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Abstract We evaluate the new icosahedral nonhydrostatic atmospheric (ICON‐A) general circulation model of the Max Planck Institute for Meteorology that is flexible to be run at grid spacings from a few tens of meters to hundreds of kilometers. A simulation with ICON‐A at a low resolution (160 km) is compared to a not‐tuned fourfold higher‐resolution simulation (40 km). Simulations using the last release of the ECHAM climate model (ECHAM6.3) are also presented at two different resolutions. The ICON‐A simulations provide a compelling representation of the climate and its variability. The climate of the low‐resolution ICON‐A is even slightly better than that of ECHAM6.3. Improvements are obtained in aspects that are sensitive to the representation of orography, including the representation of cloud fields over eastern‐boundary currents, the latitudinal distribution of cloud top heights, and the spatial distribution of convection over the Indian Ocean and the Maritime Continent. Precipitation over land is enhanced, in particular at high‐resolution ICON‐A. The response of precipitation to El Niño sea surface temperature variability is close to observations, particularly over the eastern Indian Ocean. Some parameterization changes lead to improvements, for example, with respect to rain intensities and the representation of equatorial waves, but also imply a warmer troposphere, which we suggest leads to an unrealistic poleward mass shift. Many biases familiar to ECHAM6.3 are also evident in ICON‐A, namely, a too zonal SPCZ, an inadequate representation of north hemispheric blocking, and a relatively poor representation of tropical intraseasonal variability.

Abstract The MPI‐ESM1.2 is the latest version of the Max Planck Institute Earth System Model and is the baseline for the Coupled Model Intercomparison Project Phase 6 and current seasonal and decadal climate predictions. This paper evaluates a coupled higher‐resolution version (MPI‐ESM1.2‐HR) in comparison with its lower‐resolved version (MPI‐ESM1.2‐LR). We focus on basic oceanic and atmospheric mean states and selected modes of variability, the El Niño/Southern Oscillation and the North Atlantic Oscillation. The increase in atmospheric resolution in MPI‐ESM1.2‐HR reduces the biases of upper‐level zonal wind and atmospheric jet stream position in the northern extratropics. This results in a decrease of the storm track bias over the northern North Atlantic, for both winter and summer season. The blocking frequency over the European region is improved in summer, and North Atlantic Oscillation and related storm track variations improve in winter. Stable Atlantic meridional overturning circulations are found with magnitudes of ~16 Sv for MPI‐ESM1.2‐HR and ~20 Sv for MPI‐ESM1.2‐LR at 26°N. A strong sea surface temperature bias of ~5°C along with a too zonal North Atlantic current is present in both versions. The sea surface temperature bias in the eastern tropical Atlantic is reduced by ~1°C due to higher‐resolved orography in MPI‐ESM‐HR, and the region of the cold‐tongue bias is reduced in the tropical Pacific. MPI‐ESM1.2‐HR has a well‐balanced radiation budget and its climate sensitivity is explicitly tuned to 3 K. Although the obtained reductions in long‐standing biases are modest, the improvements in atmospheric dynamics make this model well suited for prediction and impact studies.

A long-standing task in climate research has been to distinguish between anthropogenic climate change and natural climate variability. A prerequisite for fulfilling this task is the understanding of the relative roles of external drivers and internal variability of climate and the carbon cycle. Here, we present the first ensemble simulations over the last 1200 years with a comprehensive Earth system model including a fully interactive carbon cycle. Applying up-to-date reconstructions of external forcing including the recent low-amplitude estimates of solar variations, the ensemble simulations reproduce temperature evolutions consistent with the range of reconstructions. The 20th-century warming trend stands out against all pre-industrial trends within the ensemble. Volcanic eruptions are necessary to explain variations in pre-industrial climate such as the Little Ice Age; yet only the strongest, repeated eruptions lead to cooling trends that differ significantly from the internal variability across all ensemble members. The simulated atmospheric CO2 concentrations exhibit a stable carbon cycle over the pre-industrial era with multi-centennial variations somewhat smaller than in the observational records. Early land-cover changes have modulated atmospheric CO2 concentrations only slightly. We provide a model-based quantification of the sensitivity (termed γ) of the global carbon cycle to temperature for a variety of climate and forcing conditions. We diagnose a distinct dependence of γ on the forcing strength and time-scales involved, thus providing a possible explanation for the systematic difference in the observational estimates for different segments of the last millennium.

We apply different aerosol and aerosol precursor emission scenarios reflecting possible future control strategies for air pollution in the ECHAM5-HAM model, and simulate the resulting effect on the Earth's radiation budget. We use two opposing future mitigation strategies for the year 2030: one in which emission reduction legislation decided in countries throughout the world are effectively implemented (current legislation; CLE 2030) and one in which all technical options for emission reductions are being implemented independent of their cost (maximum feasible reduction; MFR 2030). We consider the direct, semi-direct and indirect radiative effects of aerosols. The total anthropogenic aerosol radiative forcing defined as the difference in the top-of-the-atmosphere radiation between 2000 and pre-industrial times amounts to −2.00 W/m2. In the future this negative global annual mean aerosol radiative forcing will only slightly change (+0.02 W/m2) under the "current legislation" scenario. Regionally, the effects are much larger: e.g. over Eastern Europe radiative forcing would increase by +1.50 W/m2 because of successful aerosol reduction policies, whereas over South Asia it would decrease by −1.10 W/m2 because of further growth of emissions. A "maximum feasible reduction" of aerosols and their precursors would lead to an increase of the global annual mean aerosol radiative forcing by +1.13 W/m2. Hence, in the latter case, the present day negative anthropogenic aerosol forcing could be more than halved by 2030 because of aerosol reduction policies and climate change thereafter will be to a larger extent be controlled by greenhouse gas emissions. We combined these two opposing future mitigation strategies for a number of experiments focusing on different sectors and regions. In addition, we performed sensitivity studies to estimate the importance of future changes in oxidant concentrations and the importance of the aerosol microphysical coupling within the range of expected future changes. For changes in oxidant concentrations caused by future air pollution mitigation, we do not find a significant effect for the global annual mean radiative aerosol forcing. In the extreme case of only abating SO2 or carbonaceous emissions to a maximum feasible extent, we find deviations from additivity for the radiative forcing over anthropogenic source regions up to 10% compared to an experiment abating both at the same time.

The double-moment cloud microphysics scheme from ECHAM4 that predicts both the mass mixing ratios and number concentrations of cloud droplets and ice crystals has been coupled to the size-resolved aerosol scheme ECHAM5-HAM. ECHAM5-HAM predicts the aerosol mass, number concentrations and mixing state. The simulated liquid, ice and total water content and the cloud droplet and ice crystal number concentrations as a function of temperature in stratiform mixed-phase clouds between 0 and −35° C agree much better with aircraft observations in the ECHAM5 simulations. ECHAM5 performs better because more realistic aerosol concentrations are available for cloud droplet nucleation and because the Bergeron-Findeisen process is parameterized as being more efficient. The total anthropogenic aerosol effect includes the direct, semi-direct and indirect effects and is defined as the difference in the top-of-the-atmosphere net radiation between present-day and pre-industrial times. It amounts to −1.9 W m−2 in ECHAM5, when a relative humidity dependent cloud cover scheme and aerosol emissions representative for the years 1750 and 2000 from the AeroCom emission inventory are used. The contribution of the cloud albedo effect amounts to −0.7 W m−2. The total anthropogenic aerosol effect is larger when either a statistical cloud cover scheme or a different aerosol emission inventory are employed because the cloud lifetime effect increases.

The evolution of the global aerosol system from 1860 to 2100 is investigated through a transient atmosphere-ocean General Circulation Model climate simulation with interactively coupled atmospheric aerosol and oceanic biogeochemistry modules. The microphysical aerosol module HAM incorporates the major global aerosol cycles with prognostic treatment of their composition, size distribution, and mixing state. Based on an SRES A1B emission scenario, the global mean sulfate burden is projected to peak in 2020 while black carbon and particulate organic matter show a lagged peak around 2070. From present day to future conditions the anthropogenic aerosol burden shifts generally from the northern high-latitudes to the developing low-latitude source regions with impacts on regional climate. Atmospheric residence- and aging-times show significant alterations under varying climatic and pollution conditions. Concurrently, the aerosol mixing state changes with an increasing aerosol mass fraction residing in the internally mixed accumulation mode. The associated increase in black carbon causes a more than threefold increase of its co-single scattering albedo from 1860 to 2100. Mid-visible aerosol optical depth increases from pre-industrial times, predominantly from the aerosol fine fraction, peaks at 0.26 around the sulfate peak in 2020 and maintains a high level thereafter, due to the continuing increase in carbonaceous aerosols. The global mean anthropogenic top of the atmosphere clear-sky short-wave direct aerosol radiative perturbation intensifies to −1.1 W m−2 around 2020 and weakens after 2050 to −0.6 W m−2, owing to an increase in atmospheric absorption. The demonstrated modifications in the aerosol residence- and aging-times, the microphysical state, and radiative properties challenge simplistic approaches to estimate the aerosol radiative effects from emission projections.

This paper describes a set of sensitivity experiments to several formulations of orography. Three sets are considered: a "Standard" orography consisting of an envelope orography produced originally for the ECMWF model, a"Navy" orography directly from the US Navy data and a "Scripps" orography based on the data set originally compiled several years ago at Scripps. The last two are mean orographies which do not use the envelope enhancement. A new filtering technique for handling the problem of Gibbs oscillations in spectral models has been used to produce the "Navy" and "Scripps" orographies, resulting in smoother fields than the "Standard" orography. The sensitivity experiments show that orography is still an important factor in controlling the model performance even in this class of models that use a semi-lagrangian formulation for water vapour, that in principle should be less sensitive to Gibbs oscillations than the Eulerian formulation. The largest impact can be seen in the stationary waves (asymmetric part of the geopotential at 500 mb) where the differences in total height and spatial pattern generate up to 60 m differences, and in the surface fields where the Gibbs removal procedure is successful in alleviating the appearance of unrealistic oscillations over the ocean. These results indicate that Gibbs oscillations also need to be treated in this class of models. The best overall result is obtained using the "Navy" data set, that achieves a good compromise between amplitude of the stationary waves and smoothness of the surface fields.

A climate model's ability to reproduce observed historical warming is sometimes viewed as a measure of quality. Yet, for practical reasons it cannot be considered a purely empirical result of the modeling efforts because the desired result is known in advance and so is a potential target of tuning. Here we report how the latest edition of the Max Planck Institute for Meteorology Earth System Models (MPI-ESM1.2) atmospheric component (ECHAM6.3) had its sensitivity systematically tuned in order to improve the modeled match with the instrumental record. In practice, this was done by targeting an equilibrium climate sensitivity of about 3 K, slightly lower than in the previous model generation (MPI-ESM), which warmed more than observed, and in particular by addressing a climate sensitivity of about 7 K in an intermediate version of the model. In the process we identified several controls on cloud feedback, some of which confirm recently proposed hypotheses. We find the model exhibits excellent fidelity with the observed centennial global warming. We further find that an alternative approach with high climate sensitivity compensated by strong aerosol cooling instead would yield colder than observed results in the second half of the twentieth century., (©2020. The Authors.)

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., (©2019. The Authors.)

The climate of the North Atlantic region exhibits fluctuations on decadal timescales that have large societal consequences. Prominent examples include hurricane activity in the Atlantic, and surface-temperature and rainfall variations over North America, Europe and northern Africa. Although these multidecadal variations are potentially predictable if the current state of the ocean is known, the lack of subsurface ocean observations that constrain this state has been a limiting factor for realizing the full skill potential of such predictions. Here we apply a simple approach-that uses only sea surface temperature (SST) observations-to partly overcome this difficulty and perform retrospective decadal predictions with a climate model. Skill is improved significantly relative to predictions made with incomplete knowledge of the ocean state, particularly in the North Atlantic and tropical Pacific oceans. Thus these results point towards the possibility of routine decadal climate predictions. Using this method, and by considering both internal natural climate variations and projected future anthropogenic forcing, we make the following forecast: over the next decade, the current Atlantic meridional overturning circulation will weaken to its long-term mean; moreover, North Atlantic SST and European and North American surface temperatures will cool slightly, whereas tropical Pacific SST will remain almost unchanged. Our results suggest that global surface temperature may not increase over the next decade, as natural climate variations in the North Atlantic and tropical Pacific temporarily offset the projected anthropogenic warming.

Estimated global-scale temperature trends at Earth's surface (as recorded by thermometers) and in the lower troposphere (as monitored by satellites) diverge by up to 0.14 degrees C per decade over the period 1979 to 1998. Accounting for differences in the spatial coverage of satellite and surface measurements reduces this differential, but still leaves a statistically significant residual of roughly 0.1 degrees C per decade. Natural internal climate variability alone, as simulated in three state-of-the-art coupled atmosphere-ocean models, cannot completely explain this residual trend difference. A model forced by a combination of anthropogenic factors and volcanic aerosols yields surface-troposphere temperature trend differences closest to those observed.

Global warming caused by an increase in the concentrations of greenhouse gases, is the direct result of greenhouse gas-induced radiative forcing. When a doubling of atmospheric carbon dioxide is considered, this forcing differed substantially among 15 atmospheric general circulation models. Although there are several potential causes, the largest contributor was the carbon dioxide radiation parameterizations of the models.

Long-range global climate forecasts were made by use of a model for predicting a tropical Pacific sea-surface temperature (SST) in tandem with an atmospheric general circulation model. The SST is predicted first at long lead times into the future. These ocean forecasts are then used to force the atmospheric model and so produce climate forecasts at lead times of the SST forecasts. Prediction of seven large climatic events of the 1970s to 1990s by this technique are in good agreement with observations over many regions of the globe.

Snow feedback is expected to amplify global warming caused by increasing concentrations of atmospheric greenhouse gases. The conventional explanation is that a warmer Earth will have less snow cover, resulting in a darker planet that absorbs more solar radiation. An intercomparison of 17 general circulation models, for which perturbations of sea surface temperature were used as a surrogate climate change, suggests that this explanation is overly simplistic. The results instead indicate that additional amplification or moderation may be caused both by cloud interactions and longwave radiation. One measure of this net effect of snow feedback was found to differ markedly among the 17 climate models, ranging from weak negative feedback in some models to strong positive feedback in others.

Numerical simulations with a global atmospheric circulation model suggest that largescale variations in the amount of snowfall over Eurasia in the springtime are linked to the subsequent strength of the Asian summer monsoon. Large-scale changes in Eurasian snow cover are coupled to larger scale changes in the global climate system. There is a large, strong teleconnection to the atmospheric field over North America. The model results also show snow cover effects to subsequently alter other climatic fields known to be intimately associated with the El Niño-Southern Oscillation (ENSO) phenomenon. Thus the model results seem to challenge the current dogma that the ENSO phenomenon is solely the result of close coupling between the atmosphere and ocean by suggesting that processes over continental land masses may also have to be considered.

Understanding the cause of differences among general circulation model projections of carbon dioxide-induced climatic change is a necessary step toward improving the models. An intercomparison of 14 atmospheric general circulation models, for which sea surface temperature perturbations were used as a surrogate climate change, showed that there was a roughly threefold variation in global climate sensitivity. Most of this variation is attributable to differences in the models' depictions of cloud-climate feedback, a result that emphasizes the need for improvements in the treatment of clouds in these models if they are ultimately to be used as climatic predictors.