The Late Pliocene, particularly the Marine Isotope Stage KM5c (3.205 Ma BP) has been increasingly proposed as an analog to future climate change, especially considering changes in the hydrological cycle, monsoon systems, and atmospheric and ocean warming above Pre-Industrial (1850 CE) and historical levels. The Pliocene Modeling Intercomparison Project (PlioMIP), now in its third phase (PlioMIP3), seeks to explore climate of the Pliocene based on a combination of climate model simulations and proxy data reconstructions. One of its goals is also to assess the analogy between past and future climates and to quantify climate sensitivity to Pliocene boundary conditions. This work shall help to improve climate models and their application for both past and future warm climates and to provide a paleoclimate-informed assessment of uncertainties in modeled warm climates. With this manuscript we present the PlioMIP3 core simulations for the pre-industrial control (PI) and the Late Pliocene (LP) based on the AWI Climate Model, Version 3 (AWI-CM3). This represents the first application of AWI-CM3 at tectonic timescales which necessitates more extensive adjustment of model setups than the application for recent climate. We therefore take advantage of the opportunity to also document more generally the methods we devised to generate AWI-CM3 model setups for paleoclimate research under geographies that differ from the modern reference state. AWI-CM3 simulates a Late Pliocene climate that is about 4 degrees C warmer than the pre-industrial reference, with land warming exceeding ocean warming by a factor of 1.2. Polar amplification is particularly pronounced, with Antarctic surface air temperature anomalies exceeding 6 degrees C while Arctic anomalies reach 4 degrees C to 5 degrees C. In comparison to the previous PlioMIP2, this places AWI-CM3 among the warmer ensemble members, consistent with a relatively high equilibrium climate sensitivity of similar to 4 degrees C. Our simulations also display an intensified hydrological cycle, with global mean precipitation increasing by 0.31 mmd-1. The ocean surface warms globally to about 3.06 degrees C, accompanied by contrasting salinity trends, with salinization of the North Atlantic (+3 PSU) and freshening of the Arctic (-2.5 PSU) and Indian (-1 PSU) Oceans. Additionally, the meridional overturning circulation (MOC) reorganizes, with the Atlantic MOC strengthening by about 8 Sv, the Pacific MOC remaining inactive, and the global Antarctic Bottom Water cell being substantially reduced (11 Sv weaker relative to PI). We find reduced global sea-ice extent, that is halved with respect to PI in the Southern Hemisphere, and enhanced northward ocean heat transport in the North Atlantic. Overall, AWI-CM3 reproduces the large-scale climate features of the Late Pliocene inferred from proxy records and the PlioMIP2 ensemble, while highlighting key ocean-atmosphere feedbacks shaping this warm climate.

We present FESOM2-JAX, a Python re-implementation of the Finite-volumE Sea ice-Ocean Model (FESOM2) in JAX. The model retains the unstructured-mesh, cell-vertex finite-volume formulation of the original, runs unchanged from a laptop CPU to 256 GPUs, and is end-to-end differentiable. FESOM2-JAX is a code shadow of the Fortran model: a projection onto the Python ecosystem, translated with large language models and verified kernel by kernel against the original. It is built to lower the barrier to experimentation, from new numerics and parameterizations to gradient-based calibration and hybrid physics-machine-learning components, while remaining close enough to the original so that what is developed in the shadow can be transferred back. In a 1958-2019 hindcast at 1^∘ equivalent resolution with identical physics and forcing, the mean states of the JAX and Fortran versions differ from each other by two orders of magnitude less than either differs from observations, and the two runs agree for six decades in global temperature, salinity, heat content, and sea ice. The complete 1^∘ configuration fits on a single GPU, a node of four GH200 superchips integrates ∼113 simulated years per wall-clock day, and meshes of up to 7.4 million surface vertices (∼5 km) scale to 128 GPUs. What limits the model is communication rather than arithmetic. What the shadow adds to the original is the gradient: a single reverse-mode pass through the full time loop returns the sensitivity of a model diagnostic to a parameter at every mesh vertex, verified against finite differences. To our knowledge, FESOM2-JAX is the first global ocean-sea-ice model of CMIP-class complexity written natively in a differentiable framework, and the first on an unstructured mesh.

Abstract. We present novel centennial-scale global climate simulations at kilometre-scale resolution utilizing the coupled IFS-FESOM model, featuring a 9 km atmosphere and a minimal 5 km ocean. Following the HighResMIP protocol, a 50-year high-resolution coupled spin-up was conducted, which was followed by a 65-year historical simulation (1950–2014) and a scenario simulation (SSP2-4.5, 2015-2050). This was accompanied by a 100-year control simulation (1950–2050) employing the 1950 radiative forcing. These simulations explicitly resolve ocean mesoscale eddies within a long-term climate context. Overall, the model demonstrates an improved mean climate state compared to CMIP6 models, with a notable reduction in persistent model biases, except for the polar regions. Performance metrics reveal reduced global errors in surface temperature, winds, and cloud formations. The very high-resolution ocean captures eddy-rich dynamics and realistic boundary current variability, contributing to an improved sea surface salinity patterns and a strengthened Atlantic Meridional Overturning Circulation (peak ~20 Sv). The simulation also reproduces internal climate variability with high fidelity, notably a realistic El Niño–Southern Oscillation with the desired quasi-periodicity (~4–5 years) and realistic winter teleconnection patterns. Sea ice and high-latitude biases have been identified as the primary remaining challenges: the model overestimates the extent of Arctic sea ice, resulting in a cold bias in the Northern high latitudes, while an initialization error in Antarctic snow cover induces a warm bias over Antarctica. Furthermore, there is a warm bias over the Weddell Sea with high ocean mix layer depth, associated with a winter devoid of sea ice. Despite persistent sea-ice and high-latitude biases, the coupled system remains stable over centennial time scales with minimal long-term drift. These results demonstrate the feasibility and scientific value of global coupled climate simulations operating in the ocean eddy-rich regime at sub-10 km resolution. The IFS–FESOM kilometre-scale configuration thus represents a significant step forward in the development of next-generation Earth system models that robustly bridge global climate dynamics and regional-scale processes over multi-decadal to centennial periods.

Large language models (LLMs) can translate and modify source code, and have been shown to do so for codes of different complexity. Whether they can port a complete, production geophysical model to a different language without degrading its physics has not been established. We demonstrate that LLM-assisted code translation can preserve the physics of a complete production ocean model while moving it into a modern performance-portable form. We report our experience using an agentic LLM coding assistant, directed by domain experts, to port the FESOM2 unstructured mesh ocean–sea-ice model (about 74000 lines of core Fortran) first to C and then to C++/Kokkos for performance portability across CPUs and GPUs. We describe the practices that proved necessary, what worked and what did not, and the failure modes that we encountered. Three practices mattered most: translating in two stages that separate reproducing the numerics (Fortran to a clean C reference) from introducing parallelism (C to Kokkos); requiring a strictly literal translation in which the assistant was not permitted to “improve” the source; and validating each stage against an acceptance criterion suited to it. The C port reproduces the original Fortran at the level of long-term simulation statistics over five years. The Kokkos port is bit-for-bit identical to the C reference on CPU and statistically close on GPU over multi-year runs. On eddy-rich meshes up to 7.4 million surface vertices a single A100 GPU node runs 1.6–3.7 times faster than a CPU node, reaching the 1-2 simulated-years-per-day required for production integrations. The result is more than a single GPU port: by following a clear validation procedure, an LLM moved a full Fortran ocean model into another language and onto accelerators while preserving its physics in a matter of weeks.

Effective climate adaptation benefits from detailed, actionable information on how specific extreme events are influenced by climate change. Here we present the first global, kilometre-scale coupled modelling framework that enables counterfactual reconstructions of recent weather events, including extremes, in different climates. The system is built on the IFS–FESOM model and applies scale-selective spectral nudging of the large-scale atmospheric circulation to ERA5 while allowing atmospheric small-scale dynamics and thermodynamic processes as well as the land surface, ocean, and sea ice to evolve freely across contrasting climate backgrounds. This enables the replay of recent events across different climate states, including the 1950s, present-day conditions, and a +2 K warmer climate. We demonstrate the system's skill in reproducing the observed variability on daily and longer timescales during the period 2017--2024, particularly in the extratropics. Furthermore, we evaluate its performance using high-quality observations, including data from the MOSAiC expedition. We further present climate change storylines for a European heatwave in July 2019 and a major European flooding event in September 2024, Storm Boris. We thereby demonstrate how the use of kilometre-scale resolution captures local-scale intensification with local granularity, including details missed by coarser models. This framework forms a core operational component of the EU’s Destination Earth Climate Digital Twin, enabling scalable, high-resolution, circulation-constrained climate storylines for science and decision-making.

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.

Within the EU’s Destination Earth (DestinE) initiative we are developing a digital climate twin with km-scale resolution. This enables us to resolve physical processes that, so far, have only been represented by approximations. This core model setup (called digital twin engine) is able to run multidecadal simulations for historic periods as well as different future scenarios in unprecedented resolution which will be used by decision makers.In phase one of DestinE, our goal is to run a control simulation (under 1950 pre industrial conditions), a historic simulation from 1990 to 2020 and finally, projection simulations from 2020 to 2040. The control run will be performed with a global atmospheric resolution of 9km, while the projection simulations use 4km. The ocean component uses the unstructured NG5 mesh, which means an approximate resolution of 5km.In this work we present the latest iteration of the IFS-FESOM model, the Integrated Forecasting System coupled to the Finite volumE Sea Ice-Ocean Model FESOM2. We explain its components and recent improvements, including the integration of ECMWF’s IO-server and post processing toolkit multio into the FESOM2 component and the introduction of a novel runoff mapper. Preliminary results from our kilometre-scale simulations are shown and compared to preindustrial conditions, with the primary objective to quantify effects of a ~1K warming world.

The Atlantic Meridional Overturning Circulation (AMOC) plays a crucial role in shaping the global climate system by redistributing heat and influencing large-scale climate patterns. Utilizing the AWI-CM3 model, we investigate the AMOC sensitivity to an abrupt climate change scenario (abrupt-4xCO2) with respect to pre-industrial climate (PI), comparing the AMOC diagnosed in depth (z-AMOC) and density (ρ-AMOC) space. Water mass transformations are assessed to analyze the impact of background climate on surface-forced and interior-mixing-induced transformations. We find that both the location and magnitude of AMOC maximum are directly affected by the framework choice. In PI, the ρ-AMOC maximum is substantially stronger than that of the z-AMOC, while at 26° N the two diagnostics are nearly equivalent. Consequently, the variability of the z-AMOC maximum correlates only with that at 26° N, reflecting isopycnal flattening into constant depth levels in the subpolar North Atlantic inherent to these diagnostics. Strong AMOC weakening is observed under 4xCO2 forcing in both frameworks until simulation year 75. Subsequently, both diagnostics reveal a weaker AMOC with an approximate strength of 7.1 Sv, although with z-AMOC displaying a slight recover towards the end of the simulation and ρ-AMOC oscillating steadily around 5 Sv. At 26° N, variability patterns remain comparable to PI, albeit with an additional ρ-AMOC weakening of approximately 2 Sv, indicating divergence between the representation of AMOC dynamics in the subtropical Atlantic within both frameworks in comparison to PI. The diagnostics in density space allow for the attribution of this further ρ-AMOC weakening to increased entrainment of fresher overflows from amplified GIN seas overturning and reduced deep convection in the Labrador and Irminger Seas. In contrast, the diagnostics in depth space only reveals reduced downwelling around the southwestern Greenland coast and along the path of the Gulf Stream, features that are more challenging to evaluate against available observations. Thus, the comparison between z-AMOC and ρ-AMOC indicates that diagnosing the AMOC in density space provides more physically meaningful information regarding the state of the water mass transformations and their contribution to ocean circulation regimes across the entire Atlantic basin, not only the subpolar North Atlantic, and especially as the climate continues to warm. These findings emphasize the importance of diagnosing AMOC in density space to better understand water mass transformations, which are concealed in depth space and to capture AMOC variability in warmer climates, across all latitudes.

Efforts to enhance climate model simulations by achieving higher resolutions to explicitly capture sub-grid scale processes constitute a central objective in contemporary climate modeling. In this pursuit, our focus is on resolving a pivotal element of the climate system—the ocean meso-scale eddies. At the Alfred-Wegener-Institute, we are working towards this objective by employing the ocean-sea ice model FESOM at approximately 5km horizontal resolution (NG5), coupled with the atmospheric model IFS at a 9km horizontal resolution (tco1279). This presentation showcases preliminary results from the control simulations of IFS-FESOM under 1950 radiative conditions. Furthermore, we provide an initial glimpse into results from a historical simulation starting in 1950 with the same model configuration. Our analysis illuminates how ocean eddy-rich regions are portrayed in our simulations relative to observations. We delineate the changes and improvements in key climate components, encompassing North Atlantic/Southern Ocean temperatures, NAO, atmospheric blocking, midlatitude storm tracks, ENSO, Monsoon, ITCZ, Hadley/Walker Cells, MJO, meridional overturning, gyre circulations, as well as Arctic/Antarctic Sea ice dynamics under such high resolution. Moreover, we endeavor to demonstrate how regional high-frequency weather and climate processes can be accurately represented in such simulations, including capturing the nature of regional extremes. In essence, our goal is to illustrate how advancing model resolution to resolve ocean eddies contributes to a more comprehensive representation of the climate system.

The Next Generation of Earth Modeling Systems (nextGEMS) project aimed to produce multidecadal climate simulations, for the first time, with resolved kilometer-scale (km-scale) processes in the ocean, land, and atmosphere. In only 3 years, nextGEMS achieved this milestone with the two km-scale Earth system models, ICOsahedral Non-hydrostatic model (ICON) and Integrated Forecasting System coupled to the Finite-volumE Sea ice-Ocean Model (IFS-FESOM). nextGEMS was based on three cornerstones: (1) developing km-scale Earth system models with small errors in the energy and water balance, (2) performing km-scale climate simulations with a throughput greater than 1 simulated year per day, and (3) facilitating new workflows for an efficient analysis of the large simulations with common data structures and output variables. These cornerstones shaped the timeline of nextGEMS, divided into four cycles. Each cycle marked the release of a new configuration of ICON and IFS-FESOM, which were evaluated at hackathons. The hackathon participants included experts from climate science, software engineering, and high-performance computing as well as users from the energy and agricultural sectors. The continuous efforts over the four cycles allowed us to produce 30-year simulations with ICON and IFS-FESOM, spanning the period 2020-2049 under the SSP3-7.0 scenario. The throughput was about 500 simulated days per day on the Levante supercomputer of the German Climate Computing Center (DKRZ). The simulations employed a horizontal grid of about 5 km resolution in the ocean and 10 km resolution in the atmosphere and land. Aside from this technical achievement, the simulations allowed us to gain new insights into the realism of ICON and IFS-FESOM. Beyond its time frame, nextGEMS builds the foundation of the Climate Change Adaptation Digital Twin developed in the Destination Earth initiative and paves the way for future European research on climate change.

Earth's climate response to increasing greenhouse gas emissions occurs on a variety of spatial scales. To assess climate risks on regional scales and implement adaptation measures, policymakers and stakeholders often require climate change information on scales that are considerably smaller than the typical resolution of global climate models (O(100 km)). To close this important knowledge gap and consider the impact of small-scale processes on the global scale, we adopted a novel iterative global earth system modeling protocol. This protocol provides key information on earth's future climate and its variability on storm-resolving scales (less than 10 km). To this end we used the coupled earth system model OpenIFS–FESOM2 (AWI-CM3; Open Integrated Forecasting System – Finite volumE Sea ice–Ocean Model) with a 9 km atmospheric resolution (TCo1279) and a 4–25 km ocean resolution. We conducted a 20-year 1950 control simulation and four 10-year-long coupled transient simulations for the 2000s, 2030s, 2060s, and 2090s. These simulations were initialized from the trajectory of a coarser 31 km (TCo319) SSP5-8.5 transient greenhouse warming simulation of the coupled model with the same high-resolution ocean. Similar to the coarser-resolution TCo319 transient simulation, the high-resolution TCo1279 simulation with the SSP5-8.5 scenario exhibits a strong warming response relative to present-day conditions, reaching up to 6.5 °C by the end of the century at CO2 levels of about 1100 ppm. The TCo1279 high-resolution simulations show a substantial increase in regional information and climate change granularity relative to the TCo319 experiment (or any other lower-resolution model), especially over topographically complex terrain. Examples of enhanced regional information include projected changes in temperature, rainfall, winds, extreme events, tropical cyclones, and the hydroclimate teleconnection patterns of the El Niño–Southern Oscillation and the North Atlantic Oscillation on scales of less than 1000 km. The novel iterative modeling protocol that facilitates coupled storm-resolving global climate simulations for future climate time slices offers major benefits over regional climate models. However, it also has some drawbacks, such as initialization shocks and resolution-dependent biases and climate sensitivities, which are further discussed.

The surface mixed layer of the ocean plays a key role in ocean‐atmosphere interactions. Despite the ocean surface warming in the past four decades, which increased the stratification, the mixed layer depth (MLD) has been found to increase, most notably in the Southern Ocean in summer. We use 12 models from the Ocean Model Intercomparison Project (OMIP) at different resolutions, forced by the atmospheric reanalysis JRA55‐do, to assess their capability to represent the MLD trends over the period 1970–2018 and to investigate their origin. The MLD evolution in the OMIP models is extremely well correlated across models at interannual time scales, especially in summer. Correlations are lower in high resolution models because of the chaotic nature of the mesoscale variability. OMIP models reproduce consistently the deepening trend of the mixed layer in summer in the Southern Ocean and confirm its relation to the wind speed. The MLD deepening is weaker in the models than in observations, probably due to the fact that the wind speed trend is underestimated in the atmospheric reanalysis. We find however that the MLD deepening is not a simple one‐dimensional response to the increase of the wind speed at a given location, but that the three‐dimensional processes that control the stratification also play a part. This study gives confidence in the capacity of ocean models to project the response of the mixed layer to future changes in wind speed.

Predictive skills of coupled sea-ice/ocean and atmosphere models are limited by the chaotic nature of the atmosphere. Assimilation of observational information on ocean hydrography and sea ice allows to obtain a coupled-system state that provides a basis for subseasonal-to-seasonal ocean and sea-ice forecast (Mu et al., 2022). However, if the atmosphere is not additionally constrained, the quasi-random atmospheric states within an ensemble forecast lead to a fast divergence of the ocean and sea-ice states, degrading the system’s performance with respect to the sea ice forecasts. As reported previously, imposing an additional constraint by nudging large-scale winds to the ERA5 reanalysis data (Sánchez-Benítez et al., 2021; Athanase et al., 2022) improves predictive skills of the AWI Coupled Prediction System (AWI-CPS, Mu et al. 2022) with regard to sea ice drift (Losa et al., 2023). Here we provide results based on a much more extensive set of ensemble-based data assimilation experiments spanning the time period from 2002 to 2023 and a series of long forecast experiments over 2010 – 2023, initialized in four different seasons. We compare the performance of forecasts initialized from two sets of data assimilation experiments, with and without atmospheric wind nudging. The additional relaxation of the large-scale atmospheric circulation to the ERA5 reanalysis data for the initialization leads to reasonable atmospheric forecast skill on weather timescales: Despite the simple technique, the coarse resolution compared to NWP systems, and the limited optimization efforts, 10-day forecasts of the 500 hPa geopotential height are about as skillful as the best performing NWP forecasts were about 10 –15 years ago. Among other aspects, this leads to significantly improved subseasonal-to-seasonal sea-ice concentration and thickness forecasts. Athanase, M., Schwager, M., Streffing, J., Andrés-Martínez, M., Loza, S., and Goessling, H.: Impact of the atmospheric circulation on the Arctic snow cover and ice thickness variability , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5836, https://doi.org/10.5194/egusphere-egu22-5836, 2022.Losa, S. N., Mu, L., Athanase, M., Streffing, J., Andrés-Martínez, M., Nerger, L., Semmler, T., Sidorenko, D., and Goessling, H. F.: Combining sea-ice and ocean data assimilation with nudging atmospheric circulation in the AWI Coupled Prediction System, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-14227, https://doi.org/10.5194/egusphere-egu23-14227, 2023.Mu, L. , Nerger, L. , Streffing, J. , Tang, Q. , Niraula, B. , Zampieri, L., Loza, S. N. and Goessling, H. F. (2022): Sea‐Ice Forecasts With an Upgraded AWI Coupled Prediction System , Journal of Advances in Modeling Earth Systems, 14 (12) . doi: 10.1029/2022ms003176Sánchez-Benítez, A. , Goessling, H. , Pithan, F. , Semmler, T. and Jung, T. (2022): The July 2019 European Heat Wave in a Warmer Climate: Storyline Scenarios with a Coupled Model Using Spectral Nudging , Journal of Climate, 35 (8), pp. 2373-2390 . doi: 10.1175/JCLI-D-21-0573.

Antarctic basal melt is crucial for the future evolution of the Antarctic ice sheet and ocean circulation. However, few Earth system models explicitly simulate ice-shelf cavities. Here, using an Earth system model with interactive Antarctic ice-shelf cavities, we show that regional hydrography and topography determine a cavity tipping point. The Filchner-Ronne ice-shelf cavity will encounter such a tipping point with abrupt warm-water intrusion, rapid basal melt increase and massive freshwater release in response to increasing CO2 levels within this century. Conversely, the Ross Ice Shelf shows a more gradual response. Our results also suggest that previous ice-sheet modelling overestimated future ice-shelf melt, highlighting the need for comprehensive Earth system models with interactive ice-sheet dynamics and cavities for better climate projections.

Despite the importance of the Arctic Ocean for the large-scale circulation and climate, there is still a knowledge gap in our understanding of the spatial characteristics of the Arctic Ocean circulation, especially for the mesoscale. This research diagoses the kinetic energy (KE) and its transfer features of a rich-eddy Arctic Ocean from eddy-resolved sea-ice model FESOM (Finite-Element/volumE Sea ice-Ocean Model) at about 1km in horizontal resolution, revealing the KE spectra at spatial scales and the seasonality. There are two peaks in the kinetic energy spectral density, one at the gyre scale of the Arctic boundary currents (centered at 1700-2000km), and the other associated with the mesoscale (centered at 60km), both of which exhibit a power-law scaling typical for large circulation and ocean eddies, respectively. Energy transfer diagnosis shows that there is inverse-cascade KE pathway at a hundred of kilometers to several killometers, of which the KE transfer value from larger scales to smaller scales is negative. The seasonality of the eddy KE spectrum and energy transfer in upper ocean is found to be highly consistent to sea ice loss trend, while eddy KE in deep ocean shows not significant seasonal variations.

The Atlantic Meridional Overturning Circulation (AMOC) is a crucial component of our climate system, influencing water mass formation and transformation. It is driven by buoyancy fluctuations and mixing within the water column. The AMOC is often studied using climate models by calculating strength indexes based on constant depth intervals (z-AMOC). However, at high latitudes, where deep water forms in the Atlantic, isopycnals are much steeper than in subtropical regions. This means that the z-AMOC framework may not fully capture the processes involved in interior ocean ventilation due to its failure to consider density gradients. To address the potential biases of the z-AMOC approach, we calculate the AMOC using density surfaces (ρ-AMOC). We compare the z-AMOC and ρ-AMOC frameworks under three scenarios: Pre-Industrial (PI), historical, and quadrupled PI CO2 concentrations (4xCO2). The PI and historical simulations serve as a testbed for evaluating the frameworks, while the 4xCO2 scenario is crucial for assessing climate sensitivity and natural variability in response to extreme CO2 levels. We also analyze water mass transformations driven by surface-induced and interior-mixing processes.Our findings reveal that both the location and strength of AMOC maxima are significantly influenced by the choice of framework. Under constant depth coordinates, the AMOC reaches a maximum transport of 21 Sv at approximately 35oN, while it achieves around 25 Sv at 55oN when calculated from density surfaces for both PI and historical climates. In the 4xCO2 scenario, both frameworks show an abrupt weakening of the AMOC, linked to sea-ice melting and reduced deep convection, followed by a gradual recovery to maximum values of 10-15 Sv due to increased evaporation and salt export to the North Atlantic. Furthermore, we find that the z-AMOC maxima time series correlates more closely with those at 26oN (r ~ 0.7) than with ρ-AMOC maxima (r ~-0.3). This discrepancy arises from the flatter isopycnals in the z framework, even in the subpolar North Atlantic where isopycnals are actually steeper. Based on these results, we argue that the density framework better represents the physics of AMOC by directly incorporating water mass transformations and their density structure.We indicate that including the density framework in climate model output configurations enhances our understanding of uncertainties regarding future climate change impacts. The AMOC is a critical climate tipping point, and there is currently no consensus on its future behavior. Calculating ρ-AMOC also becomes especially relevant when considering the 4xCO2 scenario as the AMOC shutdown and recovery in both frameworks driven by different processes indicates that the z-AMOC depicts the right patterns based on incorrect underlying mechanisms. This inconsistency introduces additional uncertainties to conclusions draw in studies addressing future AMOC strength and variability derived from the z-AMOC framework. Finally, we suggest that analysis across timescales and under different conditions must be performed with density surface outputs as much as possible, to enable a more comprehensive evaluation of these two frameworks and their applications.

The Climate Adaptation Digital Twin within the Destination Earth project represents an innovative initiative aimed at achieving operational kilometer-scale global climate simulations to support climate adaptation efforts. Three state-of-the-art Earth System Models (ESMs) are used separately and we are focusing on the scientific advancements and simulation results of the IFS-NEMO model throughout the project's duration.During the first phase of the project, two main simulations were produced: a historical experiment (1990–2019) at 10 km resolution, and a SSP3-7.0 scenario (2020–2039) at 5 km resolution. Phase 2 aims to enable the operationalization of these simulations. Analysis of phase 1 IFS-NEMO results revealed a notable cold bias in the model’s mean state. To address this issue, a newly tuned version of the model was developed, significantly reducing the cooling trends. Key adjustments to achieve this improvement, first tested at a 25 km resolution version of the model, included refinements to sea-ice parameterization within the NEMO model, and the introduction of MACv2-SP forcings in IFS, which enabled the representation of time-varying aerosols in the future scenarios. Additional enhancements were made to couple the river runoff to the ocean.The outcomes of these efforts highlight the potential for substantial advancements in global climate modeling. Looking ahead, the integration of kilometer-scale simulations into operational workflows promises to deliver unprecedented detail and accuracy in climate projections. This will enable more precise assessments of climate impacts and provide critical insights for policymakers and stakeholders striving to implement effective climate adaptation strategies. The continued refinement of the IFS-NEMO model and its components will play a pivotal role in achieving these ambitious goals.

Freshwater hosing experiments are a widely used tool for understanding the impacts of Antarctic ice shelf basal melting on the Southern Ocean and global climate. Most existing coupled climate models lack the necessary physics to explicitly simulate basal melting. Therefore, freshwater anomalies have to be imposed as a proxy. Previous studies have employed diverse freshwater scenarios and application methods. In this study, we explore variations in the application and representation of meltwater anomalies around Antarctica. We compare simulations where freshwater anomalies are introduced at the ocean surface over different spatial extents and at specified depths along the continental slope for a more realistic representation of plume dynamics resulting from basal melting. Additionally, we investigate ocean heat fluxes variability when accounting for the latent heat of fusion required to melt the ice. It is possible to observe similarities and differences in ocean responses depending on the methodology used to impose the freshwater anomaly. Surface application scenarios tend to exhibit more diffuse impacts on ocean stratification and circulation, while depth-specific applications lead to localized but more intense changes in water mass transformation. Accounting for latent heat can introduce further complexity, altering the thermal structure and influencing buoyancy-driven dynamics. By comparing these approaches, we want to highlight the sensitivity of simulated ocean dynamics to the spatial and physical representation of meltwater inputs. Accurately parameterizing ice-ocean interactions in models is necessary to improve the reliability of projections regarding Antarctic contributions to sea level rise and global climate variability.

We report on the first multi-year kilometre-scale global coupled simulations using ECMWF's Integrated Forecasting System (IFS) coupled to both the NEMO and FESOM ocean–sea ice models, as part of the H2020 Next Generation Earth Modelling Systems (nextGEMS) project. We focus mainly on an unprecedented IFS-FESOM coupled setup, with an atmospheric resolution of 4.4 km and a spatially varying ocean resolution that reaches locally below 5 km grid spacing. A shorter coupled IFS-FESOM simulation with an atmospheric resolution of 2.8 km has also been performed. A number of shortcomings in the original numerical weather prediction (NWP)-focused model configurations were identified and mitigated over several cycles collaboratively by the modelling centres, academia, and the wider nextGEMS community. The main improvements are (i) better conservation properties of the coupled model system in terms of water and energy budgets, which also benefit ECMWF's operational 9 km IFS-NEMO model; (ii) a realistic top-of-the-atmosphere (TOA) radiation balance throughout the year; (iii) improved intense precipitation characteristics; and (iv) eddy-resolving features in large parts of the mid- and high-latitude oceans (finer than 5 km grid spacing) to resolve mesoscale eddies and sea ice leads. New developments at ECMWF for a better representation of snow and land use, including a dedicated scheme for urban areas, were also tested on multi-year timescales. We provide first examples of significant advances in the realism and thus opportunities of these kilometre-scale simulations, such as a clear imprint of resolved Arctic sea ice leads on atmospheric temperature, impacts of kilometre-scale urban areas on the diurnal temperature cycle in cities, and better propagation and symmetry characteristics of the Madden–Julian Oscillation.