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The Earth's crust is grinding to life, releasing deadly volcanoes and bizarre creatures... so humanity's first instinct is to blame Atlantis! And as the plates pull apart, the pressures of ruling a kingdom under siege are weighing on Aquaman and Mera as well!

The Southern Hemisphere cryosphere has recently shown regionally-contrasted responses to climate change, in particular to the positive phases of the Southern Annular Mode. However, the understanding of the impacts of this mode on ice-shelf basal melt at a circum-Antarctic scale is still limited. Here, we performed idealized experiments with a pan-Antarctic regional ice-shelf cavity-resolving ocean—sea-ice model for different phases of the Southern Annular Mode. We show that positive phases lead to increased upwelling and subsurface ocean temperature and salinity close to ice shelves, while the opposite occurs for negative phases. A one-standard-deviation increase of the Southern Annular Mode leads to a net basal mass loss of 40 Gt yr −1 , with strong regional contrasts: increased ice-shelf basal melt in the Bellingshausen and Western Pacific sectors and the opposite response in the Amundsen sector. Estimates of 1000–1200 and 2090–2100 ice-shelf basal melt changes due to the Southern Annular Mode are −86.6 Gt yr −1 and 55.0 to 164.9 Gt yr −1 , respectively, compared to the present.

We introduce PARASO, a novel five-component fully coupled regional climate model over an Antarctic circumpolar domain covering the full Southern Ocean. The state-of-the-art models used are the fast Elementary Thermomechanical Ice Sheet model (f.ETISh) v1.7 (ice sheet), the Nucleus for European Modelling of the Ocean (NEMO) v3.6 (ocean), the Louvain-la-Neuve sea-ice model (LIM) v3.6 (sea ice), the COnsortium for Small-scale MOdeling (COSMO) model v5.0 (atmosphere) and its CLimate Mode (CLM) v4.5 (land), which are here run at a horizontal resolution close to 1/4∘. One key feature of this tool resides in a novel two-way coupling interface for representing ocean–ice-sheet interactions, through explicitly resolved ice-shelf cavities. The impact of atmospheric processes on the Antarctic ice sheet is also conveyed through computed COSMO-CLM–f.ETISh surface mass exchange. In this technical paper, we briefly introduce each model's configuration and document the developments that were carried out in order to establish PARASO. The new offline-based NEMO–f.ETISh coupling interface is thoroughly described. Our developments also include a new surface tiling approach to combine open-ocean and sea-ice-covered cells within COSMO, which was required to make this model relevant in the context of coupled simulations in polar regions. We present results from a 2000–2001 coupled 2-year experiment. PARASO is numerically stable and fully operational. The 2-year simulation conducted without fine tuning of the model reproduced the main expected features, although remaining systematic biases provide perspectives for further adjustment and development.

We coupled together high-resolution versions of the ocean–sea ice model NEMO and the ice sheet model BISICLES configured to the Totten Glacier area and ran a series of simulations over the recent past (1995–2014) and under warming conditions (2081–2100; SSP4-4.5) with NEMO in stand-alone mode and with the coupled model to assess the effects of the coupling. During the recent past, the ocean–ice sheet coupling has increased the time-averaged value of the basal melt rate in both the Totten and Moscow University ice shelf cavities by 6.7% and 14.2%, respectively. The relationship between the changes in ice shelf thickness and ice shelf basal melt rate suggests that the effect of the coupling is not a linear response to the melt rate but rather a more complex response, driven partly by the dynamical component of the ice sheet model. The response of the ice sheet–ocean coupling due to the ocean warming is a 10% and 3% basal melt rate decrease in the Totten and Moscow University ice shelf cavities, respectively. This indicates that the ocean–ice sheet coupling under climate warming conditions dampens the basal melt rates. Our study highlights the importance of incorporating ocean–ice sheet coupling in climate simulations, even over short time periods.

In the field of bio-engineering, there is a need for a specialized manipulator that protect targets from hard physical contact. The solution proposed in this paper is a system that controls micro flows to manipulate a micro-sized bio-target. The manipulation principle and system structure are presented. In addition, a simple model that uses physically observable parameters is constructed to capture the flow-target interactions following a chemically assisted flow visualization. The experimental results of a prototype are presented, and the feasibility is discussed. The purpose of this paper is to prove the feasibility of this manipulation method. Further developments are introduced, highlighting the full potential of the prototype.

In this paper, we present a global-in-time non-overlapping Schwarz method applied to the Ekman boundary layer problem. Such a coupled problem is representative of large-scale atmospheric and oceanic flows in the vicinity of the air-sea interface. Schwarz waveform relaxation (SWR) algorithms provide attractive methods for ensuring a “tight coupling” between the ocean and the atmosphere. However, the convergence study of such algorithms in this context raises a number of challenges. Numerous convergence studies of Schwarz methods have been carried out in idealized settings, but the underlying assumptions to make these studies tractable may prohibit them to be directly extended to the complexity of climate models. We illustrate this aspect on the coupled Ekman problem, which includes several essential features inherent to climate modeling while being simple enough for analytical results to be derived. We investigate its well-posedness and derive an appropriate SWR algorithm. Sufficient conditions for ensuring its convergence for different viscosity profiles are then established. Finally, we illustrate the relevance of our theoretical analysis with numerical results and suggest ways to improve the computational cost of the coupling. Our study emphasizes the fact that the convergence properties can be highly sensitive to some model characteristics such as the geometry of the problem and the use of continuously variable viscosity coefficients.

Accurate weather and climate forecasting relies heavily on the precise modeling of sea ice, a critical component of the Earth's climate system. Sea ice influences global weather patterns, ocean circulation, and the exchange of heat and moisture between the atmosphere and oceans. Initialisation of the sea ice component of global coupled models relies on data assimilation techniques to incorporate information from observations to constrain the system.

The seasonal cycle of the Antarctic sea ice extent is strongly asymmetric, with a relatively slow increase after the summer minimum followed by a more rapid decrease after the winter maximum. This cycle is intimately linked to the seasonal cycle of the insolation received at the top of the atmosphere, but sea ice processes as well as the exchanges with the atmosphere and ocean may also play a role. To quantify these contributions, a series of idealized sensitivity experiments have been performed with an eddy-permitting (∘) NEMO-LIM3 (Nucleus for European Modelling of the Ocean–Louvain-la-Neuve sea ice model version 3) Southern Ocean configuration, including a representation of ice shelf cavities, in which the model was either driven by an atmospheric reanalysis or coupled to the COSMO-CLM2 regional atmospheric model. In those experiments, sea ice thermodynamics and dynamics as well as the exchanges with the ocean and atmosphere are strongly perturbed. This perturbation is achieved by modifying snow and ice thermal conductivities, the vertical mixing in the ocean top layers, the effect of freshwater uptake and release upon sea ice growth and melt, ice dynamics, and surface albedo. We find that the evolution of sea ice extent during the ice advance season is largely independent of the direct effect of the perturbation and appears thus mainly controlled by initial state in summer and subsequent insolation changes. In contrast, the melting rate varies strongly between the experiments during the retreat, in particular if the surface albedo or sea ice transport are modified, demonstrating a strong contribution of those elements to the evolution of ice coverage through spring and summer. As with the advance phase, the retreat is also influenced by conditions at the beginning of the melt season in September. Atmospheric feedbacks enhance the model winter ice extent response to any of the perturbed processes, and the enhancement is strongest when the albedo is modified. The response of sea ice volume and extent to changes in entrainment of subsurface warm waters to the ocean surface is also greatly amplified by the coupling with the atmosphere.

Societal adaptation to rising sea levels requires robust projections of the Antarctic Ice Sheet's retreat, particularly due to ocean-driven basal melting of its fringing ice shelves. Recent advances in ocean models that simulate ice-shelf melting offer an opportunity to reduce uncertainties in ice–ocean interactions. Here, we compare several community-contributed, circum-Antarctic ocean simulations to highlight inter-model differences, evaluate agreement with satellite-derived melt rates, and examine underlying physical processes. All but one simulation use a melting formulation depending on both thermal driving (T⋆) and friction velocity (u⋆), which together represent the thermal and ocean current forcings at the ice–ocean interface. Simulated melt rates range from 650 to 1277 Gt yr−1 (m=0.45-0.91 m yr−1), driven by variations in model resolution, parameterisations, and sub-ice shelf circulation. Freeze-to-melt ratios span 0.30 % to 30.12 %, indicating large differences in how refreezing is represented. The multi-model mean (MMM), produces an averaged melt rate of 0.64 m yr−1 from a net mass loss of 843 Gt yr−1 (876 Gt yr−1 melting and 33 Gt yr−1 refreezing), yielding a freeze-to-melt ratio of 3.92 %. We define a thermo-kinematic melt sensitivity, ζ=m/(T⋆u⋆)=4.82×10-5 °C−1 for the MMM, with individual models spanning 2.85×10-5 to 19.4×10-5 °C−1. Higher melt rates typically occur near grounding zones where both T⋆ and u⋆ exert roughly equal influence. Because friction velocity is critical for turbulent heat exchange, ice-shelf melting must be characterised by both ocean energetics and thermal forcing. Further work to standardise model setups and evaluation of results against in situ observations and satellite data will be essential for increasing model accuracy, reducing uncertainties, to improve our understanding of ice-shelf–ocean interactions and refine sea-level rise predictions.

The Climate Change Adaptation Digital Twin (Climate DT), developed as part of the European Commission's Destination Earth (DestinE) initiative, sets up an operational system for producing multi-decadal, multi-model global climate projections and translating climate data into climate impact information to support adaptation efforts. This system delivers data with local granularity at spatial resolutions of 5–10 km and hourly outputs, leading to globally consistent information at scales that matter for decision-making. It also enables the testing of what-if scenarios such as high-resolution storylines, which are physically consistent global simulations of extreme events under different climate conditions and provide contextual insights to support concrete adaptation decisions. They support the generation of more equitable (understood as accessible and relevant across regions) climate information. The Climate DT is built on cutting-edge infrastructure, expert collaboration, and digital innovation. It is designed to support on-demand responses to policy questions, with quantified uncertainty. It will foster interactivity by allowing users to influence simulation design, model output portfolios, and application integration through co-design. AI-based tools, including emulators and chatbots, are being developed in parallel to enhance climate information access. Sector-specific applications are embedded in the system to synchronously translate climate data into tailored climate-impact indicators, with examples provided for energy, water, and forest management. The applications have been co-designed with informed users. A unified, cross-platform workflow defines the orchestration of all components, which is handled by a single workflow manager and relies on containerised components, facilitating automation, portability, maintainability, and traceability. Data management is unified using standard grids (HEALPix), ensuring consistency and easing data usability under a strict governance policy. Streaming enables real-time data use by the data consumers and unlocks access to the unprecedented data wealth produced by the high-resolution simulations. Monitoring tools provide real-time quality control of data and model outputs and enable continuous assessment of the realism of the climate simulations during Climate DT operation. The compute-intensive system is powered by world-class supercomputing capabilities through a strategic partnership with the European High Performance Computing Joint Undertaking (EuroHPC). Despite high computational demands, the Climate DT sets a new benchmark for delivering equitable, credible, and actionable climate information. It complements existing initiatives like CMIP, CORDEX, and national and European climate services, and aligns with global climate science goals to support climate adaptation.