Abstract. We introduce ACCESS-OM2, a new version of the ocean–sea ice model of the Australian Community Climate and Earth System Simulator. ACCESS-OM2 is driven by a prescribed atmosphere (JRA55-do) but has been designed to form the ocean–sea ice component of the fully coupled (atmosphere–land–ocean–sea ice) ACCESS-CM2 model. Importantly, the model is available at three different horizontal resolutions: a coarse resolution (nominally 1∘ horizontal grid spacing), an eddy-permitting resolution (nominally 0.25∘), and an eddy-rich resolution (0.1∘ with 75 vertical levels); the eddy-rich model is designed to be incorporated into the Bluelink operational ocean prediction and reanalysis system. The different resolutions have been developed simultaneously, both to allow for testing at lower resolutions and to permit comparison across resolutions. In this paper, the model is introduced and the individual components are documented. The model performance is evaluated across the three different resolutions, highlighting the relative advantages and disadvantages of running ocean–sea ice models at higher resolution. We find that higher resolution is an advantage in resolving flow through small straits, the structure of western boundary currents, and the abyssal overturning cell but that there is scope for improvements in sub-grid-scale parameterizations at the highest resolution.

The oceans are traversed by a large-scale overturning circulation, essential for the climate system as it sets the rate at which the deep ocean interacts with the atmosphere. The main region where deep waters reach the surface is in the Southern Ocean, where they are transformed by interactions with the atmosphere and sea-ice. Here, we present an observation-based estimate of the rate of overturning sustained by surface buoyancy fluxes in the Southern Ocean sea-ice sector. In this region, the seasonal growth and melt of sea-ice dominate water-mass transformations. Both sea-ice freezing and melting act as a pump, removing freshwater from high latitudes and transporting it to lower latitudes, driving a large-scale circulation that upwells 27 ± 7 Sv of deep water to the surface. The upwelled water is then transformed into 22 ± 4 Sv of lighter water and 5 ± 5 Sv into denser layers that feed an upper and lower overturning cell, respectively.

The Southern Ocean is a critical component of the global climate system and an important ecoregion that contains a diverse range of interdependent flora and fauna. The Southern Ocean also hosts numerous fronts: sharp boundaries between waters with different characteristics. As they strongly influence exchanges between the ocean, atmosphere and cryosphere, fronts are of fundamental importance to the climate system. However, rapid advances in physical oceanography over the past 20 years have challenged previous definitions of fronts and their response to anthropogenic climate change. Here, we review the implications of this recent research for the study of climate, ecology and biology in the Southern Ocean. We include a frontal definition "user guide" to clarify the current debate and facilitate future research. The Southern Ocean, generally defined as the global ocean south of about 35 • S that encircles the Antarctic continent, is unique oceanographic environment due to the lack of continental barriers blocking its flow and the strong winds that blow over its surface 1. At large scales, the Southern Ocean is characterised by both the intense eastward flowing Antarctic Circumpolar Current (ACC), one of the most powerful current systems on Earth, and strongly tilted isopycnals (lines of constant density) that shallow to the south. Observations of the Southern Ocean dating back to the Discovery expedition in the 1920s revealed that the transition from warmer subtropical waters to colder Antarctic waters does not occur smoothly, but is concentrated into a series of sharp transition zones, aligned generally east-west, that have come to be called fronts 2. Further observations revealed that salinity, oxygen, nutrients and various other tracers showed similar behaviour, and that between the fronts, water properties are relatively homogeneous. As such, fronts delimit the boundaries between different water-masses with distinct environmental characteristics 3. These fronts also tend to coincide with the location of narrow yet very intense currents known as "jets" 4 that dominate the ACC's flow 5. The Southern Ocean is divided by fronts into a number of distinct biophysical zones, and hence a number of distinct habitats, which in turn support distinct biota 6, 7. Numerous studies have shown that seabirds and marine mammals tend to congregate and forage in and around fronts 7. As the Earth continues to warm due to anthropogenic climate change, it is vital that we understand how these fronts and jets will respond to changes in the global climate system, and what influence that might have on associated ecosystems 8-10. Due to its remoteness and harsh climate, undertaking field studies in the Southern Ocean is both difficult and expensive. As a result, the Southern Ocean is amongst the most data-sparse of all major ocean basins, which has hindered progress on key questions regarding its dynamics and ecological communities 10. In recent decades however, a deluge of new data from satellites and Argo profiling floats, along with e...

The frontal structure of the Southern Ocean is investigated using a sophisticated frontal detection methodology, the Wavelet/Higher Order Statistics Enhancement (WHOSE) method, introduced in Chapman [2014]. This methodology is applied to 21 years of daily gridded sea-surface height (SSH) data to obtain daily maps of the locations of the fronts. By forming 'heat-maps' of the frontal occurrence frequency and then approximating these heat-maps by a superposition of simple functions, the time-mean locations of the fronts, as well as a measure of their capacity to meander, are obtained and related to the frontal locations found by previous studies.The spatial and temporal variability of the frontal structure is then considered. The number of fronts is found to be highly variable throughout the Southern Ocean, increasing ('splitting') downstream of large bathymetric features and decreasing ('merging') in regions where the fronts are tightly controlled by the underlying topography. In contrast, frontal meandering remains relatively constant. Contrary to many previous studies, little no southward migration of the fronts over the 1993-2014 time period is found, and there is only weak sensitivity to atmospheric forcing related to SAM or ENSO. The reasons for the discrepancy between this study and previous studies using contour methods are investigated and it is shown that the spatial variability of the frontal structure is not tied to the underlying sea-surface height. It is argued that the results of studies using sea-surface height contours to define front must be interpreted with care.

This study undertakes a detailed comparison of different methods used for detecting and tracking oceanic jets in the Southern Ocean. The methods under consideration are the gradient thresholding method, the probability density function (PDF) method, and the contour method. Some weaknesses of the gradient thresholding method are discussed and an enhancement (the WHOSE method), based on techniques from signal processing, is proposed. The WHOSE method is then compared to the other three methods. Quantitative comparison is undertaken using synthetic sea-surface height fields. The WHOSE method and the contour method are found to perform well even in the presence of a strong eddy field. In contrast, the standard gradient thresholding and PDF methods only perform well in high signal-to-noise ratio situations. The WHOSE, PDF, and the contour methods are then applied to data from the eddy-resolving Ocean General Circulation Model for the Earth Simulator. While the three methods are in broad agreement on the location of the main ACC jets, the nature of the jet fields they produce differ. In particular, the WHOSE method reveals a fine-scale jet field with complex braiding behavior. It is argued that this fine-scale jet field may affect the calculation of eddy diffusivities. Finally, recommendations based on this study are made. The WHOSE and gradient thresholding methods are more suitable for the study of jets as localized strong currents, useful for studies of tracer fluxes. The contour and PDF methods are recommended for studies linking jets to hydrographic fronts.

The mechanisms that initiate and maintain oceanic ''storm tracks'' (regions of anomalously high eddy kinetic energy) are studied in a wind-driven, isopycnal, primitive equation model with idealized bottom topography. Storm tracks are found downstream of the topography in regions strongly influenced by a largescale stationary meander that is generated by the interaction between the background mean flow and the topography. In oceanic storm tracks the length scale of the stationary meander differs from that of the transient eddies, a point of distinction from the atmospheric storm tracks. When the zonal length and height of the topography are varied, the storm-track intensity is largely unchanged and the downstream storm-track length varies only weakly. The dynamics of the storm track in this idealized configuration are investigated using a wave activity flux (related to the Eliassen-Palm flux and eddy energy budgets). It is found that vertical fluxes of wave activity (which correspond to eddy growth by baroclinic conversion) are localized to the region influenced by the standing meander. Farther downstream, organized horizontal wave activity fluxes (which indicate eddy energy fluxes) are found. A mechanism for the development of oceanic storm tracks is proposed: the standing meander initiates localized conversion of energy from the mean field to the eddy field, while the storm track develops downstream of the initial baroclinic growth through the ageostrophic flux of Montgomery potential. Finally, the implications of this analysis for the parameterization and prediction of storm tracks in ocean models are discussed.

Abstract. We introduce a new version of the ocean-sea ice implementation of the Australian Community Climate and Earth System Simulator, ACCESS-OM2. The model has been developed with the aim of being aligned as closely as possible with the fully coupled (atmosphere-land-ocean-sea ice) ACCESS-CM2. Importantly, the model is available at three different horizontal resolutions: a coarse resolution (nominally 1° horizontal grid spacing), an eddy-permitting resolution (nominally 0.25°) and an eddy-rich resolution (0.1° with 75 vertical levels), where the eddy-rich model is designed to be incorporated into the Bluelink operational ocean prediction and reanalysis system. The different resolutions have been developed simultaneously, both to allow testing at lower resolutions and to permit comparison across resolutions. In this manuscript, the model is introduced and the individual components are documented. The model performance is evaluated across the three different resolutions, highlighting the relative advantages and disadvantages of running ocean-sea ice models at higher resolution. We find that higher resolution is an advantage in resolving flow through small straits, the structure of western boundary currents and the abyssal overturning cell, but that there is scope for improvements in sub-grid scale parameterisations at the highest resolution.

In this letter a new method based on modified selforganizing maps is presented for the reconstruction of deep ocean current velocities from surface information provided by satellites. This method takes advantage of local correlations in the data-space to improve the accuracy of the reconstructed deep velocities. Unlike previous attempts to reconstruct deep velocities from surface data, our method makes no assumptions regarding the structure of the water column, nor the underlying dynamics of the flow field. Using satellite observations of surface velocity, sea-surface height and sea-surface temperature, as well as observations of the deep current velocity from autonomous Argo floats to train the map, we are able to reconstruct realistic high-resolution velocity fields at a depth of 1000m. Validation reveals extremely promising results, with a speed root mean squared error of ∼2.8cm. −1 , a factor more than a factor of two smaller than competing methods, and direction errors consistently smaller than 30 • . Finally, we discuss the merits and shortcomings of this methodology and its possible future applications.