Human-induced global warming manifests as a distinct spatial pattern of changes in temperature and precipitation extremes. IPCC assessments of such changes are primarily based on models of the latest Coupled Model Intercomparison Project (CMIP6), which are limited in their representation of local details due to their rather coarse resolution of 50-200km. Here, we test if the first multi-decadal simulations with two fully-coupled km-scale global climate models (ICON and IFS), project greater or smaller local changes in extremes in response to global warming, focusing on annual minimum and maximum temperature, as well as on extreme precipitation. 

Using spatially pooled rank histograms of changes, we find that IFS behaves remarkably similarly to the CMIP6 multi-model mean in many cases, indicating a very low range of local trends across the globe despite its high resolution. ICON, in turn, shows a much broader range with more strongly positive or negative local trends than any of the CMIP6 models. However, while this leads to ICON being more similar to the observation-based ERA5, further analysis also reveals that this behavior is, at least partly, caused by unrealistic change signals in some regions, where local extreme temperature changes can exceed 15K per degree of global warming even in the historical period. 

Notably, both km-scale models show a higher fraction of strong positive trends in extreme precipitation than CMIP6 models. This is a promising result as CMIP6 models have previously been shown to underestimate the area fraction experiencing a strong intensification in extreme precipitation. Both ICON and IFS also show considerably more spatial detail than CMIP6, in particular along coastlines and mountain ranges, and, in some cases, even capture the influence of large rivers on change signals. 

Our results clearly demonstrate the potential of km-scale models for resolving sharp gradients in change signals, but also reveal remaining shortcomings of this new model generation. In this first analysis, we, hence, find no robust evidence that changes in daily extremes are consistently different between CMIP6 and km-scale models, but our results highlight that more and longer model experiments are needed to robustly quantify extremes in this new generation of models. These findings are particularly relevant as km-scale models are envisioned to serve as the basis for Digital Twins of Earth, which, in turn, are supposed to inform impact assessments and support mitigation and adaptation decisions.

How to cite: Brunner, L. and Fischer, E. M.: Do km-scale global models reshape our understanding of local changes in temperature and precipitation extremes?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12773, https://doi.org/10.5194/egusphere-egu26-12773, 2026.

Realistic simulations of near-surface wind speeds are important for many reasons, including an accurate characterisation of storm effects on dust-particle emissions. Km-scale models are expected to represent winds including their extremes more realistically by explicitly resolving mesoscale dynamics; however, the extent to which they outperform coarser-resolution models has not yet been systematically assessed. In this study, we conduct a multi-dataset, multi-resolution comparison of sub-daily near-surface wind speeds and the dust uplift potential (DUP) for North African dust regions for the period 1994–2014. The analysis integrates recently developed global km-scale climate simulations from ICON (Icosahedral Nonhydrostatic) and IFS (Integrated Forecasting System), reanalysis products including ERA5 (ECMWF Reanalysis v5) and MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications, Version 2), historical climate simulations from CMIP5 and CMIP6 (Coupled Model Intercomparison Projects), as well as observational data from surface meteorological stations. In addition to statistical analyses of the sub-daily winds across these datasets, we have applied a machine-learning technique to pinpoint the weather patterns that drive wind differences across the models.

The results highlight that the two kilometre-scale models ICON and IFS show an overall improved representation of observed surface wind speed distributions, along with reanalysis products, compared to coarser-resolution CMIP models. However, the level of agreement varies with region, season, and time of day. For instance, winds in the Sahel region show higher consistency with observed wind speed distributions for all models, whereas substantially larger deviations occur over the Bodélé Depression, which is the world’s most active dust source, in the coarser-resolution simulations of CMIP compared to observations. The largest inter-model differences are seen during boreal winter (December–February), when northeasterly Harmattan winds often occur, and are most pronounced during the early morning hours (06 - 09 UTC), pointing to the breakdown of nocturnal low-level jets. This work provides an assessment of the strengths and limitations of contemporary global datasets for simulating dust-relevant winds over North Africa and provides a reference framework for evaluating upcoming model output from CMIP7 historical experiments.

How to cite: Sreekumar, S., Azoulay, A., Leuzinger, A., and Fiedler, S.: Do km-scale models better simulate near-surface winds?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9952, https://doi.org/10.5194/egusphere-egu26-9952, 2026.

Climate models are an important tool to address challenges we face due to the changing climate. The global warming of the atmosphere and ocean leads to an increase in energy accessible to foster more frequent and intense tropical cyclones, extreme precipitation, and heatwaves, causing increasingly larger economic and non-economic damage. Many of those events are caused or influenced by small-scale convective processes that are not resolved in the typical CMIP-style models with resolutions of about 100 km.

Models capable of resolving deep convection and large turbulent eddies in the atmosphere require horizontal resolutions between 1 km and 10 km. Turbulent processes in the atmosphere play a major role in distributing the energy within the atmosphere, and it has been shown that atmospheric models at resolutions of about 10 km or less significantly improve the resemblance to observations, for instance, regarding the magnitude of maximum wind gusts and the statistics and characteristics of tropical cyclones. Similarly, ocean models require resolutions in the order of 10 km or finer to explicitly resolve mesoscale ocean eddies and their contributions to the transport of salinity and heat and their effects upon the global system. 

Before we can make the transient historical simulations from which future projections are typically initialized with climate models, based on a certain emission scenario, the models need to achieve a climate state that is consistent with the boundary conditions at the initial time. For this, the model needs to be gradually spun up to reach a balanced state. Traditional approaches for model tuning and spinup used for coarse resolution models cannot be applied at very high resolutions. Typical spinup times to reach model equilibrium are around 1000 years, which remains unrealistic to achieve for km-scale models until today. 

This work presents the analysis of alternative cost-efficient spinup protocols and evaluates their associated initial shocks and drifts and how efficiently the coupled model approaches the equilibrium. We also contribute to answering the question of how reliable future projections are when initialized from a transient model state. The analysis is based on a series of ensemble simulations performed with the coupled IFS-NEMO climate model at about 25 km atmospheric and ocean resolution, i.e., Tco399/eORCA025 grids, and on different combinations of ocean-only spinup and coupled spinup lengths. Our analysis focuses on spinup designs that are optimized to initialize climate projections and historical simulations of 50 to 100 years with a minimal initial adjustment and “well-behaved” model trends, contrasting them to the existing multi-decadal km-scale simulations from initiatives like Destination Earth and EERIE.

How to cite: Keller, K., Batlle, M., Ortega, P., Rocha, N., You, C., and Doblas-Reyes, F.: Climate simulations with global storm-resolving models from transient states., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1842, https://doi.org/10.5194/egusphere-egu26-1842, 2026.

Aviation turbulence leads to safety, comfort, and economic risks. For example, a recent high-profile event of a severe turbulence encountered by Singapore Airlines flight SQ321 in 2024 led to a large number of injured passengers, showing the challenge of anticipating hazardous conditions in the tropics.

Multiple studies suggest that turbulence has already increased and will continue to intensify in a warming climate, particularly over the midlatitudes, driven by changes in upper-tropospheric wind shear. However, evidence for the tropics is inconclusive and largely based on climate models with a horizontal resolution of approximately 100 km, which cannot directly resolve key atmospheric processes. Basic theory indicates that the tropical upper troposphere becomes more stable on average as the climate warms, which could suppress clear‑air turbulence. At the same time, the most extreme thunderstorm updrafts are expected to strengthen, potentially increasing turbulence in and around storms and their outflow. Together, these opposing signals leave the net impact on tropical aviation uncertain.

We address this gap using a set of global simulations at 5 km horizontal resolution, which explicitly resolve many upper-tropospheric updrafts in both convective and nearby clear-air environments. We use 40-day long simulations for present-day conditions for uniform sea-surface temperature warming of +2 °C and +4 °C. Additional simulations isolate the impact of CO₂ radiative forcing independent of SST warming, motivated by recent findings that CO₂ direct radiative effects can strengthen upper-tropospheric updrafts and reduce the upper tropospheric static stability. We focus on altitudes of 9-13 km along major flight corridors in tropics and subtropics, where most commercial aviation occurs.

Our analysis examines how the distribution and extremes of vertical velocity change both near and far from deep convection. We use updraft probability density functions and exceedance fractions for aviation-relevant thresholds, together with shear and stability diagnostics. With a global, storm‑resolving framework, we clarify how tropical upper‑tropospheric turbulence is changing and provide evidence that can guide future forecasting and route‑planning decisions in a warming climate.

How to cite: Gasparini, B. and Voigt, A.: Does a warmer climate lead to more bumpy flights in the tropics? Insights from a global km-scale global model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5941, https://doi.org/10.5194/egusphere-egu26-5941, 2026.

Simulating accurately the South Asian summer monsoon is crucial for food security of several South Asian countries yet challenging for global climate models (GCMs). The GCMs suffer from some systematic biases including dry bias in mean monsoon rainfall over the India subcontinent and excessive equatorial light rain between which the relationship was rarely discussed. Numerical experiments are conducted for one month during active monsoon with global quasi-uniform resolution of 60 km (U60 km) and 3 km (U3 km) separately. Evaluation with observations shows that U3 km reduces the dry bias over northern India and excessive light rain over the equatorial Indian Ocean (EIO) that are both prominent in U60 km. Excessive light rain in U60km contributes critically to stronger rainfall and latent heating over the EIO. A Hadley-type anomalous circulation is thus induced, whose subsidence branch suppresses updrafts and reduces moisture transport into northern India, contributing to the dry bias. The findings highlight the importance of constraining excessive light rain for regional climate projection in GCMs.

How to cite: Li, G., Zhao, C., Gu, J., Feng, J., Xu, M., Hao, X., Chen, J., An, H., Cai, W., and Geng, T.: Excessive equatorial light rain causes modeling dry bias of Indian summer monsoon rainfall, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7340, https://doi.org/10.5194/egusphere-egu26-7340, 2026.

Accurately assessing regional climate change and its associated risks, particularly over complex terrain and coastal regions, remains challenging due to large uncertainties in conventional global climate models. Kilometer-scale coupled climate modeling offers a promising pathway by explicitly resolving mesoscale atmospheric and oceanic processes, their interactions with large-scale circulation, and air-sea coupling at regional scales. Here, we present global warming simulations conducted with the coupled OpenIFS-FESOM2 climate model (AWI-CM3) at atmospheric resolutions of 31 km (TCo319), 9 km (TCo1279), and 4 km (TCo2559), combined with a variable-resolution ocean mesh ranging from 4 to 25 km. All km-scale-resolution simulations were initialized from the trajectory of the 31 km transient simulation with the same ocean configuration. Compared to 31 km simulations, the km-scale simulations exhibit substantially enhanced regional detail, including mesoscale circulation features such as sea-land breezes, their influence on coastal climate, and a clearer sensitivity of local climate responses to global warming. Our results highlight the potential of cloud-permitting, km-scale coupled modeling to improve projections of regional climate change and extremes, advance understanding of local climate sensitivity, and support climate impact assessments and adaptation strategies.

How to cite: Lee, S.-S., Moon, J.-Y., Timmermann, A., Cho, E.-B., Streffing, J., and Jung, T.: Resolving regional climate change with global kilometer-scale climate simulations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8397, https://doi.org/10.5194/egusphere-egu26-8397, 2026.

A suite of high-resolution configurations of the coupled climate model IFS-NEMO to investigate recent and future climate variability and change has been recently developed within the project EERIE (European Eddy-Rich Earth System Models) and the Destination Earth initiative. This contribution emphasises the climate responses emerging from these simulations and their sensitivity to spatial resolution and the experimental protocol considered.

The model hierarchy combines eddy-permitting (∼25 km) and eddy-rich (∼9 km) ocean components with convection-parameterised (∼25 km) and convection-permitting (∼4.5 km) atmospheric configurations, enabling a systematic assessment of resolution-dependent processes and feedbacks. Particular attention is given to how differences in model physics, resolution-aware tuning strategies, scenario forcing (i.e. SSP1-2.6 vs SSP3-7.0) and experimental design influence the simulated climate variability across configurations.

Ongoing analyses of historical simulations show enhanced performance for the higher-resolution configurations in the representation of mean-state properties, with especially clear improvements in dynamical fields. We further assess the extent to which the shorter spinup approach employed in Destination Earth, compared to EERIE, can reliably capture internal variability and externally forced responses while substantially reducing computational cost.

A systematically stronger future response of the Atlantic Meridional Overturning Circulation to external forcings is found in the eddy-resolving configurations compared to the eddy-permitting ones. Idealised control simulations with quadrupled CO2 forcing – inspired by the CMIP6 DECK experiments – also show a more pronounced temperature response at the highest resolution compared with the ∼25 km configuration, thus yielding stronger climate sensitivity.

More generally, we also briefly outline emerging applications of the kilometre-scale IFS-NEMO model in other European research projects, including TerraDT, which focuses on land–atmosphere coupling, and PREDDYCT, which investigates the role of mesoscale ocean eddies in seasonal-to-decadal climate prediction. Together, these efforts highlight the added scientific value of high-resolution climate modelling for understanding forced responses and informing future climate projections.

How to cite: Batlle, M., Becker, T., Caprioli, S., Davini, P., Dobas-Reyes, F. J., Gaya-Àvila, A., Ghosh, S., Von Hardenberg, J., Hearne, S., Keller, K., Milinski, S., Monteiro, N., Murray-Watson, R., Nurisso, M., Ortega, P., Pedruzo-Bagazgoitia, X., Pelletier, C., Peña, C., Van Thielen, G., and You, C.: A hierarchy of high-resolution IFS-NEMO configurations for analysing climate variability and change, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9694, https://doi.org/10.5194/egusphere-egu26-9694, 2026.

As part of the development of GFDL’s new high resolution, seamless weather to S2S to climate timescale coupled model,  we present the integration of GFDL’s atmospheric model SHiELD and land model LM4, enabling a suite of Earth system interactions, including extreme hydroclimate events, ecological droughts, and fires. This work details the implementation strategy and technical challenges of integrating GFDL’s LM4 with dynamic subgrid tiling capabilities within SHiELD capable of kilometer-scale global and global-nested simulation. In addition, this effort demonstrates how GFDL terrestrial components designed for implicit flux coupling could be integrated with SHiELD  physics designed for an explicit atmospheric solver. The primary objective is to extend SHiELD from an uncoupled atmospheric model, in which land processes are treated as a part of the atmospheric physics package, to a fully coupled high resolution atmosphere-ocean-land-ice-wave model leveraging GFDL’s FMS full coupler infrastructure. This enhanced coupling enables more accurate simulations of land-surface feedbacks, cryosphere and hydrological processes, and extreme weather events such as flooding and abrupt changes in aerosols emissions from fires. We demonstrate the model’s capability through validation test cases. The results underscore the importance of robust land-atmosphere coupling for high-resolution prediction and provide a framework for future development of fully coupled Earth system models of high resolution for forecast and earth system prediction applications.

How to cite: Mouallem, J., Malyshev, S., Gao, K., Tan, Z., Harris, L., Benson, R., Shevliakova, E., Zhou, L., Zadeh, N., and Chen, J.-H.: Coupling techniques in the new high-resolution SHiELD: implicit land-atmosphere coupling., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14566, https://doi.org/10.5194/egusphere-egu26-14566, 2026.

Global kilometre‑scale modelling is advancing rapidly, supported by international efforts such as the 2025 global km‑scale hackathon (HK25) and the development of km-scale models in the nextGEMS, EERIE, and Destination Earth projects. As part of HK25, ECMWF produced two dedicated global coupled IFS–FESOM simulations and one atmosphere-only IFS (AMIP) simulation, representing one of the highest‑resolution global datasets currently available. Here we present the simulation setups, describe the creation of cloud and analysis-ready datasets, and showcase some initial results.

The simulations employ a fully coupled atmosphere–ocean–sea‑ice system at 2.8 km atmospheric resolution and around 5km in the ocean, explicitly resolving mesoscale ocean eddies, tropical cyclone cold wakes, and fine‑scale sea‑ice structures. The two coupled simulations differ only in their representation of atmospheric deep convection. Cloud‑ready Zarr output on the HEALPix grid enabled efficient analysis and remote access from the different HK25 nodes word-wide, and supported a number of case studies.

These 2.8 km simulations will form a core contribution to the DYAMOND3 intercomparison, providing some of the first fully coupled global simulations at this scale for coordinated intercomparison. Beyond this, the simulations enable unprecedented investigation of ocean–atmosphere interactions, including air–sea fluxes, mesoscale SST–atmosphere coupling, and the influence of ocean variability on extreme events.

How to cite: Rackow, T., Aengenheyster, M., Becker, T., Pedruzo-Bagazgoitia, X., Dreier, N.-A., Reis, M., Wachsmann, F., and Ziemen, F.: Global 2.8 km coupled simulations with the Integrated Forecasting System, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19900, https://doi.org/10.5194/egusphere-egu26-19900, 2026.

UXarray is a community-developed Python package that extends the widely used Xarray ecosystem with native support for horizontally unstructured meshes, eliminating the need for costly, problematic regridding prior to visualization and analysis. Designed to meet the growing demands of kilometer-scale climate and weather models, UXarray aims to become a preeminent tool for the analysis, visualization, and postprocessing of Earth system data on irregular grids. It has been used in practice across a wide range of high-resolution atmospheric and ocean models, including MPAS, CAM-SE, E3SM, FESOM2, IFS, and ICON.

Recently, UXarray played a key role in the 2025 WCRP Digital Earth – Global Hackathon (DEGH), where over 600 researchers, spanning four continents, collaborated to explore km-scale outputs, contributed from 11 different modeling centers from around the world. The use of UXarray was essential to fulfilling hackathon objectives, such as promoting global collaboration, sharing best-practice in process-based analysis of km-scale simulations, developing practical km-scale analysis workflows, and facilitating model intercomparison.

This presentation will highlight UXarray’s current capabilities—including visualization tools and foundational analysis operators—share insights from the DEGH experience, outline future development plans, and highlight ways that the community can engage to shape the package moving forward.

How to cite: Clyne, J., chen, H., Eroglu, O., Jacob, R., Jain, R., Medeiros, B., Ullrich, P., and Zarzycki, C.: UXarray: A Python package for the analysis of kilometer-scale atmosphere and ocean model outputs, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15560, https://doi.org/10.5194/egusphere-egu26-15560, 2026.

We develop a variable-resolution method based on the tripolar grid to achieve fine-resolution regional simulations with limited computational resources. Based on the global ocean general circulation model LICOM3.0, we select the South China Sea (SCS) as the refined area and design five experiments to assess the impact of the variable-resolution grid on oceanic simulation. The results show that the method can retain the model capacity for global ocean simulation and obtain results in the refined region comparable to the reference global high-resolution model. Improving the resolution in the SCS from 0.1◦ to 0.02◦ significantly enhances the model performance in simulating submesoscale phenomena. The model can effectively reproduce submesoscale processes generated by frontogenesis, topographic wakes, and their seasonal variation. We uncover the effect of the submesoscale vortex train near the Luzon Strait. In summer, the vortex train tends to carry positive vorticity westward into the SCS and constrain the negative vorticity along the Kuroshio Current. In winter, the vortex train is more intrusive into the SCS with enhanced filament activities.

How to cite: Yu, J., Xie, J., Liu, H., Lin, P., Yu, Z., and Bai, J.: The simulation of the South China Sea by the variable resolution version of the global ocean general circulation model LICOM3.0, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8863, https://doi.org/10.5194/egusphere-egu26-8863, 2026.

Current observations of the Atlantic Meridional Overturning Circulation (AMOC) from the RAPID array show a long-term weakening of nearly 2 Sv since 2004, which would be expected to have produced noticeable and widespread climate impacts. However, these impacts are challenging to isolate in  observations because they are confounded by concurrent global warming signals that also induce long-term trends. To study the impacts associated with persistent AMOC weakening, studies typically rely on long runs forced with freshwater perturbations. The highly idealized nature of these experiments, together with the primary use of low resolution models, limits their applicability to AMOC-related impacts over the recent historical period. 

Here, we propose an alternative approach based on the analysis of a large ensemble of control simulations, in which the confounding anthropogenic trends are avoided. We use a total of 14 global coupled simulations from the HighResMIP exercise and the EERIE project. Eight of these simulations were performed with eddy-rich ocean configurations (with a horizontal resolution of about 8 km in mid-latitudes), while the remaining simulations represent the low-resolution counterparts of six of the former. In these runs, we first select 19-year periods in which the AMOC trends are comparable in magnitude to that observed by the RAPID array for 2005-2023 and then produce the associated composites describing the concomitant trends in sea level pressure, surface atmospheric temperature, and precipitation. We compare the composites across resolutions to determine whether and how resolving mesoscale eddy interactions enable different climate impacts. We also repeat the analyses for the few cases in which the simulated trends are at least 50 % stronger than in RAPID, to learn about the potential future changes to come if the observed weakening trend intensifies.

How to cite: Arumí-Planas, C., Martin-Martinez, E., Maraldi, B., Brotons, M., Moreno-Chamarro, E., Haarsma, R., Monteiro, N., Axness, M., Kuznetsova, D., Viñas, A., Bretonnière, P.-A., and Ortega, P.: A model-based assessment of the climate impacts of the observed AMOC weakening and their sensitivity to model resolution, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18545, https://doi.org/10.5194/egusphere-egu26-18545, 2026.

In response to increasing concentrations of carbon dioxide in the atmosphere, the ocean is estimated to take up ~2.3 Pg C yr^-1. Emerging evidence has shown that mesoscale eddies can act to significantly alter the rate of carbon uptake by the ocean; however, current model-based estimates of the anthropogenic carbon flux rely on empirically derived parameterisations of mesoscale eddies. Such parameterisations may affect modelled carbon fluxes differently to models which explicitly resolve mesoscale eddies. The rectified impact of explicitly resolved mesoscale eddies on the global anthropogenic carbon flux has not been quantified before.

We estimate how changes in ocean ventilation resulting from the explicit resolution of mesoscale eddies alter the global uptake of anthropogenic carbon by the ocean. We use the transit-time distribution approach to reconstruct the oceanic inventory of anthropogenic carbon in both an eddy-resolving (5 km resolution) and an eddy-parameterising (20 km resolution) configuration of the ICON-Ocean model. Each model is integrated using a perpetual year forcing and five boundary impulse response tracers, required for estimating the transit-time distribution.

The uptake of anthropogenic carbon in the eddy-resolving model exceeds that in the eddy-parameterising model by 0.1 Pg C yr^-1 over the period 2005–2015, which is smaller than typical inter-model differences of around ±0.5 Pg C yr^-1. The root mean square difference in column integrated inventories of anthropogenic carbon between the eddy-resolving and eddy-parameterising model is 4.3 mol m^-2, which is slightly larger than uncertainties in observational estimates of column integrated anthropogenic carbon of around ±2 mol m^-2.

Our results suggest that explicitly resolving mesoscale eddies is unlikely to produce large differences in globally integrated anthropogenic carbon inventories via ventilation changes alone. Further differences may arise from eddy-driven effects on the solubility of carbon dioxide, gas transfer velocities and the biological carbon pump — the transit-time distribution approach only describes the effects of ventilation in the physical carbon pump.

How to cite: Goldsworth, F., von Storch, J.-S., Brüggemann, N., and Haak, H.:  Ventilation by mesoscale eddies has a negligible impact on the rate at which anthropogenic carbon is sequestered within the global ocean, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5541, https://doi.org/10.5194/egusphere-egu26-5541, 2026.