High-resolution, kilometer-scale information on regional climate impacts is critical for effective adaptation and mitigation strategies. The European Commission’s Destination Earth (DestinE) Climate Adaptation Digital Twin (Climate DT) aims to address this need; however, actionable impact assessments remain limited by incomplete representation of key Earth system components and their interactions. The Horizon Europe funded TerraDT project tackles these limitations by developing a state of the art Digital Twin focused on the cryosphere, land surface, aerosols, and their coupled processes, fully interoperable within the DestinE ecosystem.TerraDT pursues three objectives: (1) build and deploy new Digital Twin Components (DTCs) to strengthen process realism and enable impact assessments; (2) deliver a modular, scalable, interoperable platform integrating advanced software, high-performance computing, and data workflows that can host physical models and Artificial Intelligence (AI)/Machine Learning (ML) emulators; and (3) foster user uptake through early engagement and a User centric Interface (UI).In its first year, TerraDT achieved several milestones:Cryosphere: A prototype Land-Ice DTC was established by coupling Elmer/Ice with ICON climate model via YAC coupler, supported by curated glacier dynamics datasets. Development of the Sea-Ice DTC (FESIM) began in mid-2025, including YAC-mediated coupling and an AI sea-ice emulator capable of ~100-day to multi-year rollouts, producing smoother fields than physical models. Land Surface: A prototype time-varying land use dataset was generated for ECland and ICON land surface models. Aerosols: A simplified Aerosol DTC was tested, with integration into (open) Integrated Forecasting System (IFS). ML components were prototyped in HAM-LITE to capture advanced aerosol physics (e.g., hygroscopicity) at reduced computational cost.Impact modelling advanced across multiple domains:Sea-ice: Assessments of ice season duration, severe condition probabilities.Forest: Integration of 3PG and Prebasso models, calibration across European ecosystems, ML emulation of Prebasso, and characterization of old-growth forests.Urban: A carbon-sequestration emulator validated in Helsinki, with planned extensions to Lisbon, Barcelona, Munich, Paris, and Zurich. Key data sets required are prepared in combination with ML methods, and will be applied to build advanced Urban impact models for assessing climate extremes.Infrastructure and interoperability were strengthened through YAC based coupling (ICON-Energy Balance Firn Model-Elmer/Ice on LUMI and Levante Supercomputers), and Sea Ice DTC I/O plans were aligned with DestinE workflows. A map-based UI architecture was designed to expose high resolution impact assessments for decision support.By advancing new DTCs, AI/ML emulators, and generic coupling interface, TerraDT is being developed for full integration into the DestinE framework, ensuring compatibility and enhancing the overall ecosystem’s capability to inform climate adaptation and mitigation strategies. This presentation will summarize first year progress, outline objectives, and present the roadmap toward fully coupled simulations, validation, and dissemination of impact indicators through TerraDT UI for policy and stakeholder communities.

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.

The weather and climate model ICON (ICOsahedral Nonhydrostatic) is being used in high-resolution climate simulations, in order to resolve small-scale physical processes. The envisaged performance for this task is 1 simulated year per day for a coupled atmosphere–ocean setup at global 1.2 km resolution. The necessary computing power for such simulations can only be found on exascale supercomputing systems. The main question we try to answer in this article is where to find sustained exascale performance, i.e. which hardware (processor type) is best suited for the weather and climate model ICON, and consequently how this performance can be exploited by the model, i.e. what changes are required in ICON's software design so as to utilize exascale platforms efficiently. To this end, we present an overview of the available hardware technologies and a quantitative analysis of the key performance indicators of the ICON model on several architectures. It becomes clear that parallelization based on the decomposition of the spatial domain has reached the scaling limits, leading us to conclude that the performance of a single node is crucial to achieve both better performance and better energy efficiency. Furthermore, based on the computational intensity of the examined kernels of the model it is shown that architectures with higher memory throughput are better suited than those with high computational peak performance. From a software engineering perspective, a redesign of ICON from a monolithic to a modular approach is required to address the complexity caused by hardware heterogeneity and new programming models to make ICON suitable for running on such machines.

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.

We present the first-ever global simulation of the full Earth system at 1.25 km grid spacing, achieving highest time compression with an unseen number of degrees of freedom. Our model captures the flow of energy, water, and carbon through key components of the Earth system: atmosphere, ocean, and land. To achieve this landmark simulation, we harness the power of 8192 GPUs on Alps and 20480 GPUs on JUPITER, two of the world's largest GH200 superchip installations. We use both the Grace CPUs and Hopper GPUs by carefully balancing Earth's components in a heterogeneous setup and optimizing acceleration techniques available in ICON's codebase. We show how separation of concerns can reduce the code complexity by half while increasing performance and portability. Our achieved time compression of 145.7 simulated days per day enables long studies including full interactions in the Earth system and even outperforms earlier atmosphere-only simulations at a similar resolution.

Reliable, high-resolution information on regional and local climate impacts is crucial for effective climate change adaptation and mitigation strategies. The European Commission Destination Earth (DestinE) initiative aims to address this need by creating advanced Digital Twins (DTs) of the Earth, including the Climate Adaptation Digital Twin (Climate DT), which provides km-scale climate information over multiple decades. However, the ability of the Climate DT to support actionable impact assessments is limited by its incomplete representation of critical Earth system components.To overcome these limitations, we present TerraDT, a Horizon Europe-funded research project focused on developing a state-of-the-art Digital Twin of the Earth system with a specific emphasis on the cryosphere, land surface, and their interactions. TerraDT aligns with the DestinE vision of creating interoperable and interactive DTs and advances Earth system modeling by enhancing the representation of land ice, sea ice, aerosols, and land surface processes at global km-scale resolution.TerraDT features a modular and scalable infrastructure with a generic coupling interface that supports the integration of novel components, including artificial intelligence (AI) and machine learning (ML)-based emulators. This framework enables more accurate climate projections and impact assessments, while user-oriented models provide actionable insights into cryosphere and land-surface-related challenges. The project pursues three primary objectives:Develop TerraDT to improve climate projections and impact assessments for enhanced decision-making. Enhance the DestinE infrastructure by creating a modular, scalable, and interoperable TerraDT platform with advanced software, high-performance computing, and data handling capabilities. Foster user uptake by engaging the scientific community and stakeholders in public and private sectors, ensuring a user-centric approach to development and deployment. TerraDT is designed for full integration into the DestinE framework, ensuring compatibility and enhancing the overall ecosystem’s capability to guide climate adaptation and mitigation efforts.By delivering improved accuracy in modeling the cryosphere and land-surface interactions, TerraDT positions itself as a transformative enhancement to DestinE. Its innovative infrastructure, combined with its focus on modularity and user engagement, ensures TerraDT provides robust, actionable climate projections to policymakers and stakeholders worldwide, fostering a more resilient and sustainable future.

To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.

State-of-the-art Earth system models typically employ grid spacings of O(100 km), which is too coarse to explicitly resolve main drivers of the flow of energy and matter across the Earth system. In this paper, we present the new ICON-Sapphire model configuration, which targets a representation of the components of the Earth system and their interactions with a grid spacing of 10 km and finer. Through the use of selected simulation examples, we demonstrate that ICON-Sapphire can (i) be run coupled globally on seasonal timescales with a grid spacing of 5 km, on monthly timescales with a grid spacing of 2.5 km, and on daily timescales with a grid spacing of 1.25 km; (ii) resolve large eddies in the atmosphere using hectometer grid spacings on limited-area domains in atmosphere-only simulations; (iii) resolve submesoscale ocean eddies by using a global uniform grid of 1.25 km or a telescoping grid with the finest grid spacing at 530 m, the latter coupled to a uniform atmosphere; and (iv) simulate biogeochemistry in an ocean-only simulation integrated for 4 years at 10 km. Comparison of basic features of the climate system to observations reveals no obvious pitfalls, even though some observed aspects remain difficult to capture. The throughput of the coupled 5 km global simulation is 126 simulated days per day employing 21 % of the latest machine of the German Climate Computing Center. Extrapolating from these results, multi-decadal global simulations including interactive carbon are now possible, and short global simulations resolving large eddies in the atmosphere and submesoscale eddies in the ocean are within reach.

​​​​​​​The scalability of the atmospheric model ECHAM6 at low resolution, as used in palaeoclimate simulations, suffers from the limited number of grid points. As a consequence, the potential of current high-performance computing architectures cannot be used at full scale for such experiments, particularly within the available domain decomposition approach. Radiation calculations are a relatively expensive part of the atmospheric simulations, taking up to approximately 50 % or more of the total runtime. This current level of cost is achieved by calculating the radiative transfer only once in every 2 h of simulation. In response, we propose extending the available concurrency within the model further by running the radiation component in parallel with other atmospheric processes to improve scalability and performance. This paper introduces the concurrent radiation scheme in ECHAM6 and presents a thorough analysis of its impact on the performance of the model. It also evaluates the scientific results from such simulations. Our experiments show that ECHAM6 can achieve a speedup of over 1.9× using the concurrent radiation scheme. By performing a suite of stand-alone atmospheric experiments, we evaluate the influence of the concurrent radiation scheme on the scientific results. The simulated mean climate and internal climate variability by the concurrent radiation generally agree well with the classical radiation scheme, with minor improvements in the mean atmospheric circulation in the Southern Hemisphere and the atmospheric teleconnection to the Southern Annular Mode. This empirical study serves as a successful example that can stimulate research on other concurrent components in atmospheric modelling whenever scalability becomes challenging.

This paper is about increasing parallelism in climate models via additional component concurrency.

•Adjoint- and sensitivity-based optimisations are investigated for active flow control.•Comprehensive review of both optimisation strategies is given.•Both methods are applied to control the laminar flow over a backward-facing step.•Sensitivity-based approach is chosen to optimise an electrically-excited micromixer.

This paper is concerned with the optimization of an electrokinetic micromixer suitable for Lab-on-Chip and other microfluidic applications. The mixing concept is based on the combination of an alternating electrical excitation applied to a pressure-driven base flow in a meandering microchannel geometry. The electrical excitation induces a secondary electrokinetic velocity component which results in a complex flow field within the meander bends. A mathematical model describing the physicochemical phenomena present within the micromixer is implemented in an in-house Finite-Element-Method code. We first perform simulations comparable to experiments concerned with the investigation of the flow field in the bends. The comparison of simulation and experiment reveals excellent agreement. Hence, the validated model and numerical schemes are employed for a numerical optimization of the micromixer performance. In detail, we optimize the secondary electrokinetic flow by finding the best electrical excitation parameters, i.e. frequency and amplitude, for a given waveform. The simulation results of two optimized electrical excitations featuring a discrete and a continuous waveform are compared and discussed. The results demonstrate that the micromixer is able to achieve high mixing degrees very rapidly.

This work is concerned with the investigation of the concentration fields in an electrokinetic micromixer and its optimization in order to achieve high mixing rates. The mixing concept is based on the combination of an alternating electrical excitation applied to a pressure-driven base flow in a meandering microchannel geometry. The electrical excitation induces a secondary electrokinetic velocity component, which results in a complex flow field within the meander bends. A mathematical model describing the physicochemical phenomena present within the micromixer is implemented in an in-house finite-element-method code. We first perform simulations comparable to experiments concerned with the investigation of the flow field in the bends. The comparison of the complex flow topology found in simulation and experiment reveals excellent agreement. Hence, the validated model and numerical schemes are employed for a numerical optimization of the micromixer performance. In detail, we optimize the secondary electrokinetic flow by finding the best electrical excitation parameters, i.e., frequency and amplitude, for a given waveform. Two optimized electrical excitations featuring a discrete and a continuous waveform are discussed with respect to characteristic time scales of our mixing problem. The results demonstrate that the micromixer is able to achieve high mixing degrees very rapidly.

Mixing of liquids in micro mixers at low Reynolds numbers is a challenging task since the flow regime is laminar and it is difficult to engage instabilities of the flow. In many microfluidic systems, mixing can be improved by means of electrokinetic effects. A favorable micro mixer design consists of a Y-junction, where the different liquid streams merge, and a subsequent meandering microchannel. A pressure gradient pumps the liquids to be mixed through the microchannel. An oscillating electrical field is superimposed onto the pressure-driven base flow which generates an additional electrokinetic (electro osmotic) flow. These oscillating secondary flows in conjunction with the meandering geometry are responsible for stretching and folding of the contact area of the liquids to be mixed which enhances the mass transfer rates considerably. In this contribution, we present a mathematical model which allows for the numerical simulation of flow, electrical potential, and species concentration. The model is validated by experiments relying on Micro Particle Image Velocimetry (mu PIV). Consequently, this model can be used to numerically optimize the electrical field in order to achieve fast and high mixing even at low Reynolds numbers.