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A lightweight software library has been developed to realise the coupling of Earth system model components. The software provides parallelised two-dimensional neighbourhood search, interpolation, and communication for the coupling between any two model components. The software offers flexible coupling of physical fields defined on regular and irregular grids on the sphere without a priori assumptions about grid structure or grid element types. All supported grids can be combined with any of the supported interpolations. We describe the new aspects of our approach and provide an overview of the implemented functionality and of some algorithms we use. Preliminary performance measurements for a set of realistic use cases are presented to demonstrate the potential performance and scalability of our approach. YAC 1.2.0 is now used for the coupling of the model components in the Icosahedral Nonhydrostatic (ICON) general circulation model.

The confrontation of complex Earth system model (ESM) codes with novel supercomputing architectures poses challenges to efficient modeling and job submission strategies. The modular setup of these models naturally fits a modular supercomputing architecture (MSA), which tightly integrates heterogeneous hardware resources into a larger and more flexible high-performance computing (HPC) system. While parts of the ESM codes can easily take advantage of the increased parallelism and communication capabilities of modern GPUs, others lag behind due to the long development cycles or are better suited to run on classical CPUs due to their communication and memory usage patterns. To better cope with these imbalances between the development of the model components, we performed benchmark campaigns on the Jülich Wizard for European Leadership Science (JUWELS) modular HPC system. We enabled the weather and climate model Icosahedral Nonhydrostatic (ICON) to run in a coupled atmosphere–ocean setup, where the ocean and the model I/O is running on the CPU Cluster, while the atmosphere is simulated simultaneously on the GPUs of JUWELS Booster (ICON-MSA). Both atmosphere and ocean are running globally with a resolution of 5 km. In our test case, an optimal configuration in terms of model performance (core hours per simulation day) was found for the combination of 84 GPU nodes on the JUWELS Booster module to simulate the atmosphere and 80 CPU nodes on the JUWELS Cluster module, of which 63 nodes were used for the ocean simulation and the remaining 17 nodes were reserved for I/O. With this configuration the waiting times of the coupler were minimized. Compared to a simulation performed on CPUs only, the MSA approach reduces energy consumption by 45 % with comparable runtimes. ICON-MSA is able to scale up to a significant portion of the JUWELS system, making best use of the available computing resources. A maximum throughput of 170 simulation days per day (SDPD) was achieved when running ICON on 335 JUWELS Booster nodes and 268 Cluster nodes.

The relative importance of regional processes inside the Arctic climate system and the large scale atmospheric circulation for Arctic interannual climate variability has been estimated with the help of a regional Arctic coupled ocean-ice-atmosphere model. The study focuses on sea ice and surface climate during the 1980s and 1990s. Simulations agree reasonably well with observations. Correlations between the winter North Atlantic Oscillation index and the summer Arctic sea ice thickness and summer sea ice extent are found. Spread of sea ice extent within an ensemble of model runs can be associated with a surface pressure gradient between the Nordic Seas and the Kara Sea. Trends in the sea ice thickness field are widely significant and can formally be attributed to large scale forcing outside the Arctic model domain. Concerning predictability, results indicate that the variability generated by the external forcing is more important in most regions than the internally generated variability. However, both are in the same order of magnitude. Local areas such as the Northern Greenland coast together with Fram Straits and parts of the Greenland Sea show a strong importance of internally generated variability, which is associated with wind direction variability due to interaction with atmospheric dynamics on the Greenland ice sheet. High predictability of sea ice extent is supported by north-easterly winds from the Arctic Ocean to Scandinavia.

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.

Since the dawn of functioning numerical dynamical atmosphere- and ocean models, their resolution has steadily increased, fed by an exponential growth in computational capabilities. However, because resolution of models is at all times limited by computational power a number of mostly small-scale or micro-scale processes have to be parameterised. Particularly those of atmospheric moist convection and ocean eddies are problematic when scientists seek to interpret output from model experiments. Here we present the first coupled ocean-atmosphere model experiments with sufficient resolution to dispose of moist convection and ocean eddy parameterisations. We describe the early development and discuss the challenges associated with conducting the simulations with a focus on tuning the global mean radiation balance in order to limit drifts. A four-month experiment with quadrupled CO2 is then compared with a ten-member ensemble of low-resolution simulations using MPI-ESM1.2-LR. We find broad similarities of the response, albeit with a more diversified spatial pattern with both stronger and weaker regional warming, as well as a sharpening of precipitation in the inter tropical convergence zone. These early results demonstrate that it is already now possible to learn from such coupled model experiments, even if short by nature.

The recovery of the oceanic flow field in situ data is one of the oldest problems of modern oceanography. In this study, a stationary, nonlinear inverse model is used to estimate a mean geostrophic flow field from hydrographic data along a hydrographic section.

The new Max‐Planck‐Institute Earth System Model (MPI‐ESM) is used in the Coupled Model Intercomparison Project phase 5 (CMIP5) in a series of climate change experiments for either idealized CO2‐only forcing or forcings based on observations and the Representative Concentration Pathway (RCP) scenarios. The paper gives an overview of the model configurations, experiments related forcings, and initialization procedures and presents results for the simulated changes in climate and carbon cycle. It is found that the climate feedback depends on the global warming and possibly the forcing history. The global warming from climatological 1850 conditions to 2080–2100 ranges from 1.5°C under the RCP2.6 scenario to 4.4°C under the RCP8.5 scenario. Over this range, the patterns of temperature and precipitation change are nearly independent of the global warming. The model shows a tendency to reduce the ocean heat uptake efficiency toward a warmer climate, and hence acceleration in warming in the later years. The precipitation sensitivity can be as high as 2.5% K−1 if the CO2 concentration is constant, or as small as 1.6% K−1, if the CO2 concentration is increasing. The oceanic uptake of anthropogenic carbon increases over time in all scenarios, being smallest in the experiment forced by RCP2.6 and largest in that for RCP8.5. The land also serves as a net carbon sink in all scenarios, predominantly in boreal regions. The strong tropical carbon sources found in the RCP2.6 and RCP8.5 experiments are almost absent in the RCP4.5 experiment, which can be explained by reforestation in the RCP4.5 scenario. Key Points The climate feedback in MPI‐ESM is non‐linear and depends on the forcing history Ocean heat uptake is reduced in a warmer climate. Patterns of temperature and precipitation changes are robust for RCP26/45/85.

Since the dawn of functioning numerical dynamical atmosphere- and ocean models, their resolution has steadily increased, fed by an exponential growth in computational capabilities. However, because resolution of models is at all times limited by computational power a number of mostly small-scale or micro-scale processes have to be parameterised. Particularly those of atmospheric moist convection and ocean eddies are problematic when scientists seek to interpret output from model experiments. Here we present the first coupled ocean-atmosphere model experiments with sufficient resolution to dispose of moist convection and ocean eddy parameterisations. We describe the early development and discuss the challenges associated with conducting the simulations with a focus on tuning the global mean radiation balance in order to limit drifts. A four-month experiment with quadrupled CO2 is then compared with a ten-member ensemble of low-resolution simulations using MPI-ESM1.2-LR. We find broad similarities of the response, albeit with a more diversified spatial pattern with both stronger and weaker regional warming, as well as a sharpening of precipitation in the inter tropical convergence zone. These early results demonstrate that it is already now possible to learn from such coupled model experiments, even if short by nature.

A new release of the Max Planck Institute for Meteorology Earth System Model version 1.2 (MPI‐ESM1.2) is presented. The development focused on correcting errors in and improving the physical processes representation, as well as improving the computational performance, versatility, and overall user friendliness. In addition to new radiation and aerosol parameterizations of the atmosphere, several relatively large, but partly compensating, coding errors in the model's cloud, convection, and turbulence parameterizations were corrected. The representation of land processes was refined by introducing a multilayer soil hydrology scheme, extending the land biogeochemistry to include the nitrogen cycle, replacing the soil and litter decomposition model and improving the representation of wildfires. The ocean biogeochemistry now represents cyanobacteria prognostically in order to capture the response of nitrogen fixation to changing climate conditions and further includes improved detritus settling and numerous other refinements. As something new, in addition to limiting drift and minimizing certain biases, the instrumental record warming was explicitly taken into account during the tuning process. To this end, a very high climate sensitivity of around 7 K caused by low‐level clouds in the tropics as found in an intermediate model version was addressed, as it was not deemed possible to match observed warming otherwise. As a result, the model has a climate sensitivity to a doubling of CO 2 over preindustrial conditions of 2.77 K, maintaining the previously identified highly nonlinear global mean response to increasing CO 2 forcing, which nonetheless can be represented by a simple two‐layer model. An updated version of the Max Planck Institute for Meteorology Earth System Model (MPI‐ESM1.2) is presented The model includes both code corrections and parameterization improvements Despite this, the model maintains an equilibrium climate sensitivity, which rises with warming

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.