Most of the ocean's kinetic energy is contained within the mesoscale eddy field. Models that do not resolve these eddies tend to parameterize their impacts such that the parameterized transport of buoyancy and tracers reduces the large-scale available potential energy and spreads tracers. However, the parameterizations used in the ocean components of current generation Earth System Models (ESMs) rely on an assumption of a flat ocean floor even though observations and high-resolution modelling show that eddy transport is sensitive to the potential vorticity gradients associated with a sloping seafloor. We show that buoyancy transport coefficient diagnosed from idealized eddy-resolving simulations is indeed reduced over both prograde and retrograde bottom slopes (topographic wave propagation along or against the mean flow, respectively) and that the reduction can be skilfully captured by a mixing length parameterization by introducing the topographic Rhines scale as a length scale. This modified 'GM' parameterization enhances the strength of thermal wind currents over the slopes in coarse-resolution, non-eddying, simulations. We find that in realistic global coarse-resolution simulations the impact of topography is most pronounced at high latitudes, enhancing the mean flow strength and reducing temperature and salinity biases. Reducing the buoyancy transport coefficient further with a mean-flow dependent eddy efficiency factor, has notable effects also at lower latitudes and leads to reduction of global mean biases.

Antarctic Bottom Water (AABW) forms the deepest limb of the meridional overturning circulation (MOC) and is a key control on global exchanges of heat, freshwater, and carbon. Density differences that drive the MOC have their origin, in part, in coastal polynyas. Prydz Bay polynyas in East Antarctica are a key source of Dense Shelf Water (DSW) that feeds AABW to the Atlantic and Indian Oceans. However, several poorly understood mechanisms influence the pathways and change water mass properties of the DSW on its way to the abyss. To better understand these mechanisms, we release Lagrangian particles in a 10 km resolution simulation of the Whole Antarctic Ocean Model and analyze the resulting tracks using novel cluster analysis. Our results highlight the role of mixing with other water masses on the shelf in controlling the fate of DSW and its eventual contribution to AABW. When advected beneath the ice shelf, DSW can mix with fresh Ice Shelf Water (ISW), becoming less dense and making future AABW formation less likely. This study confirms that towards the shelf break along the Antarctic Slope Current, mixing with circumpolar deep water (CDW) forms modified circumpolar deep water (mCDW) and influences DSW export as AABW. Our findings indicate that the pathway from DSW to AABW is sensitive to mixing with ambient waters on the shelf. An important implication is that with future increase in ice shelf melt and CDW warming, AABW production is likely to decline, even if DSW production in coastal polynyas remains constant.

The Barents Sea attracts year-around human activity as the winter sea ice cover retreats, creating a need for short and long term prediction of environmental conditions in the region. Previous studies have shown that local ocean heat content and heat transport at the Barents Sea Opening provide interannual to decadal predictability of Barents Sea ice cover. Part of this predictability is suggested to originate from thermodynamic anomalies propagating along the Norwegian Atlantic Current. To better understand this source of predictability, and the relevant timescales, we use models (Coupled Model Intercomparison Project Phase 6; CMIP6) and satellite observations, to study the linear response of the monthly mean Barents Sea ice cover to downstream sea surface temperature anomalies. We show that in March the sea ice response is strongest on short lead times (<2 year), vanishing towards ~7 year timescale and that the linear sea ice response function can be reconstructed using an advective-diffusive ‘leaky-pipe’ model with multiple propagation timescales. The sea surface temperature based sea ice predictability is linked to decadal and longer timescale variability. Our results also show that sea surface temperatures close to the sea ice edge provide the best predictability at short timescales, but with a skill that approaches that of the sea surface temperatures further away at long timescales.