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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‐observedWe use an ocean state estimate to test the feasibility of inferring the MOC based solely on satellite observationsA unified machine learning methodology shows high skill in MOC reconstruction as a function of latitude and basin [ABSTRACT FROM AUTHOR]

Surface winds around the Antarctic continent control coupled ocean‐ice processes that influence the climate system, including bottom water production, heat transport onto the continental shelf and sea ice coverage. However, few studies have examined projected changes in these winds, even though it would aid in the interpretation and understanding of the ocean's response to climate change. Using Coupled Model Intercomparison Project Phase 6 and reanalysis data, we show a significant reduction in the near‐Antarctic surface winds throughout the historical period that continues until the end of the twenty‐first century, amounting to 23% and 7% for the easterly and southerly wind components respectively under the high emission scenario. The most intense weakening happens during the summer season. We find that the weakening is coherent with the trend toward a positive Southern Annular Mode and a reduction of the pole‐to‐coast meridional pressure gradient, which we term Antarctic Annular Index. Plain Language Summary: Surface winds over the ocean around the Antarctic continent influence several aspects of the oceanic circulation and sea ice in the region that become relevant in the context of climate change. For example, Antarctic coastal surface winds have been found to drive the warming experienced in some regions that subsequently triggers increased ice shelf melt. However, there is little understanding regarding how this wind regime is expected to change in the future, with most research focusing on the mid‐latitude westerlies. In this work, we use Coupled Model Intercomparison Project Phase 6 models to quantify projected changes in these winds to the end of the twenty‐first century, hoping that it will aid in the interpretation of the ocean's response to climate change. Under the high emission scenario, we find a significant weakening of 23% for the easterly wind component and 7% for the meridional wind component. This weakening can be partly explained by a large‐scale pattern of change in sea level pressure that reflects in an increase of the atmospheric mode of variability known as the Southern Annular Mode, and a decrease of the pole‐to‐coast surface pressure gradient, which we term Antarctic Annular Index. Key Points: Coupled Model Intercomparison Project Phase 6 models show a weakening of the near‐Antarctic surface winds during the period 1979–2015Future projections in CMIP6 models show that the weakening trend continues until the end of the twenty‐first centuryWeakened winds are associated with a more positive Southern Annular Mode and a reduction in the pole‐to‐coast meridional pressure gradient [ABSTRACT FROM AUTHOR]

The flow of tides over rough bathymetry in the deep ocean generates baroclinic motion including internal waves and bottom‐trapped tides. The stresses generated by this motion feedback on the amplitude and phase of the large‐scale tide. Quantifying the stresses associated with tidal flow over abyssal hills is especially important, as this scale of bathymetry is often unresolved in global baroclinic tide models, and the stresses must therefore be parameterized. Here, we extend the previous theoretical work of the authors to determine the amplitude, phasing, and vertical location of the stresses exerted on a flow driven by a time‐periodic body force when it encounters rough bathymetry. The theory compares favorably with a suite of fully nonlinear numerical simulations. It is shown that all topographic stresses are applied directly above the bathymetry, leading to a two‐layer baroclinic flow, with the near‐bottom spatial‐mean flow (the benthic tide) strongly modified by topographic stresses, and the flow at height unperturbed by the presence of topography. Our results provide a framework to improve baroclinic tide models by (i) providing a simple parameterization for the subinertial stress which is currently not included in any models, (ii) establishing that parameterized stresses should be applied in the diffusive boundary layer directly above the topography, independent of where internal tides may dissipate, and (iii) identifying a minimum resolution of ∼10 km for baroclinic tidal models to adequately capture wave resonance effects that can significantly impact the magnitude of the benthic tide. Plain Language Summary: The ocean tide is a periodic motion of the water column at the scale of ocean basins. The amplitude of the ocean tide is determined by a balance between the gravitational attraction of the moon and the forces exerted when the tide flows over the rough seafloor. Much of the roughness in the deep ocean is due to mountains on the seafloor, 10–50 km in width, known as "abyssal hills." In this study, mathematical descriptions are developed for the strength and distribution of the forces exerted on the ocean tide due to its interaction with these hills. These forces always act below the crest of the hills, leading to a sub‐crest or "benthic tide" that differs from the tide above the crest of the hills. Our results provide a framework for improving the representation of tides in numerical ocean models. Key Points: The interaction of the spatial‐mean tide with rough bathymetry generates baroclinic motion including internal tidesThese motions exert stresses on the spatial‐mean tide near the seafloor which modifies the benthic tidal amplitudeThe benthic tidal amplitude may be decreased or increased depending on the nature of the interaction [ABSTRACT FROM AUTHOR]