSH) and ocean bottom pressure (OBP), using an idealized channel model of the Southern Ocean as a test bed. A key result is that a convolutional neural network produces skillful predictions of the ACC transport and MOC strength (skill score of ∼${\\sim} $ 0.74 and ∼${\\sim} $ 0.44, respectively). The skill of these predictions is similar across timescales ranging from daily to decadal but decreases substantially if SSH or OBP is omitted as a predictor. Using a fully connected or linear neural network yields similarly accurate predictions of the ACC transport but substantially less skillful predictions of the MOC strength. Our results suggest that Deep Learning offers a route to linking the Southern Ocean's zonal transport and overturning circulation to remote measurements, even in the presence of pronounced mesoscale variability. Plain Language Summary Monitoring changes in the strengths of Southern Ocean current systems is challenging due to their vast size and the region's relative inaccessibility. This study explores the potential for remotely monitoring these currents via satellite measurements. Neural networks are used to “learn” the relationship between satellite‐measurable ocean properties and the strengths of Southern Ocean currents, using a simplified simulation as a test case. A key question is whether the circulation can be inferred from satellite measurements when the ocean hosts a vigorous field of mesoscale eddies—horizontal swirls of fluid that reach hundreds of kilometers in diameter. Three neural network (NN) frameworks are trained to predict the simulated ocean circulation strength from the simulated satellite measurements, and then their performance is evaluated using a separate segment of the simulation data. It is shown that this approach yields accurate predictions of all of the targeted components of the Southern Ocean circulation strength, provided that the NNs use a “convolutional” filter, which enhances their ability to identify spatial patterns in the simulated satellite measurements, and thus to infer movements of ocean water induced by the eddies. These findings serve to guide future indirect approaches to observing the Southern Ocean using remote sensing. Key Points Deep Learning methods link sea surface height and ocean bottom pressure to transport variability in an eddying Southern Ocean channel model Convolutional neural network captures sub‐annual and interannual variance in both circumpolar transport and overturning strength Predicting overturning variability requires convolutional kernel to capture eddy‐induced meridional transports