Modeling the tropospheric multiphase aerosol-cloud processing using the 3-D chemistry transport model COSMO-MUSCAT

Die chemische Zusammensetzung und die physikalischen Eigenschaften von troposphärischen Gasen, Partikeln und Wolken hängen aufgrund zahlreicher Prozesse stark voneinander ab. Insbesondere chemische Multiphasenprozesse in Wolken können die physiko-chemischen Eigenschaften der Luft und troposphärischer Partikel klein- und großräumig verändern. Diese chemische Prozessierung des troposphärischen Aerosols innerhalb von Wolken beeinflusst die chemischen Umwandlungen in der Atmosphäre, die Bildung von Wolken, deren Ausdehnung und Lebensdauer, sowie die Transmissivität von einfallender und ausgehender Strahlung durch die Atmosphäre. Damit sind wolken-chemische Prozesse relevant für das Klima auf der Erde und für verschiedene Umweltaspekte. Daher ist ein umfassendes Verständnis dieser Prozesse wichtig. Die explizite Behandlung chemischer Reaktionen in der Flüssigphase stellt allerdings eine Herausforderung für atmosphärische Computermodelle dar. Detaillierte Beschreibungen der Flüssigphasenchemie werden deshalb häufig nur für Boxmodelle verwendet. Regionale Chemie-Transport-Modelle und Klimamodelle berücksichtigen diese Prozesse meist nur mit vereinfachten chemischen Mechanismen oder Parametrisierungen. Die vorliegende Arbeit hat zum Ziel, den Einfluss der chemischer Mehrphasenprozesse innerhalb von Wolken auf den Verbleib relevanter Spurengase und Partikelbestandteile mit Hilfe des state‑of‑the‑art 3D-Chemie-Transport-Modells COSMO-MUSCAT zu untersuchen. Zu diesem Zweck wurde das Model um eine detaillierte Beschreibung chemischer Prozesse in der Flüssigphase erweitert. Zusätzlich wurde das bestehende Depositionsschema verbessert, um auch die Deposition von Nebeltropfen zu berücksichtigen. Die durchgeführten Modellerweiterungen ermöglichen eine bessere Beschreibung des troposphärischen Multiphasensystems. Das erweiterte Modellsystem wurde sowohl für künstliche 2D-Bergüberströmungsszenarien als auch für reale 3D-Simulationen angewendet. Mittels Prozess- und Sensitivitätsstudien wurde der Einfluss (i) des Detailgrades der verwendeten Mechanismen zur Beschreibung der Flüssigphasenchemie, (ii) der Größenauflösung des Tropfenspektrums und (iii) der Tropfenanzahl auf die chemischen Modellergebnisse untersucht. Die Studien belegen, dass die Auswirkungen der Wolkenchemie aufgrund ihres signifikanten Einflusses auf die Oxidationskapazität in der Gas- und Flüssigphase, die Bildung von organischer und anorganischer Partikelmasse sowie die Azidität der Wolkentropfen und Partikel in regionalen Chemie-Transport-Modellen berücksichtigt werden sollten. Im Vergleich zu einer vereinfachten Beschreibung der Wolkenchemie führt die Verwendung des detaillierten chemischen Flüssigphasenmechanismus C3.0RED zu verringerten Konzentrationen wichtiger Oxidantien in der Gasphase, einer höheren Nitratmasse in der Nacht, geringeren nächtlichen pH-Werten und einer veränderten Sulfatbildung. Darüber hinaus ermöglicht eine detaillierte Wolkenchemie erst Untersuchungen zur Bildung sekundärer organischer Partikelmasse in der Flüssigphase. Die größenaufgelöste Behandlung der Flüssigphasenchemie hatte nur geringen Einfluss auf die chemischen Modellergebnisse. Schließlich wurde das erweiterte Modell für Fallstudien zur Feldmesskampagne HCCT‑2010 genutzt. Zum ersten Mal wurde dabei ein chemischer Mechanismus mit der Komplexität von C3.0RED verwendet. Die räumlichen Effekte realer Wolken z. B. auf troposphärische Oxidantien oder die Bildung anorganischer Masse wurden untersucht. Der Vergleich der Modellergebnisse mit verfügbaren Messungen hat viele Übereinstimmungen aber auch interessante Unterschiede aufgezeigt, die weiter untersucht werden müssen.In the troposphere, a vast number of interactions between gases, particles, and clouds affect their physico-chemical properties, which, therefore, highly depend on each other. Particularly, multiphase chemical processes within clouds can alter the physico-chemical properties of the gas and the particle phase from the local to the global scale. This cloud processing of the tropospheric aerosol may, therefore, affect chemical conversions in the atmosphere, the formation, extent, and lifetime of clouds, as well as the interaction of particles and clouds with incoming and outgoing radiation. Considering the relevance of these processes for Earth\''s climate and many environmental issues, a detailed understanding of the chemical processes within clouds is important. However, the treatment of aqueous phase chemical reactions in numerical models in a comprehensive and explicit manner is challenging. Therefore, detailed descriptions of aqueous chemistry are only available in box models, whereas regional chemistry transport and climate models usually treat cloud chemical processes by means of rather simplified chemical mechanisms or parameterizations. The present work aims at characterizing the influence of chemical cloud processing of the tropospheric aerosol on the fate of relevant gaseous and particulate aerosol constituents using the state-of-the-art 3‑D chemistry transport model (CTM) COSMO‑MUSCAT. For this purpose, the model was enhanced by a detailed description of aqueous phase chemical processes. In addition, the deposition schemes were improved in order to account for the deposition of cloud droplets of ground layer clouds and fogs. The conducted model enhancements provide a better insight in the tropospheric multiphase system. The extended model system was applied for an artificial mountain streaming scenario as well as for real 3‑D case studies. Process and sensitivity studies were conducted investigating the influence of (i) the detail of the used aqueous phase chemical representation, (ii) the size-resolution of the cloud droplets, and (iii) the total droplet number on the chemical model output. The studies indicated the requirement to consider chemical cloud effects in regional CTMs because of their key impacts on e.g., oxidation capacity in the gas and aqueous phase, formation of organic and inorganic particulate mass, and droplet acidity. In comparison to rather simplified aqueous phase chemical mechanisms focusing on sulfate formation, the use of the detailed aqueous phase chemistry mechanism C3.0RED leads to decreased gas phase oxidant concentrations, increased nighttime nitrate mass, decreased nighttime pH, and differences in sulfate mass. Moreover, the treatment of detailed aqueous phase chemistry enables the investigation of the formation of aqueous secondary organic aerosol mass. The consideration of size-resolved aqueous phase chemistry shows only slight effects on the chemical model output. Finally, the enhanced model was applied for case studies connected to the field experiment HCCT-2010. For the first time, an aqueous phase mechanism with the complexity of C3.0RED was applied in 3‑D chemistry transport simulations. Interesting spatial effects of real clouds on e.g., tropospheric oxidants and inorganic mass have been studied. The comparison of the model output with available measurements revealed many agreements and also interesting disagreements, which need further investigations

CAPRAM reduction towards an operational multiphase halogen and dimethyl sulfide chemistry treatment in the chemistry transport model COSMO-Muscat(5.04e)

A condensed multiphase halogen and dimethyl sulfide (DMS) chemistry mechanism for application in chemistry transport models is developed by reducing the CAPRAM DMS module 1.0 (CAPRAM-DM1.0) and the CAPRAM halogen module 3.0 (CAPRAM-HM3.0). The reduction is achieved by determining the main oxidation pathways from analysing the mass fluxes of complex multiphase chemistry simulations with the air parcel model SPACCIM (SPectral Aerosol Cloud Chemistry Interaction Model). These simulations are designed to cover both pristine and polluted marine boundary layer conditions. Overall, the reduced CAPRAM-DM1.0 contains 32 gas-phase reactions, 5 phase transfers, and 12 aqueous-phase reactions, of which two processes are described as equilibrium reactions. The reduced CAPRAM-HM3.0 contains 199 gas-phase reactions, 23 phase transfers, and 87 aqueous-phase reactions. For the aqueous-phase chemistry, 39 processes are described as chemical equilibrium reactions. A comparison of simulations using the complete CAPRAM-DM1.0 and CAPRAM-HM3.0 mechanisms against the reduced ones indicates that the relative deviations are below 5 % for important inorganic and organic air pollutants and key reactive species under pristine ocean and polluted conditions. The reduced mechanism has been implemented into the chemical transport model COSMO-MUSCAT and tested by performing 2D simulations under prescribed meteorological conditions that investigate the effect of stable (stratiform cloud) and more unstable meteorological conditions (convective clouds) on marine multiphase chemistry. The simulated maximum concentration of HCl is of the order of 109 molecules cm−3 and that of BrO is around 1×107 molecules cm−3, reproducing the range of ambient measurements. Afterwards, the oxidation pathways of DMS in a cloudy marine atmosphere have been investigated in detail. The simulations demonstrate that clouds have both a direct and an indirect photochemical effect on the multiphase processing of DMS and its oxidation products. The direct photochemical effect is related to in-cloud chemistry that leads to high dimethyl sulfoxide (DMSO) oxidation rates and a subsequently enhanced formation of methane sulfonic acid compared to aerosol chemistry. The indirect photochemical effect is characterized by cloud shading, which occurs particularly in the case of stratiform clouds. The lower photolysis rate affects the activation of Br atoms and consequently lowers the formation of BrO radicals. The corresponding DMS oxidation flux is lowered by up to 30 % under thick optical clouds. Moreover, high updraught velocities lead to a strong vertical mixing of DMS into the free troposphere predominately under cloudy conditions. The photolysis of hypohalous acids (HOX, X = Cl, Br, or I) is reduced as well, resulting in higher HOX-driven sulfite-to-sulfate oxidation in aerosol particles below stratiform clouds. Altogether, the present model simulations have demonstrated the ability of the reduced mechanism to be applied in studying marine aerosol–cloud processing effects in regional models such as COSMO-MUSCAT. The reduced mechanism can be used also by other regional models for more adequate interpretations of complex marine field measurement data

Description and evaluation of a secondary organic aerosol and new particle formation scheme within TM5-MP v1.2

We have implemented and evaluated a secondary organic aerosol scheme within the chemistry transport model TM5-MP in this work. In earlier versions of TM5-MP the secondary organic aerosol (SOA) was emitted as Aitken-sized particle mass emulating the condensation. In the current scheme we simulate the formation of secondary organic aerosol from oxidation of isoprene and monoterpenes by ozone and hydroxyl radicals, which produce semi-volatile organic compounds (SVOCs) and extremely low-volatility compounds (EVOCs). Subsequently, SVOCs and ELVOCs can condense on particles. Furthermore, we have introduced a new particle formation mechanism depending on the concentration of ELVOCs. For evaluation purposes, we have simulated the year 2010 with the old and new scheme; we see an increase in simulated production of SOA from 39.9 Tg yr(-1) with the old scheme to 52.5 Tg yr(-1) with the new scheme. For more detailed analysis, the particle mass and number concentrations and their influence on the simulated aerosol optical depth are compared to observations. Phenomenologically, the new particle formation scheme implemented here is able to reproduce the occurrence of observed particle formation events. However, the modelled concentrations of formed particles are clearly lower than in observations, as is the subsequent growth to larger sizes. Com - pared to the old scheme, the new scheme increases the number concentrations across the observation stations while still underestimating the observations. The organic aerosol mass concentrations in the US show a much better seasonal cycle and no clear overestimation of mass concentrations anymore. In Europe the mass concentrations are lowered, leading to a larger underestimation of observations. Aerosol optical depth (AOD) is generally slightly increased except in the northern high latitudes. This brings the simulated annual global mean AOD closer to the observational estimate. However, as the increase is rather uniform, biases tend to be reduced only in regions where the model underestimates the AOD. Furthermore, the correlations with satellite retrievals and ground-based sun-photometer observations of AOD are improved. Although the process-based approach to SOA formation causes a reduction in model performance in some areas, overall the new scheme improves the simulated aerosol fields.Peer reviewe

Large difference in aerosol radiative effects from BVOC-SOA treatment in three Earth system models

Biogenic volatile organic compounds (BVOCs) emitted from vegetation are oxidised in the atmosphere and can form aerosol particles either by contributing to new particle formation or by condensing onto existing aerosol particles. As the understanding of the importance of BVOCs for aerosol formation has increased over the years, these processes have made their way into Earth system models (ESMs). In this study, sensitivity experiments are run with three different ESMs (the Norwegian Earth System Model (NorESM), EC-Earth and ECHAM) to investigate how the direct and indirect aerosol radiative effects are affected by changes in the formation of secondary organic aerosol (SOA) from BVOCs. In the first two sensitivity model experiments, the yields of SOA precursors from oxidation of BVOCs are changed by ±50 %. For the third sensitivity test, the formed oxidation products do not participate in the formation of new particles but are only allowed to condense onto existing aerosols. In the last two sensitivity experiments, the emissions of BVOC compounds (isoprene and monoterpenes) are turned off, one at a time. The goal of the study is to investigate whether it is of importance to treat SOA formation processes correctly in the models rather than to evaluate the correctness of the current treatment in the models. The results show that the impact on the direct radiative effect (DRE) is linked to the changes in the SOA production in the models, where more SOA leads to a stronger DRE and vice versa. However, the magnitude by which the DRE changes (maximally 0.15 W m-2 globally averaged) in response to the SOA changes varies between the models, with EC-Earth displaying the largest changes. The results for the cloud radiative effects (CREs) are more complicated than for the DRE. The changes in CRE differ more among the ESMs, and for some sensitivity experiments they even have different signs. The most sensitive models are NorESM and EC-Earth, which have CRE changes of up to 0.82 W m-2. The varying responses in the different models are connected to where in the aerosol size distributions the changes in mass and number due to SOA formation occur, in combination with the aerosol number concentration levels in the models. We also find that interactive gas-phase chemistry as well as the new particle formation parameterisation has important implications for the DRE and CRE in some of the sensitivity experiments. The results from this study indicate that BVOC-SOA treatment in ESMs can have a substantial impact on the modelled climate but that the sensitivity varies greatly between the models. Since BVOC emissions have changed historically and will continue to change in the future, the spread in model results found in this study implies uncertainty into ESM estimates of aerosol forcing from land-use change and BVOC feedback strengths. © Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License

Important role of stratospheric injection height for the distribution and radiative forcing of smoke aerosol from the 2019–2020 Australian wildfires

More than 1 Tg smoke aerosol was emitted into the atmosphere by the exceptional 2019–2020 southeastern Australian wildfires. Triggered by the extreme fire heat, several deep pyroconvective events carried the smoke directly into the stratosphere. Once there, smoke aerosol remained airborne considerably longer than in lower atmospheric layers. The thick plumes traveled eastward, thereby being distributed across the high and mid-latitudes in the Southern Hemisphere, enhancing the atmospheric opacity. Due to the increased atmospheric lifetime of the smoke plume, its radiative effect increased compared to smoke that remains in lower altitudes. Global models describing aerosol-climate impacts lack adequate descriptions of the emission height of aerosols from intense wildfires. Here, we demonstrate, by a combination of aerosol-climate modeling and lidar observations, the importance of the representation of those high-altitude fire smoke layers for estimating the atmospheric energy budget. Through observation-based input into the simulations, the Australian wildfire emissions by pyroconvection are explicitly prescribed to the lower stratosphere in different scenarios. Based on our simulations, the 2019–2020 Australian fires caused a significant top-of-atmosphere (TOA) hemispheric instantaneous direct radiative forcing signal that reached a magnitude comparable to the radiative forcing induced by anthropogenic absorbing aerosol. Up to +0.50 W m−2 instantaneous direct radiative forcing was modeled at TOA, averaged for the Southern Hemisphere (+0.25 W m−2 globally) from January to March 2020 under all-sky conditions. At the surface, on the other hand, an instantaneous solar radiative forcing of up to −0.81 W m−2 was found for clear-sky conditions, with the respective estimates depending on the model configuration and subject to the model uncertainties in the smoke optical properties. Since extreme wildfires are expected to occur more frequently in the rapidly changing climate, our findings suggest that high-altitude wildfire plumes must be adequately considered in climate projections in order to obtain reasonable estimates of atmospheric energy budget changes

EC-Earth3-AerChem: a global climate model with interactive aerosols and atmospheric chemistry participating in CMIP6

This paper documents the global climate model EC-Earth3-AerChem, one of the members of the EC-Earth3 family of models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6). EC-Earth3-AerChem has interactive aerosols and atmospheric chemistry and contributes to the Aerosols and Chemistry Model Intercomparison Project (AerChemMIP). In this paper, we give an overview of the model, describe in detail how it differs from the other EC-Earth3 configurations, and outline the new features compared with the previously documented version of the model (EC-Earth 2.4). We explain how the model was tuned and spun up under preindustrial conditions and characterize the model's general performance on the basis of a selection of coupled simulations conducted for CMIP6. The net energy imbalance at the top of the atmosphere in the preindustrial control simulation is on average −0.09 W m−2 with a standard deviation due to interannual variability of 0.25 W m−2, showing no significant drift. The global surface air temperature in the simulation is on average 14.08 ∘C with an interannual standard deviation of 0.17 ∘C, exhibiting a small drift of 0.015 ± 0.005 ∘C per century. The model's effective equilibrium climate sensitivity is estimated at 3.9 ∘C, and its transient climate response is estimated at 2.1 ∘C. The CMIP6 historical simulation displays spurious interdecadal variability in Northern Hemisphere temperatures, resulting in a large spread across ensemble members and a tendency to underestimate observed annual surface temperature anomalies from the early 20th century onwards. The observed warming of the Southern Hemisphere is well reproduced by the model. Compared with the ECMWF (European Centre for Medium-Range Weather Forecasts) Reanalysis version 5 (ERA5), the surface air temperature climatology for 1995–2014 has an average bias of −0.86 ± 0.05 ∘C with a standard deviation across ensemble members of 0.35 ∘C in the Northern Hemisphere and 1.29 ± 0.02 ∘C with a corresponding standard deviation of 0.05 ∘C in the Southern Hemisphere. The Southern Hemisphere warm bias is largely caused by errors in shortwave cloud radiative effects over the Southern Ocean, a deficiency of many climate models. Changes in the emissions of near-term climate forcers (NTCFs) have significant effects on the global climate from the second half of the 20th century onwards. For the SSP3-7.0 Shared Socioeconomic Pathway, the model gives a global warming at the end of the 21st century (2091–2100) of 4.9 ∘C above the preindustrial mean. A 0.5 ∘C stronger warming is obtained for the AerChemMIP scenario with reduced emissions of NTCFs. With concurrent reductions of future methane concentrations, the warming is projected to be reduced by 0.5 ∘C

EC-Earth3-AerChem : a global climate model with interactive aerosols and atmospheric chemistry participating in CMIP6

This paper documents the global climate model EC-Earth3-AerChem, one of the members of the EC-Earth3 family of models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6). EC-Earth3-AerChem has interactive aerosols and atmospheric chemistry and contributes to the Aerosols and Chemistry Model Intercomparison Project (AerChemMIP). In this paper, we give an overview of the model, describe in detail how it differs from the other EC-Earth3 configurations, and outline the new features compared with the previously documented version of the model (EC-Earth 2.4). We explain how the model was tuned and spun up under preindustrial conditions and characterize the model's general performance on the basis of a selection of coupled simulations conducted for CMIP6. The net energy imbalance at the top of the atmosphere in the preindustrial control simulation is on average 0.09 Wm(-2) with a standard deviation due to interannual variability of 0.25 Wm(-2), showing no significant drift. The global surface air temperature in the simulation is on average 14.08 degrees C with an interannual standard deviation of 0.17 degrees C, exhibiting a small drift of 0.015 +/- 0.005 degrees C per century. The model's effective equilibrium climate sensitivity is estimated at 3.9 degrees C, and its transient climate response is estimated at 2.1 degrees C. The CMIP6 historical simulation displays spurious interdecadal variability in Northern Hemisphere temperatures, resulting in a large spread across ensemble members and a tendency to underestimate observed annual surface temperature anomalies from the early 20th century onwards. The observed warming of the Southern Hemisphere is well reproduced by the model. Compared with the ECMWF (European Centre for Medium-Range Weather Forecasts) Reanalysis version 5 (ERA5), the surface air temperature climatology for 1995-2014 has an average bias of -0.86 +/- 0.05 degrees C with a standard deviation across ensemble members of 0.35 degrees C in the North-ern Hemisphere and 1.29 +/- 0.02 degrees C with a corresponding standard deviation of 0.05 degrees C in the Southern Hemisphere. The Southern Hemisphere warm bias is largely caused by errors in shortwave cloud radiative effects over the Southern Ocean, a deficiency of many climate models. Changes in the emissions of near-term climate forcers (NTCFs) have significant effects on the global climate from the second half of the 20th century onwards. For the SSP3-7.0 Shared Socioeconomic Pathway, the model gives a global warming at the end of the 21st century (2091-2100) of 4.9 degrees C above the preindustrial mean. A 0.5 degrees C stronger warming is obtained for the AerChemMIP scenario with reduced emissions of NTCFs. With concurrent reductions of future methane concentrations, the warming is projected to be reduced by 0.5 degrees C.Peer reviewe

Constraining the Twomey effect from satellite observations: issues and perspectives

The Twomey effect describes the radiative forcing associated with a change in cloud albedo due to an increase in anthropogenic aerosol emissions. It is driven by the perturbation in cloud droplet number concentration (1Nd; ant) in liquid-water clouds and is currently understood to exert a cooling effect on climate. The Twomey effect is the key driver in the effective radiative forcing due to aerosol–cloud interactions, but rapid adjustments also contribute. These adjustments are essentially the responses of cloud fraction and liquid water path to 1Nd; ant and thus scale approximately with it. While the fundamental physics of the influence of added aerosol particles on the droplet concentration (Nd) is well described by established theory at the particle scale (micrometres), how this relationship is expressed at the large-scale (hundreds of kilometres) perturbation, 1Nd; ant, remains uncertain. The discrepancy between process understanding at particle scale and insufficient quantification at the climate-relevant large scale is caused by co-variability of aerosol particles and updraught velocity and by droplet sink processes. These operate at scales on the order of tens of metres at which only localised observations are available and at which no approach yet exists to quantify the anthropogenic perturbation. Different atmospheric models suggest diverse magnitudes of the Twomey effect even when applying the same anthropogenic aerosol emission perturbation. Thus, observational data are needed to quantify and constrain the Twomey effect. At the global scale, this means satellite data. There are four key uncertainties in determining 1Nd; ant, namely the quantification of (i) the cloud-active aerosol – the cloud condensation nuclei (CCN) concentrations at or above cloud base, (ii) Nd, (iii) the statistical approach for inferring the sensitivity of Nd to aerosol particles from the satellite data and (iv) uncertainty in the anthropogenic perturbation to CCN concentrations, which is not easily accessible from observational data. This review discusses deficiencies of current approaches for the different aspects of the problem and proposes several ways forward: in terms of CCN, retrievals of optical quantities such as aerosol optical depth suffer from a lack of vertical resolution, size and hygroscopicity information, non-direct relation to the concentration of aerosols, difficulty to quantify it within or below clouds, and the problem of insufficient sensitivity at low concentrations, in addition to retrieval errors. A future path forward can include utilising co-located polarimeter and lidar instruments, ideally including high-spectral-resolution lidar capability at two wavelengths to maximise vertically resolved size distribution information content. In terms of Nd, a key problem is the lack of operational retrievals of this quantity and the inaccuracy of the retrieval especially in broken-cloud regimes. As for the Nd-to-CCN sensitivity, key issues are the updraught distributions and the role of Nd sink processes, for which empirical assessments for specific cloud regimes are currently the best solutions. These considerations point to the conclusion that past studies using existing approaches have likely underestimated the true sensitivity and, thus, the radiative forcing due to the Twomey effect

Detection and attribution of aerosol-cloud interactions in large-domain large-eddy simulations with the ICOsahedral Non-hydrostatic model

Clouds and aerosols contribute the largest uncertainty to current estimates and interpretations of the Earth’s changing energy budget. Here we use a new-generation large-domain large-eddy model, ICON-LEM (ICOsahedral Non-hydrostatic Large Eddy Model), to simulate the response of clouds to realistic anthropogenic perturbations in aerosols serving as cloud condensation nuclei (CCN). The novelty compared to previous studies is that (i) the LEM is run in weather prediction mode and with fully interactive land surface over a large domain and (ii) a large range of data from various sources are used for the detection and attribution. The aerosol perturbation was chosen as peak-aerosol conditions over Europe in 1985, with more than fivefold more sulfate than in 2013. Observational data from various satellite and ground-based remote sensing instruments are used, aiming at the detection and attribution of this response. The simulation was run for a selected day (2 May 2013) in which a large variety of cloud regimes was present over the selected domain of central Europe. It is first demonstrated that the aerosol fields used in the model are consistent with corresponding satellite aerosol optical depth retrievals for both 1985 (perturbed) and 2013 (reference) conditions. In comparison to retrievals from ground-based lidar for 2013, CCN profiles for the reference conditions were consistent with the observations, while the ones for the 1985 conditions were not. Similarly, the detection and attribution process was successful for droplet number concentrations: the ones simulated for the 2013 conditions were consistent with satellite as well as new ground-based lidar retrievals, while the ones for the 1985 conditions were outside the observational range. For other cloud quantities, including cloud fraction, liquid water path, cloud base altitude and cloud lifetime, the aerosol response was small compared to their natural variability. Also, large uncertainties in satellite and ground-based observations make the detection and attribution difficult for these quantities. An exception to this is the fact that at a large liquid water path value (LWP > 200 g m−2), the control simulation matches the observations, while the perturbed one shows an LWP which is too large. The model simulations allowed for quantifying the radiative forcing due to aerosol–cloud interactions, as well as the adjustments to this forcing. The latter were small compared to the variability and showed overall a small positive radiative effect. The overall effective radiative forcing (ERF) due to aerosol–cloud interactions (ERFaci) in the simulation was dominated thus by the Twomey effect and yielded for this day, region and aerosol perturbation −2.6 W m$^{-2}$. Using general circulation models to scale this to a global-mean present-day vs. pre-industrial ERFaci yields a global ERFaci of −0.8 W m$^{-2}$