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Abstract The Southern Ocean is a region of high surface nutrient content, reflecting an inefficient biological carbon pump. The variability, predictability, and causes of changes in these nutrient levels on interannual to decadal time scales remain unclear. We employ a deep learning approach, specifically a Temporal Convolution Attention Neural Network (TCANN), to conduct multi‐year forecasting of surface based on oceanic physical drivers. The TCANN successfully replicates testing data with a prediction skill extending to at least 4 years with the GFDL‐ESM4‐driven model and 1 year with the observation‐driven model. To benchmark the results, we compare the prediction skill of TCANN with a simple persistence model and two regression methods, a linear regression and a ridge regression. The TCANN model was able to predict variability with a higher skill than persistence and the two regression methods indicating that non‐linearities present in the system become too high to predict inter‐annual variability with traditional regression methods. To enhance the interpretability of the predictions, we explore three explainable AI techniques: occlusion analysis, integrated gradients, and Gradient Shap. The outcomes suggest a crucial role played by salinity processes and buoyancy/potential density fluxes on the prediction of on annual time scales. The deep learning tools' ability to provide skillful forecasts well into the future presents a promising avenue for gaining insights into how the Southern Ocean's surface nutrients respond to climate change based on physical quantities. 

Abstract Water Mass Transformation (WMT) theory provides conceptual tools that in principle enable innovative analyses of numerical ocean models; in practice, however, these methods can be challenging to implement and interpret, and therefore remain under‐utilized. Our aim is to demonstrate the feasibility of diagnosing all terms in the water mass budget and to exemplify their usefulness for scientific inquiry and model development by quantitatively relating water mass changes, overturning circulations, boundary fluxes, and interior mixing. We begin with a pedagogical derivation of key results of classical WMT theory. We then describe best practices for diagnosing each of the water mass budget terms from the output of Finite‐Volume Generalized Vertical Coordinate (FV‐GVC) ocean models, including the identification of a non‐negligible remainder term as the spurious numerical mixing due to advection scheme discretization errors. We illustrate key aspects of the methodology through the analysis of a polygonal region of the Greater Baltic Sea in a regional demonstration simulation using the Modular Ocean Model v6 (MOM6). We verify the convergence of our WMT diagnostics by brute‐force, comparing time‐averaged (“offline”) diagnostics on various vertical grids to timestep‐averaged (“online”) diagnostics on the native model grid. Finally, we briefly describe a stack of xarray‐enabled Python packages for evaluating WMT budgets in FV‐GVC models (culminating in the newxwmbpackage), which is intended to be model‐agnostic and available for community use and development. 

Abstract Density-driven steric seawater changes are a leading-order contributor to global mean sea level rise. However, intermodel differences in the magnitude and spatial patterns of steric sea level rise exist at regional scales and often emerge during the spinup and preindustrial control integrations of climate models. Steric sea level results from an eddy-permitting climate model, GFDL CM4, are compared with a lower-resolution counterpart, GFDL-ESM4. The results from both models are examined through basin-scale heat budgets and watermass analysis, and we compare the patterns of ocean heat uptake, redistribution, and sea level differ in ocean-only [i.e., Ocean Model Intercomparison Project (OMIP)] and coupled climate configurations. After correcting for model drift, both GFDL CM4 and GFDL-ESM4 simulate nearly equivalent ocean heat content change and global sea level rise during the historical period. However, the GFDL CM4 model exhibits as much as a 40% increase in surface ocean heat uptake in the Southern Ocean and subsequent increases in horizontal export to other ocean basins after bias correction. The results suggest regional differences in the processes governing Southern Ocean heat export, such as the formation of Antarctic Intermediate Water (AAIW), Subpolar Mode Water (SPMW), and gyre transport between the two models, and that sea level changes in these models cannot be fully bias-corrected. Since the process-level differences between the two models are evident in the preindustrial control simulations of both models, these results suggest that the control simulations are important for identifying and correcting sea level–related model biases. 

Abstract West Antarctic Ice Sheet mass loss is a major source of uncertainty in sea level projections. The primary driver of this melting is oceanic heat from Circumpolar Deep Water originating offshore in the Antarctic Circumpolar Current. Yet, in assessing melt variability, open ocean processes have received considerably less attention than those governing cross-shelf exchange. Here, we use Lagrangian particle release experiments in an ocean model to investigate the pathways by which Circumpolar Deep Water moves toward the continental shelf across the Pacific sector of the Southern Ocean. We show that Ross Gyre expansion, linked to wind and sea ice variability, increases poleward heat transport along the gyre’s eastern limb and the relative fraction of transport toward the Amundsen Sea. Ross Gyre variability, therefore, influences oceanic heat supply toward the West Antarctic continental slope. Understanding remote controls on basal melt is necessary to predict the ice sheet response to anthropogenic forcing. 

Abstract The Weddell Gyre mediates carbon exchange between the abyssal ocean and atmosphere, which is critical to global climate. This region also features large and highly variable freshwater fluxes due to seasonal sea ice, net precipitation, and glacial melt; however, the impact of these freshwater fluxes on the regional carbon cycle has not been fully appreciated. Using a novel budget analysis of dissolved inorganic carbon (DIC) mass in the Biogeochemical Southern Ocean State Estimate, we highlight two freshwater‐driven transports. Where freshwater with minimal DIC enters the ocean, it displaces DIC‐rich seawater outwards, driving a lateral transport of 75 ± 5 Tg DIC/year. Additionally, sea ice export requires a compensating import of seawater, which carries 48 ± 11 Tg DIC/year into the gyre. Though often overlooked, these freshwater displacement effects are of leading order in the Weddell Gyre carbon budget in the state estimate and in regrouped box‐inversion estimates, with implications for evaluating basin‐scale carbon transport.