After decades of stability, Southern Ocean sea ice has recently experienced an abrupt decline, with uncertain future behaviour. Using high-resolution climate simulations, we identify a seasonally modulated cascade of feedbacks driving rapid sea ice loss, especially in the Weddell Sea. Anthropogenic warming reduces sea ice, enhancing ocean heat release in warm seasons, which warms and moistens the atmospheric boundary layer in cold seasons. This increases mid-level cloud cover and longwave radiative warming, suppressing spring sea ice formation and activating the sea ice-albedo feedback. Current ocean warming trends indicate this transition threshold is nearly reached. These findings highlight a potential near-term regime shift in Southern Ocean sea ice, emphasising the importance of monitoring ocean-atmosphere interactions and cloud feedbacks to understand implications for regional and global climate change.

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.

Liquid-containing clouds have an important impact on Arctic winter climate because they suppress radiative cooling of the surface. Pure ice clouds have a much weaker effect on longwave radiation, and often permit substantial surface radiative cooling. Here, we show that climate models typically underestimate the difference in surface radiation under low-level liquid and ice clouds in the Arctic. The analysed models consistently overestimate the longwave radiative effect of thin ice clouds compared to ground-based observations from the MOSAiC expedition. This mismatch occurs despite realistic ice cloud effective radii in models, and thus cannot be due to errors in cloud properties. The model behaviour reflects the relationship between ice water path and cloud optical thickness that is at the core of commonly used ice optics parametrizations, but this relationship is inconsistent with MOSAiC observations. Ice optics parametrizations have been developed for cirrus clouds, and low-level Arctic ice clouds may be more heterogeneous, or have different ice habits, reducing their radiative impact compared to a cirrus cloud of the same ice water path and effective radius. Our results suggest that climate models understimate the surface warming effect of an increasing liquid fraction of cloud condensate in a warming Arctic.

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.

The projected weakening of the Atlantic Meridional Overturning Circulation (AMOC) poses substantial risks for global and regional climate stability. While the large-scale cooling associated with a weakened AMOC is well-documented, how weather and climate extremes respond to such changes remains little examined. Here, we investigate how recent European summer and winter temperature extremes (2018-2022) would change under different weakened AMOC states using the Alfred Wegener Institute Climate Model (AWI-CM3). We generate three sets of five-member ensemble simulations, each representing a different AMOC state: a factual (present-day AMOC) state and two counterfactual states with a weakened and a shut-down AMOC. All simulations are spectrally nudged to the large-scale winds observed during 2017-2022. We thus focus primarily on the thermodynamic impacts induced by AMOC weakening within the same realization of atmospheric variability. Our research indicates that a weakened AMOC generally reduces the occurrence of summer hot days, though this response is spatially heterogeneous, implying a flow-dependence of the AMOC-related impact. For instance, Eastern Europe remains comparatively less affected even when AMOC strength is reduced by 60% relative to the present day conditions. In contrast, winter cold extremes are substantially intensified. We observe a drastic increase in cold days, with daily minimum temperatures during these events decreasing by more than 6 °C in several northwestern European capital cities. These findings highlight the nonlinear and seasonally asymmetric responses of European temperature extremes to AMOC weakening and provide important insights for regional climate risk assessment and adaptation strategies.

Abstract The spread in projected global warming across the Coupled Model Intercomparison Project (CMIP) models under idealized forcing has been statistically linked to the inter‐model difference in climatological Atlantic Meridional Overturning Circulation (cAMOC), yet the underlying physical mechanisms remain unclear. Here, we analyze realistic future scenarios in CMIP models using a zero‐layer energy balance model (EBM) to establish a physical connection between cAMOC and future global warming. We find that enabled by weak stratification, a stronger cAMOC is associated with stronger ocean heat uptake efficiency and more negative climate feedbacks. Incorporating this connection into the zero‐layer EBM reveals an inverse relationship between cAMOC and future global warming. Applying the observed AMOC strength to this relationship constrains the 95% confidence interval of future sea surface warming from 0.51°C–2.25°C, 0.89°C–3.23°C, and 1.74°C–5.49°C to 0.83°C–2.19°C, 1.53°C–3.05°C, and 2.97°C–5.10°C under low‐ to high‐emission scenarios, respectively.

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.

In this study, we evaluate the performance of the latest version of the Alfred Wegener Institute Climate Model, AWI-CM3, in two configurations at different resolutions, demonstrating that higher spatial resolution substantially enhances the model's ability to reproduce key climate variables and processes. The medium-resolution configuration consistently reduces climatological biases compared to both the low-resolution setup and the CMIP6 (Coupled Model Intercomparison Project, phase 6) multi-model mean, particularly in polar regions and areas characterized by strong mesoscale dynamics. Improvements are especially notable in the simulation of sea ice variability, ocean circulation, and ocean-atmosphere interactions. The medium-resolution simulation also exhibits greater interannual variability, which may reflect a more realistic representation of underlying processes, but whose implications will need to be fully assessed with multiple ensemble members. We conclude that long-term, eddy-permitting climate projections offer promising avenues for reducing structural uncertainties in future climate projections. As global modeling efforts move toward CMIP7 and beyond, our results highlight the importance of pursuing medium-resolution strategies in parallel with improved physical parameterizations and ensemble-based evaluation to more robustly capture the nonlinearities of the Earth system.

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.

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.

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.

In the last decades, the operation, maintenance and administration of Earth System Models (ESMs) have become substantially more complex due to the increasing number of available models, coupling approaches and versions, and the need of tuning for different scales and configurations. Another factor contributing to the complexity of operation is the requirement to run the models on different High Performance Computing (HPC) platforms. In this context, configuration tools, workflow managers and ESM-oriented scripting tools have become essential for administrating, distributing and operating ESMs, across research groups, institutions and members of international projects, while still ensuring simulation reproducibility. ESM-Tools is an open-source software infrastructure and configuration tool that tackles these challenges associated with the operation of ESMs. ESM-Tools enables seamlessly building and running ESMs across different HPCs in a reproducible manner. Most importantly, it is used by model developers to distribute standard simulation configurations, so that the user can effortlessly run these predefined simulations while retaining the flexibility to modify only the parameters that align with their specific needs. This lowers the technical threshold for new model users and makes the ESMs more accessible. The source-code consists of an HPC- and model-agnostic Python back-end, and a set of model- and HPC-specific configuration YAML files. In this way, adding a new model, coupled model or HPC is just a matter of writing new configuration YAML files. The configuration files are highly modularized which allows for their reutilization in new setups (e.g. new components are added, while some existing component configurations are reused). Configuration conflicts between the different files are resolved hierarchically accordingly to their configuration category, giving priority to model- and simulation-specific configurations. ESM-Tools also provides basic workflow-management capabilities which allow for plugging in preprocessing and postprocessing tasks and running offline coupled models. The tasks of the ESM-Tools workflow can be reorganized, new tasks can be included, and single tasks can be executed independently, allowing for its integration in more advance workflow manager software if required. Among other coupled Earth System Models, ESM-Tools is currently used to manage and distribute the OpenIFS-based Climate Models AWI-CM3 (FESOM2 + OpenIFS, developed at AWI) and FOCI-OpenIFS (NEMO4 + OpenIFS43r3, developed at GEOMAR, running ORCA05 and ORCA12 in coupled mode with OASIS3-MCT5.0), as well as the AWI-ESM family of models (ECHAM6 + FESOM2). HPCs supported include those of the DKRZ (Hamburg, Germany), Jülich Supercomputing Center (Jülich, Germany), HLRN (Berlin and Göttingen, Germany), and the IBS Center for Climate Physics (Busan, South Korea), with plans to support LUMI (Kajaani, Finland) and desktop distributions (for educational purposes). In this contribution we will introduce ESM-Tools and the design choices behind ESM-Tools architecture. Additionally, we will discuss the advantages of such a modular system, and address the challenges associated with its usability and maintainability resulting from these design choices and our mitigation strategies.

Assessing the future risk of natural disasters, securing sustainable energy and water resources, and developing strategies for adapting to climate change remain challenging due to the large uncertainties in regional-scale climate projections. Recent efforts to address this issue include km-scale coupled climate model simulations that resolve mesoscale processes in the atmosphere and ocean, as well as their interactions with the large-scale environment and small-scale topographic features. Our presentation shows the first results from a series of global 9 km-scale greenhouse warming simulations using the AWI Climate Model Version 3 which is based on the OpenIFS atmosphere model at TCO1279 resolution and 137 vertical levels and the FESOM2 ocean model at 4-15 km resolution. By comparing a set of consecutive 10-year time-slice simulations forced by the CMIP6 SSP585 scenario with a transient simulation at a lower-resolution (31 km in the OpenIFS), we identify key differences in weather and climate-related phenomena, including tropical cyclones, ENSO, and regional climate change features that can be attributed to km-scale dynamics in clouds and atmospheric circulation patterns. The findings from our cloud-permitting climate simulations provide valuable insights into the role of small-scale processes in the sensitivity of the regional and global climate.

Quantifying the Earth's climate system response to changes in atmospheric carbon dioxide (CO2) concentrations is crucial for understanding the impact of greenhouse gases on the Earth's past, present, and future climate. The sensitivity of the Earth's climate to increasing CO2 levels will largely determine the environmental conditions faced by human societies, fauna, and flora in the years to come. Projected future climate conditions depend on the sensitivity of the numerical models employed. Therefore, a comprehensive understanding of model sensitivity to radiative forcing across various temporal and spatial scales is essential. Towards this goal, we employ the newly developed AWI-CM3 model, which will be used for future climate projections in CMIP7, to examine Equilibrium Climate Sensitivity (ECS) across different time scales. Our quasi-equilibrium simulations span 2,000 model years, subjected to atmospheric CO2 concentrations of 280, 400, 560, and 1120 ppmv. The highest concentration simulation is inspired by the CMIP6 abrupt4xCO2 protocol, designed to assess climate response to an abrupt change in radiative forcing. Notably, our simulations run much longer than the CMIP6 suggested 150-year duration. The lower concentration simulation represents the pre-industrial period (PI), while the remaining were designed to investigate the climate with CO2 concentrations similar to the current climate and with a doubling of PI levels, respectively.The ECS derived from AWI-CM3 stands at 3.95ºC, ranking it as medium-range sensitivity compared to the CMIP6 ensemble. A key finding is that ECS increases by up to 1.5ºC when simulations are extended beyond the CMIP6 minimum runtime requirement. This change in ECS correlates to alternations in deep water formation in both the North Atlantic and Southern Oceans. Throughout the simulations, we note adjustment processes in the overall climate and multi-centennial variability in the strength of the Atlantic Meridional Overturning Circulation (AMOC) due to changes in North Atlantic Deep Water (NADW) and Antarctic Bottom Water (AABW) formation. The simulations also reveal a progressive weakening and shallowing of the AMOC and a strengthening of the AABW as CO2 concentrations increase. Beyond 200 years, under adjusted radiative forcing, the AMOC recovers, but the resultant circulation pattern features persistently shallower NADW and a weaker, more northward-extending AABW in the Atlantic and Pacific Oceans. Our results highlight the intricate relationship between deep water formation and Earth's equilibrium climate sensitivity. Furthermore, our findings suggest a need to reevaluate the current framework for deriving ECS in the standard CMIP6 methodology. Prolonged simulations not only enhance our understanding of the underlying mechanisms driving climate sensitivity to changing radiative forcing but also provide valuable insights into the time required for the Earth's climate to adjust to these changes.

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.

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.

Clouds are an important regulator of earth’s radiation balance. Therefore, future changes in clouds and corresponding feedbacks are likely to influence global climate sensitivity. How clouds respond to greenhouse warming on global and regional scales is still not well understood. Here we present first results from a km-scale, cloud-permitting greenhouse warming simulation conducted with the coupled OpenIFS-FESOM2 model (AWI-CM3) with ~9 km atmosphere resolution, 137 vertical levels and 4-15 km variable ocean resolution. Our analysis is based on a set of 10-year time-slice simulations, which branched off from a lower-resolution (31 km) SSP585 transient scenario run with relatively high climate sensitivity. We will quantify the effect of atmosphere resolution and cloud granularity on cloud radiative feedbacks. We will further present results from the calculation of radiative kernels to determine the role of high cloud feedbacks in polar amplification.