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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.

We examine the influence of increased resolution on four long-standing biases using five different climate models developed within the PRIMAVERA project. The biases are the warm eastern tropical oceans, the double Intertropical Convergence Zone (ITCZ), the warm Southern Ocean, and the cold North Atlantic. Atmosphere resolution increases from ∼100–200 to ∼25–50 km, and ocean resolution increases from ∼1∘ (eddy-parametrized) to ∼0.25∘ (eddy-present). For one model, ocean resolution also reaches 1/12∘ (eddy-rich). The ensemble mean and individual fully coupled general circulation models and their atmosphere-only versions are compared with satellite observations and the ERA5 reanalysis over the period 1980–2014. The four studied biases appear in all the low-resolution coupled models to some extent, although the Southern Ocean warm bias is the least persistent across individual models. In the ensemble mean, increased resolution reduces the surface warm bias and the associated cloud cover and precipitation biases over the eastern tropical oceans, particularly over the tropical South Atlantic. Linked to this and to the improvement in the precipitation distribution over the western tropical Pacific, the double-ITCZ bias is also reduced with increased resolution. The Southern Ocean warm bias increases or remains unchanged at higher resolution, with small reductions in the regional cloud cover and net cloud radiative effect biases. The North Atlantic cold bias is also reduced at higher resolution, albeit at the expense of a new warm bias that emerges in the Labrador Sea related to excessive ocean deep mixing in the region, especially in the ORCA025 ocean model. Overall, the impact of increased resolution on the surface temperature biases is model-dependent in the coupled models. In the atmosphere-only models, increased resolution leads to very modest or no reduction in the studied biases. Thus, both the coupled and atmosphere-only models still show large biases in tropical precipitation and cloud cover, and in midlatitude zonal winds at higher resolutions, with little change in their global biases for temperature, precipitation, cloud cover, and net cloud radiative effect. Our analysis finds no clear reductions in the studied biases due to the increase in atmosphere resolution up to 25–50 km, in ocean resolution up to 0.25∘, or in both. Our study thus adds to evidence that further improved model physics, tuning, and even finer resolutions might be necessary.

For the first time, we compare the effects of four different ocean vertical mixing schemes on the mean state of the ocean and atmosphere in the Max Planck Institute Earth System Model (MPI-ESM1.2). These four schemes are namely the default Pacanowski and Philander (1981) (PP) scheme, the K-profile parameterization (KPP) from the Community Vertical Mixing (CVMix) library, a recently implemented scheme based on turbulent kinetic energy (TKE), and a recently developed prognostic scheme for internal wave dissipation, energy, and mixing (IDEMIX) to replace the often assumed constant background diffusivity in the ocean interior. In this study, the IDEMIX scheme is combined with the TKE scheme (collectively called the TKE+IDEMIX scheme) to provide an energetically more consistent framework for mixing, as it does not rely on the unwanted effect of creating spurious energy for mixing. Energetic consistency can have implications on the climate. Therefore, we focus on the effects of TKE+IDEMIX on the climate mean state and compare them with the first three schemes that are commonly used in other models but are not energetically consistent. We find warmer sea surface temperatures (SSTs) in the North Atlantic and Nordic Seas using KPP or TKE(+IDEMIX), which is related to 10 % higher overflows that cause a stronger and deeper upper cell of the Atlantic meridional overturning circulation (AMOC) and thereby an enhanced northward heat transport and higher inflow of warm and saline water from the Indian Ocean into the South Atlantic. Saltier subpolar North Atlantic and Nordic Seas lead to increased deep convection and thus to the increased overflows. Due to the warmer SSTs, the extratropics of the Northern Hemisphere become warmer with TKE(+IDEMIX), weakening the meridional gradient and thus the jet stream. With KPP, the tropics and the Southern Hemisphere also become warmer without weakening the jet stream. Using an energetically more consistent scheme (TKE+IDEMIX) produces a more heterogeneous and realistic pattern of vertical eddy diffusivity, with lower diffusivities in deep and flat-bottom basins and elevated turbulence over rough topography. IDEMIX improves in particular the diffusivity in the Arctic Ocean and reduces the warm bias in the Atlantic Water layer. We conclude that although shortcomings due to model resolution determine the global-scale bias pattern, the choice of the vertical mixing scheme may play an important role for regional biases.

Abstract This work documents the ICON‐Earth System Model (ICON‐ESM V1.0), the first coupled model based on the ICON (ICOsahedral Non‐hydrostatic) framework with its unstructured, icosahedral grid concept. The ICON‐A atmosphere uses a nonhydrostatic dynamical core and the ocean model ICON‐O builds on the same ICON infrastructure, but applies the Boussinesq and hydrostatic approximation and includes a sea‐ice model. The ICON‐Land module provides a new framework for the modeling of land processes and the terrestrial carbon cycle. The oceanic carbon cycle and biogeochemistry are represented by the Hamburg Ocean Carbon Cycle module. We describe the tuning and spin‐up of a base‐line version at a resolution typical for models participating in the Coupled Model Intercomparison Project (CMIP). The performance of ICON‐ESM is assessed by means of a set of standard CMIP6 simulations. Achievements are well‐balanced top‐of‐atmosphere radiation, stable key climate quantities in the control simulation, and a good representation of the historical surface temperature evolution. The model has overall biases, which are comparable to those of other CMIP models, but ICON‐ESM performs less well than its predecessor, the Max Planck Institute Earth System Model. Problematic biases are diagnosed in ICON‐ESM in the vertical cloud distribution and the mean zonal wind field. In the ocean, sub‐surface temperature and salinity biases are of concern as is a too strong seasonal cycle of the sea‐ice cover in both hemispheres. ICON‐ESM V1.0 serves as a basis for further developments that will take advantage of ICON‐specific properties such as spatially varying resolution, and configurations at very high resolution.

As a contribution towards improving the climate mean state of the atmosphere and the ocean in Earth system models (ESMs), we compare several coupled simulations conducted with the Max Planck Institute for Meteorology Earth System Model (MPI-ESM1.2) following the HighResMIP protocol. Our simulations allow to analyse the separate effects of increasing the horizontal resolution of the ocean (0.4 to 0.1∘) and atmosphere (T127 to T255) submodels, and the effects of substituting the Pacanowski and Philander (PP) vertical ocean mixing scheme with the K-profile parameterization (KPP). The results show clearly distinguishable effects from all three factors. The high resolution in the ocean removes biases in the ocean interior and in the atmosphere. This leads to the important conclusion that a high-resolution ocean has a major impact on the mean state of the ocean and the atmosphere. The T255 atmosphere reduces the surface wind stress and improves ocean mixed layer depths in both hemispheres. The reduced wind forcing, in turn, slows the Antarctic Circumpolar Current (ACC), reducing it to observed values. In the North Atlantic, however, the reduced surface wind causes a weakening of the subpolar gyre and thus a slowing down of the Atlantic meridional overturning circulation (AMOC), when the PP scheme is used. The KPP scheme, on the other hand, causes stronger open-ocean convection which spins up the subpolar gyres, ultimately leading to a stronger and stable AMOC, even when coupled to the T255 atmosphere, thus retaining all the positive effects of a higher-resolved atmosphere.

Abstract This paper investigates the causation for the decline of the Atlantic Meridional Overturning Circulation (AMOC) from approximately 17 Sv to about 9 Sv, when the atmospheric resolution of the Max Planck Institute‐Earth System Model is enhanced from ∼1° to ∼0.5°. The results show that the slowdown of the AMOC is caused by the cessation of deep convection. In most modeling studies, this is thought to be controlled by buoyancy fluxes in the convective regions, for example, by surface freshwater flux that is introduced locally or via enormous input from glacier or iceberg melts. While we find that freshwater is still the key to the reduction of AMOC seen in the higher‐resolution run, the freshening of the North Atlantic does not need to be directly caused by local freshwater fluxes. Instead, it can be caused indirectly through winds via a reduced wind‐driven gyre circulation and salinity transport associated to this circulation, as seen in the higher‐resolution run.

The quantification of sea-ice production in the Laptev Sea polynyas is important for the Arctic sea-ice budget and the heat loss to the atmosphere. We estimated the ice production for the winter season 2007/2008 (November–April) based on simulations with the regional climate model COSMO-CLM at a horizontal resolution of 5 km and compared it to remote sensing estimates. A reference and five sensitivity simulations were performed with different assumptions on grid-scale and subgrid-scale ice thickness considered within polynyas, using a tile approach for fractional sea ice. In addition, the impact of heat loss on the atmospheric boundary layer was investigated. About 29.1 km3 of total winter ice production was estimated for the reference simulation, which varies by up to +124 % depending on the thin-ice assumptions. For the most realistic assumptions based on remote sensing of ice thickness the ice production increases by +39 %. The use of the tile approach enlarges the area and enhances the magnitude of the heat loss from polynyas up to +110 % if subgrid-scale open water is assumed and by +20 % for realistic assumptions. This enhanced heat loss causes in turn higher ice production rates and stronger impact on the atmospheric boundary layer structure over the polynyas. The study shows that ice production is highly sensitive to the thin-ice parameterizations for fractional sea-ice cover. In summary, realistic ice production estimates could be retrieved from our simulations. Neglecting subgrid-scale energy fluxes might considerably underestimate the ice production in coastal polynyas, such as in the Laptev Sea, with possible consequences on the Arctic sea-ice budget.

To precisely map the changes in hydrologic response of catchments (e.g. water balance, reactivity or extremes), we need sensitive and interpretable indicators. In this study we defined nine hydrologically meaningful signature indices: five indices were sampled on the flow duration curve, four indices were closely linked to the distribution of event runoff coefficients. We applied these signature indices to the output from a hydrologic catchment model for three different catchments located in the Nahe basin (Western Germany) to detect differences in runoff behavior resulting from different meteorological input data. The models were driven by measured and simulated (COSMO-CLM) meteorological data. It could be shown that the application of signature indices is a very sensitive tool to assess differences in simulated runoff behavior resulting from climatic data sets of different sources. Specifically, the selected signature indices allow assessing changes in water balance, vertical water distribution, reactivity, seasonality and runoff generation. These indices showed that the hydrological model is very sensitive to biases in mean and spatio-temporal distribution of precipitation and temperature because it acts as a filter for the meteorological input. Besides model calibration and model structural deficits, we found that bias correction of temperature fields and further adjustment of bias correction of precipitation fields is absolutely essential. We conclude that signature indices can act as indirect "efficiency measures" or "similarity measures" for output from regional or local climate models.

Regional climate modeling using convection-permitting models (CPMs; horizontal grid spacing <4 km) emerges as a promising framework to provide more reliable climate information on regional to local scales compared to traditionally used large-scale models (LSMs; horizontal grid spacing >10 km). CPMs no longer rely on convection parameterization schemes, which had been identified as a major source of errors and uncertainties in LSMs. Moreover, CPMs allow for a more accurate representation of surface and orography fields. The drawback of CPMs is the high demand on computational resources. For this reason, first CPM climate simulations only appeared a decade ago. In this study, we aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic. The most important components in CPMs such as physical parameterizations and dynamical formulations are discussed critically. An overview of weaknesses and an outlook on required future developments is provided. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Improvements are evident mostly for climate statistics related to deep convection, mountainous regions, or extreme events. The climate change signals of CPM simulations suggest an increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains. In conclusion, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs.