Abstract. Quantifying global cloud condensation nuclei (CCN) concentrations is crucial for reducing uncertainties in radiative forcing resulting from aerosol-cloud interactions. This study analyzes two novel, independent, open-source global CCN datasets derived from spaceborne Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements and Copernicus Atmosphere Monitoring Service (CAMS) reanalysis and examines the spatio-temporal variability of CCN concentrations pertinent to liquid clouds. The results reveal consistent large-scale patterns in both CALIOP and CAMS datasets, although CALIOP values are approximately 79 % higher than those from CAMS. Comparisons with existing literature demonstrate that these datasets effectively bound the regionally observed CCN concentrations, with CALIOP typically representing the upper bound and CAMS the lower bound. Monthly and annual variations in CCN concentrations obtained from the two datasets largely agree over the Northern Hemisphere and align with previously reported variations. However, inconsistencies emerge over pristine oceans, particularly in the Southern Hemisphere, where the datasets show not only opposing seasonal changes but also contrasting annual trends. A closure study of trends in CCN and cloud droplet concentrations suggests that dust-influenced and pristine-maritime environments primarily limit our current understanding of CCN-cloud-droplet relationships. Long-term CCN observations in these regions are crucial for improving global datasets and advancing our understanding of aerosol-cloud interactions.

Determining number concentrations of cloud condensation nuclei (CCN) is one of the first steps in the chain in analysis of cloud droplet formation, the direct microphysical link between aerosols and cloud droplets, and a process key for aerosol–cloud interactions (ACI). However, due to sparse coverage of in situ measurements and difficulties associated with retrievals from satellites, a global exploration of their magnitude, source as well as temporal and spatial distribution cannot be easily obtained. Thus, a better representation of CCN numbers is one of the goals for quantifying ACI processes and achieving uncertainty-reduced estimates of their associated radiative forcing. Here, we introduce a new CCN dataset which is derived based on aerosol mass mixing ratios from the latest Copernicus Atmosphere Monitoring Service reanalysis (CAMSRA) in a diagnostic model that uses CAMSRA aerosol properties and a simplified kappa-Köhler framework suitable for global models. The emitted aerosols in CAMSRA are not only based on input from emission inventories using aerosol observations, they also have a strong tie to satellite-retrieved aerosol optical depth (AOD) as this is assimilated as a constraining factor in the reanalysis. Furthermore, the reanalysis interpolates for cases of poor or missing retrievals and thus allows for a full spatiotemporal quantification of CCN numbers. The derived CCN dataset captures the general trend and spatial and temporal distribution of total CCN number concentrations and CCN from different aerosol species. A brief evaluation with ground-based in situ measurements demonstrates the improvement of the modelled CCN over the sole use of AOD as a proxy for CCN as the overall correlation coefficient improved from 0.37 to 0.71. However, we find the modelled CCN from CAMSRA to be generally high biased and find a particular erroneous overestimation at one heavily polluted site which emphasises the need for further validation. The CCN dataset (https://doi.org/10.26050/WDCC/QUAERERE_CCNCAMS_v1, Block, 2023), which is now freely available to users, features 3-D CCN number concentrations of global coverage for various supersaturations and aerosol species covering the years 2003–2021 with daily frequency. This dataset is one of its kind as it offers lots of opportunities to be used for evaluation in models and in ACI studies.

AbstractSince the 5th Assessment Report of the Intergovernmental Panel on Climate Change (AR5) an extended concept of the energetic analysis of climate change including forcings, feedbacks and adjustment processes has become widely adopted. Adjustments are defined as processes that occur in response to the introduction of a climate forcing agent, but that are independent of global‐mean surface temperature changes. Most considered are the adjustments that impact the Earth energy budget and strengthen or weaken the instantaneous radiative forcing due to the forcing agent. Some adjustment mechanisms also impact other aspects of climate not related to the Earth radiation budget. Since AR5 and a following description by Sherwood et al. (2015, https://doi.org/10.1175/bams‐d‐13‐00167.1), much research on adjustments has been performed and is reviewed here. We classify the adjustment mechanisms into six main categories, and discuss methods of quantifying these adjustments in terms of their potentials, shortcomings and practicality. We furthermore describe aspects of adjustments that act beyond the energetic framework, and we propose new ideas to observe adjustments or to make use of observations to constrain their representation in models. Altogether, the problem of adjustments is now on a robust scientific footing, and better quantification and observational constraint is possible. This allows for improvements in understanding and quantifying climate change.

The climate effects of atmospheric aerosol particles serving as cloud condensation nuclei (CCN) depend on chemical composition and hygroscopicity, which are highly variable on spatial and temporal scales. Here we present global CCN measurements, covering diverse environments from pristine to highly polluted conditions. We show that the effective aerosol hygroscopicity, κ , can be derived accurately from the fine aerosol mass fractions of organic particulate matter ( ϵ org ) and inorganic ions ( ϵ inorg ) through a linear combination, κ = ϵ org ⋅ κ org + ϵ inorg ⋅ κ inorg . In spite of the chemical complexity of organic matter, its hygroscopicity is well captured and represented by a global average value of κ org = 0.12 ± 0.02 with κ inorg = 0.63 ± 0.01 as the corresponding value for inorganic ions. By showing that the sensitivity of global climate forcing to changes in κ org and κ inorg is small, we constrain a critically important aspect of global climate modelling.

Since increased anthropogenic aerosol result in an enhancement in cloud droplet number concentration, cloud and precipitation process are modified. It is unclear how exactly cloud liquid water path (LWP) and cloud fraction respond to aerosol perturbations. A large volcanic eruption may help to better understand and quantify the cloud response to external perturbations, with a focus on the short-term cloud adjustments . Volcloud is one of the research projects in the Vollmpact collaborative German research unit which aims to the improve understanding of how the climate system responds to volcanic eruptions. This includes skills in satellite remote sensing of atmospheric composition, stratospheric aerosol parameters and clouds as well as in modelling of aerosol microphysical and cloud processes, and in climate modelling. The goal of VolCloud is to understand and quantify the response of clouds to volcanic eruptions and to thereby advance the fundamental understanding of the cloud response to external forcing, particularly aerosol-cloud interactions. In this study we used ICON-NWP atmospheric model at a cloud-system-resolving resolution of 2.5 km horizontally, to simulate the region around the Holuhraun volcano for the duration of one week (1 – 7 September 2014). The pair of simulations, with and without the volcanic aerosol emissions allowed us to assess the simulated effective radiative forcing and its mechanisms as well as its impact on adjustments of cloud liquid water path and cloud fraction to the perturbations of cloud droplet number concentration. In this case studies liquid water path positively correlates with enhanced cloud droplet concentration.

Clouds are highly variable in time and space, affecting climate sensitivity and climate change. To study and distinguish the different influences of clouds on the climate system, it is useful to separate clouds into individual cloud regimes. In this work we present a new cloud classification for liquid water clouds at cloud scale defined using cloud parameters retrieved from combined satellite measurements from CloudSat and CALIPSO. The idea is that cloud heterogeneity is a measure that allows us to distinguish cumuliform and stratiform clouds, and cloud-base height is a measure to distinguish cloud altitude. The approach makes use of a newly developed cloud-base height retrieval. Using three cloud-base height intervals and two intervals of cloud-top variability as an inhomogeneity parameter provides six new liquid cloud classes. The results show a smooth transition between marine and continental clouds as well as between stratiform and cumuliform clouds in different latitudes at the high spatial resolution of about 20 km. Analysing the micro- and macrophysical cloud parameters from collocated combined MODIS, CloudSat and CALIPSO retrievals shows distinct characteristics for each cloud regime that are in agreement with expectation and literature. This demonstrates the usefulness of the classification.

Global climate models show that the lapse rate feedback is a key reason for Arctic amplificati n of global warming. However, a proper assessment of the underlying spatial and temporal structure of the vertically non-uniform temperature change is still lacking. In this study we use the output from several CMIP5 climate models to investigate the Arctic lapse rate change in the context of global warming forced by CO2. Comparisons between the perturbed and unperturbed states show that in the Arctic the temperature increases more near the surface than aloft, especially over ice-covered ocean and Arctic land. The bottom-heavy warming is most pronounced in boreal winter and is also seen in spring and autumn but to a lesser extent. The atmosphere over these areas is characterised by an inversion layer. We f nd that the inversion strength in the unperturbed climate and the change of the temperature lapse rate from unperturbed to perturbed state correlate to each other across the model ensemble over ice-covered ocean, open ocean and for sea ice retreat regions. However, the models simulate no correlation for the entire Arctic. Further investigation of the surface energy budget for models with weak and strong inversion strengths, respectively, show that the surface energy storage and the increase of turbulent heat f uxes which enhance the downward longwave radiation contribute most to the warming at the surface.

Climate feedbacks have been found to strongly impact the observed amplified Arctic warming. However, Arctic amplification is modeled with a wide spread which partly arises from intermodel differences of the various feedbacks. To explain the spread in modeled Arctic warming, feedback uncertainties and their origins are investigated in 13 climate models in an experiment with abruptly quadrupled CO2. While intermodel differences in the cloud feedback, being strongest in the Tropics, have been found to determine the spread of global mean effective climate sensitivity, we find that in the Arctic the cloud feedback is not responsible for the spread of Arctic warming as its contribution is too small. Instead, the spread of Arctic warming is explained by differing estimates of surface albedo and Planck feedbacks which show the largest intermodel differences. Our results indicate that these uncertainties not only arise from different degrees of simulated Arctic warming but also are partly related to the large differences in initial sea ice cover and surface temperatures which contribute to the increased spread in estimated warming compared to lower latitudes. Further investigations of feedback dependencies to the base state are needed to constrain the impact of initial uncertainties and to obtain robust results. The most significant distinction between models is the sign of the total feedback parameter. While all models investigated here simulate a negative global mean total feedback, only half of them also show negative Arctic feedbacks which implies that Arctic local feedbacks alone suffice to stably adjust Arctic surface temperatures in response to a radiative perturbation. The other half exhibits positive total Arctic feedbacks indicating local runaway systems which need to be balanced by decreased meridional heat transports. Whether or not a model features such a behaviour depends upon the strength of the simulated positive surface albedo versus the negative Planck feedback.

In its fifth assessment report (AR5), the Intergovernmental Panel on Climate Change provides a best estimate of the effective radiative forcing (ERF) due to anthropogenic aerosol at -0.9Wm(-2). This value is considerably weaker than the estimate of -1.2Wm(-2) in AR4. A part of the difference can be explained by an offset of +0.2Wm(-2) which AR5 added to all published estimates that only considered the solar spectrum, in order to account for adjustments in the terrestrial spectrum. We find that, in the CMIP5 multimodel median, the ERF in the terrestrial spectrum is small, unless microphysical effects on ice- and mixed-phase clouds are parameterized. In the latter case it is large but accompanied by a very strong ERF in the solar spectrum. The total adjustments can be separated into microphysical adjustments (aerosol effects) and thermodynamic adjustments. Using a kernel technique, we quantify the latter and find that the rapid thermodynamic adjustments of water vapor and temperature profiles are small. Observation-based constraints on these model results are urgently needed.

An overview of radiative climate feedbacks and ocean heat uptake efficiency diagnosed from idealized transient climate change experiments of 14 CMIP5 models is presented. Feedbacks explain about two times more variance in transient climate response across the models than ocean heat uptake efficiency. Cloud feedbacks can clearly be identified as the main source of inter-model spread. Models with strong longwave feedbacks in the tropics feature substantial increases in cloud ice around the tropopause suggestive of changes in cloud-top heights. The lifting of the tropical tropopause goes together with a general weakening of the tropical circulation. Distinctive inter-model differences in cloud shortwave feedbacks occur in the subtropics including the equatorward flanks of the storm-tracks. Related cloud fraction changes are not confined to low clouds but comprise middle level clouds as well. A reduction in relative humidity through the lower and mid troposphere can be identified as being the main associated large-scale feature. Experiments with prescribed sea surface temperatures are analyzed in order to investigate whether the diagnosed feedbacks from the transient climate simulations contain a tropospheric adjustment component that is not conveyed through the surface temperature response. The strengths of the climate feedbacks computed from atmosphere-only experiments with prescribed increases in sea surface temperatures, but fixed CO2 concentrations, are close to the ones derived from the transient experiment. Only the cloud shortwave feedback exhibits discernible differences which, however, can not unequivocally be attributed to tropospheric adjustment to CO2. Although for some models a tropospheric adjustment component is present in the global mean shortwave cloud feedback, an analysis of spatial patterns does not lend support to the view that cloud feedbacks are dominated by their tropospheric adjustment part. Nevertheless, there is positive correlation between the strength of tropospheric adjustment processes and cloud feedbacks across different climate models.

ECHAM6, the sixth generation of the atmospheric general circulation model ECHAM, is described. Major changes with respect to its predecessor affect the representation of shortwave radiative transfer, the height of the model top. Minor changes have been made to model tuning and convective triggering. Several model configurations, differing in horizontal and vertical resolution, are compared. As horizontal resolution is increased beyond T63, the simulated climate improves but changes are incremental; major biases appear to be limited by the parameterization of small‐scale physical processes, such as clouds and convection. Higher vertical resolution in the middle atmosphere leads to a systematic reduction in temperature biases in the upper troposphere, and a better representation of the middle atmosphere and its modes of variability. ECHAM6 represents the present climate as well as, or better than, its predecessor. The most marked improvements are evident in the circulation of the extratropics. ECHAM6 continues to have a good representation of tropical variability. A number of biases, however, remain. These include a poor representation of low‐level clouds, systematic shifts in major precipitation features, biases in the partitioning of precipitation between land and sea (particularly in the tropics), and midlatitude jets that appear to be insufficiently poleward. The response of ECHAM6 to increasing concentrations of greenhouse gases is similar to that of ECHAM5. The equilibrium climate sensitivity of the mixed‐resolution (T63L95) configuration is between 2.9 and 3.4 K and is somewhat larger for the 47 level model. Cloud feedbacks and adjustments contribute positively to warming from increasing greenhouse gases.