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 debate on the sign of the soil moisture–precipitation feedback remains open. On the one hand, studies using global coarse-resolution climate models have found strong positive feedback. However, such models cannot represent convection explicitly. On the other hand, studies using km-scale regional climate models and explicit convection have reported negative feedback. Yet, the large-scale circulation is prescribed in such models. This study revisits the soil moisture–precipitation feedback using global, coupled simulations conducted for 1 y with explicit convection and compares the results to coarse-resolution simulations with parameterized convection. We find significant differences in a majority of points with feedback that is weaker and dominantly negative with explicit convection. The model with explicit convection is more often in a wet regime and prefers the triggering of convection over dry soil in the presence of soil moisture heterogeneity, in contrast to the coarse-resolution model. Further analysis indicates that the feedback not only between soil moisture and evapotranspiration but also between evapotranspiration and precipitation is weaker, in better agreement with observations. Our findings suggest that coarse-resolution models may not be well suited to study aspects of climate change over land such as changes in droughts and heatwaves.

The dilution effect caused by boundary-layer evolution over land has strong influences on air quality. Accurate and continuous measurements of the boundary-layer height over urban areas are therefore needed for complete air-quality assessments. Commercial ceilometers, in combination with reliable and simple methodologies, can be used to retrieve the mixed-layer height, and represent a means of obtaining information on vertical mixing and atmospheric structure above cities. Here, we evaluate various retrieval algorithms based on the gradient method against high-temporal-resolution radiosonde observations. Based on the results, we propose a simple algorithm by using the gradient method, the correction of background noise and the moving averages, with the minimum number of parameters that need to be adjusted to the local properties and the instrument itself. The algorithm is adjusted for Seoul, Korea, and improves the retrieval performance by reducing high-frequency noise. The algorithm is used to investigate the relationship between the evolution of the daytime mixed-layer height and air pollution under a two-layer mixing model where changes in concentration depend only on the urban boundary-layer growth and air entrainment from the free atmosphere. Using 2 months of ceilometer retrievals of mixed-layer height and air-quality data from across the city, we find strong negative correlations for primary emitted pollutants such as NO₂, CO, SO₂, and particulate matter smaller than 10 µm, and a modest positive correlation for O₃. The results provide insight into the significant influence of urban boundary-layer evolution on Seoul’s air quality.

This paper reports on the first attempt to investigate whether excessive precipitation over mountainous areas, which is a common problem in model simulations, could be remedied by the implementation of a more realistic surface wind field in the high‐resolution Weather Research and Forecasting (WRF) model. A series of 48 h short‐range forecasts was conducted for the month of July 2006 within the triple‐nested WRF configuration, for which the highest resolution of 3 km was focused on areas with complex orography over East Asian monsoonal regions. For accurate surface wind simulations, the subgrid‐scale (SGS) orography parameterization scheme was employed. It was found that the simulated surface wind showed negative (positive) bias over mountainous (flat) regions when the SGS orography parameterization was excluded. After inclusion of the SGS orography parameterization, wind speed over mountainous (flat) regions increased (decreased), implying that the bias was mitigated. Moisture divergence (convergence) over the mountains (on the leeward side of the mountains) was induced, and surface latent heat flux increased along the mountain ranges following the improvement in the representation of the surface wind by the inclusion of the SGS orography parameterization. Eventually, excessive precipitation simulated over mountainous areas of East Asia, which is a feature commonly observed in numerical model studies, was alleviated because of the moisture divergence and increased surface latent heat flux.

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.

The roughness sublayer (RSL) is one compartment of the surface layer (SL) where turbulence deviates from Monin–Obukhov similarity theory. As the computing power increases, model grid sizes approach the gray zone of turbulence in the energy-containing range and the lowest model layer is located within the RSL. From this perspective, the RSL has an important implication in atmospheric modeling research. However, it has not been explicitly simulated in atmospheric mesoscale models. This study incorporates the RSL model proposed by Harman and Finnigan (2007, 2008) into the Jiménez et al. (2012) SL scheme. A high-resolution simulation performed with the Weather Research and Forecasting model (WRF) illustrates the impacts of the RSL parameterization on the wind, air temperature, and rainfall simulation in the atmospheric boundary layer. As the roughness parameters vary with the atmospheric stability and vegetative phenology in the RSL model, our RSL implementation reproduces the observed surface wind, particularly over tall canopies in the winter season by reducing the root mean square error (RMSE) from 3.1 to 1.8 m s⁻¹. Moreover, the improvement is relevant to air temperature (from 2.74 to 2.67 K of RMSE) and precipitation (from 140 to 135 mm per month of RMSE). Our findings suggest that the RSL must be properly considered both for better weather and climate simulations and for the application of wind energy and atmospheric dispersion.