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Shallow clouds covering vast areas of the world's middle- and high-latitude oceans play a key role in dampening the global temperature rise associated with CO2. These clouds, which contain both ice and supercooled water, respond to a warming world by transitioning to a state with more liquid water and a greater albedo, resulting in a negative “cloud-phase” climate feedback component. Here we argue that the magnitude of the negative cloud-phase feedback component depends on the amount and nature of the small fraction of aerosol particles that can nucleate ice crystals. We propose that a concerted research effort is required to reduce substantial uncertainties related to the poorly understood sources, concentration, seasonal cycles and nature of these ice-nucleating particles (INPs) and their rudimentary treatment in climate models. The topic is important because many climate models may have overestimated the magnitude of the cloud-phase feedback, and those with better representation of shallow oceanic clouds predict a substantially larger climate warming. We make the case that understanding the present-day INP population in shallow clouds in the cold sector of cyclone systems is particularly critical for defining present-day cloud phase and therefore how the clouds respond to warming. We also need to develop a predictive capability for future INP emissions and sinks in a warmer world with less ice and snow and potentially stronger INP sources.

The largest uncertainty in the historical radiative forcing of climate is caused by the interaction of aerosols with clouds. Historical forcing is not a directly measurable quantity, so reliable assessments depend on the development of global models of aerosols and clouds that are well constrained by observations. However, there has been no systematic assessment of how reduction in the uncertainty of global aerosol models will feed through to the uncertainty in the predicted forcing. We use a global model perturbed parameter ensemble to show that tight observational constraint of aerosol concentrations in the model has a relatively small effect on the aerosol-related uncertainty in the calculated forcing between preindustrial and present-day periods. One factor is the low sensitivity of present-day aerosol to natural emissions that determine the preindustrial aerosol state. However, the major cause of the weak constraint is that the full uncertainty space of the model generates a large number of model variants that are equally acceptable compared to present-day aerosol observations. The narrow range of aerosol concentrations in the observationally constrained model gives the impression of low aerosol model uncertainty. However, these multiple “equifinal” models predict a wide range of forcings. To make progress, we need to develop a much deeper understanding of model uncertainty and ways to use observations to constrain it. Equifinality in the aerosol model means that tuning of a small number of model processes to achieve model–observation agreement could give a misleading impression of model robustness.

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth’s clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol–cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol–cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol–cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.

Feldspar minerals are shown to dominate ice nucleation by mineral dust in clouds containing both liquid water and ice particles, despite feldspar being a minor component of the dust believed to be the main source of ice nuclei. Feldspar prompts ice formation in clouds Mineral dust aerosols arising in arid regions trigger ice formation in supercooled clouds, which can influence cloud radiative properties and therefore climate. It is thought that clay minerals, the major component of these dusts, are also the most potent ice-nucleating particles. But Ben Murray and colleagues show here that feldspar minerals dominate ice nucleation by mineral dust, despite being a minor dust component. They also suggest that feldspar particles may account for a large proportion of ice nuclei in the Earth's atmosphere at certain temperatures, and as feldspar content can vary, changes in the location of dust sources may alter the concentration of ice nuclei in the atmosphere and the associated climate effects. The amount of ice present in mixed-phase clouds, which contain both supercooled liquid water droplets and ice particles, affects cloud extent, lifetime, particle size and radiative properties 1 , 2 . The freezing of cloud droplets can be catalysed by the presence of aerosol particles known as ice nuclei 2 . One of the most important ice nuclei is thought to be mineral dust aerosol from arid regions 2 , 3 . It is generally assumed that clay minerals, which contribute approximately two-thirds of the dust mass, dominate ice nucleation by mineral dust, and many experimental studies have therefore focused on these materials 1 , 2 , 4 , 5 , 6 . Here we use an established droplet-freezing technique 4 , 7 to show that feldspar minerals dominate ice nucleation by mineral dusts under mixed-phase cloud conditions, despite feldspar being a minor component of dust emitted from arid regions. We also find that clay minerals are relatively unimportant ice nuclei. Our results from a global aerosol model study suggest that feldspar ice nuclei are globally distributed and that feldspar particles may account for a large proportion of the ice nuclei in Earth’s atmosphere that contribute to freezing at temperatures below about −15 °C.

Anthropogenic emissions have been shown to affect new particle formation, aerosol concentrations, and clouds. Such effects vary with region, environmental conditions, and cloud types. In the wet season of Amazonia, anthropogenic emissions emitted from Manaus, Brazil, can significantly increase the cloud condensation nuclei (CCN) concentrations compared to the background of mainly natural aerosols. However, the regional response of cloud and rain to anthropogenic emissions in Amazonia remains very uncertain. Here, we aim to quantify how aerosol concentration, cloud, and rain respond to changes in anthropogenic emissions through parameterized new particle formation and primary aerosol emission in the Manaus region and to understand the underlying mechanisms. We ran the atmosphere-only configuration of the HadGEM3 climate model with a nested regional domain that covers most of the rainforest region (720 km by 1200 km with 3 km resolution) under scaled regional emissions. The 7 d simulations show that, in the areas that are affected by anthropogenic emissions, when aerosol and precursor gas emissions are doubled from the baseline emission inventories, aerosol number concentrations increase by 13 %. The nucleation rate that involves sulfuric acid and biogenic compounds generally increases with pollution levels. However, nucleation is suppressed very close to the pollution source, resulting in lower nucleation and soluble Aitken mode aerosol number concentrations. We also found that doubling the anthropogenic emission can increase the cloud droplet number concentrations (Nd) by 9 %, but cloud water and rain mass mixing ratios do not change significantly. Even very strong reductions in aerosol number concentrations by a factor of 4, which is an unrealistic condition, cause only a 4 % increase in rain over the domain. If we assume our simulation has a fine enough grid resolution and an accurate representation of the relevant atmospheric processes, the simulated weak and non-linear response of cloud and rain properties to linearly scaled anthropogenic emissions suggests that the interactions among aerosol, cloud, and precipitation in the Amazonian convective environment are buffered by microphysical processes. It also implies that the convective environment is resilient to the changes in Nd that occur in response to localized anthropogenic aerosol perturbations.

The change in planetary albedo due to aerosol–cloud interactions during the industrial era is the leading source of uncertainty in inferring Earth’s climate sensitivity to increased greenhouse gases from the historical record. The variable that controls aerosol–cloud interactions in warm clouds is droplet number concentration. Global climate models demonstrate that the present-day hemispheric contrast in cloud droplet number concentration between the pristine Southern Hemisphere and the polluted Northern Hemisphere oceans can be used as a proxy for anthropogenically driven change in cloud droplet number concentration. Remotely sensed estimates constrain this change in droplet number concentration to be between 8 cm−3 and 24 cm−3. By extension, the radiative forcing since 1850 from aerosol–cloud interactions is constrained to be −1.2 W·m−2 to −0.6 W·m−2. The robustness of this constraint depends upon the assumption that pristine Southern Ocean droplet number concentration is a suitable proxy for preindustrial concentrations. Droplet number concentrations calculated from satellite data over the Southern Ocean are high in austral summer. Near Antarctica, they reach values typical of Northern Hemisphere polluted outflows. These concentrations are found to agree with several in situ datasets. In contrast, climate models show systematic underpredictions of cloud droplet number concentration across the Southern Ocean. Near Antarctica, where precipitation sinks of aerosol are small, the underestimation by climate models is particularly large. This motivates the need for detailed process studies of aerosol production and aerosol–cloud interactions in pristine environments. The hemispheric difference in satellite estimated cloud droplet number concentration implies preindustrial aerosol concentrations were higher than estimated by most models.

Natural aerosols define a preindustrial baseline state from which the magnitude of anthropogenic aerosol effects on climate are calculated and are a major component of the large uncertainty in anthropogenic aerosol−cloud radiative forcing. This uncertainty would be reduced if aerosol environments unperturbed by air pollution could be studied in the present-day atmosphere, but the pervasiveness of air pollution makes identification of unperturbed regions difficult. Here, we use global model simulations to define unperturbed aerosol regions in terms of two measures that compare 1750 and 2000 conditions—the number of days with similar aerosol concentrations and the similarity of the aerosol response to perturbations in model processes and emissions. The analysis shows that the aerosol system in many present-day environments looks and behaves like it did in the preindustrial era. On a global annual mean, unperturbed aerosol regions cover 12% of the Earth (16% of the ocean surface and 2% of the land surface). There is a strong seasonal variation in unperturbed regions of between 4% in August and 27% in January, with the most persistent conditions occurring over the equatorial Pacific. About 90% of unperturbed regions occur in the Southern Hemisphere, but in the Northern Hemisphere, unperturbed conditions are transient and spatially patchy. In cloudy regions with a radiative forcing relative to 1750, model results suggest that unperturbed aerosol conditions could still occur on a small number of days per month. However, these environments are mostly in the Southern Hemisphere, potentially limiting the usefulness in reducing Northern Hemisphere forcing uncertainty. Significance Uncertainty in aerosol forcing of climate since the preindustrial era hampers efforts to quantify the sensitivity of global temperature to radiative perturbations caused by human activity. Because forcings are referenced to preindustrial conditions, a large part of the uncertainty will be reduced only by accurately defining pristine aerosol conditions before air pollution. We show that pristine conditions should still be observable on a few days per month in many regions of the Earth. However, pristine cloudy regions, which are of most importance for forcing uncertainty, occur almost entirely in the Southern Hemisphere. Reduction in uncertainty of predominantly Northern Hemisphere forcing may therefore have to rely on measurements from a different hemisphere, which will limit the extent to which uncertainties can be reduced.

Climate variability in the North Atlantic influences processes such as hurricane activity and droughts. Global model simulations have identified aerosol–cloud interactions (ACIs) as an important driver of sea surface temperature variability via surface aerosol forcing. However, ACIs are a major cause of uncertainty in climate forcing; therefore, caution is needed in interpreting the results from coarse-resolution, highly parameterized global models. Here, we separate and quantify the components of the surface shortwave effective radiative forcing (ERF) due to aerosol in the atmosphere-only version of the UK Earth System Model (UKESM1) and evaluate the cloud properties and their radiative effects against observations. We focus on a northern region of the North Atlantic (NA) where stratocumulus clouds dominate (denoted the northern NA region) and a southern region where trade cumulus and broken stratocumulus dominate (southern NA region). Aerosol forcing was diagnosed using a pair of simulations in which the meteorology is approximately fixed via nudging to analysis; one simulation has pre-industrial (PI) and one has present-day (PD) aerosol emissions. This model does not include aerosol effects within the convective parameterization (but aerosol does affect the clouds associated with detrainment) and so it should be noted that the representation of aerosol forcing for convection is incomplete. Contributions to the surface ERF from changes in cloud fraction (fc), in-cloud liquid water path (LWPic) and droplet number concentration (Nd) were quantified. Over the northern NA region, increases in Nd and LWPic dominate the forcing. This is likely because the already-high fc there reduces the chances of further large increases in fc and allows cloud brightening to act over a larger region. Over the southern NA region, increases in fc dominate due to the suppression of rain by the additional aerosols. Aerosol-driven increases in macrophysical cloud properties (LWPic and fc) will rely on the response of the boundary layer parameterization, along with input from the cloud microphysics scheme, which are highly uncertain processes. Model grid boxes with low-altitude clouds present in both the PI and PD dominate the forcing in both regions. In the northern NA, the brightening of completely overcast low cloud scenes (100 % cloud cover, likely stratocumulus) contributes the most, whereas in the southern NA the creation of clouds with fc of around 20 % from clear skies in the PI was the largest single contributor, suggesting that trade cumulus clouds are created in response to increases in aerosol. The creation of near-overcast clouds was also important there. The correct spatial pattern, coverage and properties of clouds are important for determining the magnitude of aerosol forcing, so we also assess the realism of the modelled PD clouds against satellite observations. We find that the model reproduces the spatial pattern of all the observed cloud variables well but that there are biases. The shortwave top-of-the-atmosphere (SWTOA) flux is overestimated by 5.8 % in the northern NA region and 1.7 % in the southern NA, which we attribute mainly to positive biases in low-altitude fc. Nd is too low by −20.6 % in the northern NA and too high by 21.5 % in the southern NA but does not contribute greatly to the main SWTOA biases. Cloudy-sky liquid water path mainly shows biases north of Scandinavia that reach between 50 % and 100 % and dominate the SWTOA bias in that region. The large contribution to aerosol forcing in the UKESM1 model from highly uncertain macrophysical adjustments suggests that further targeted observations are needed to assess rain formation processes, how they depend on aerosols and the model response to precipitation in order to reduce uncertainty in climate projections.

Understanding and reducing uncertainty in model-based estimates of aerosol radiative forcing is crucial for improving climate projections. A key challenge is that differences between model output and observations can stem from uncertainties in input parameters (parametric uncertainty) or from deficiencies in model code and configuration (structural uncertainty), and these two causes are difficult to distinguish. Structural deficiencies limit efforts to reduce parametric uncertainty through observational constraint because they prevent models from being simultaneously consistent with multiple observations. However, no framework exists to detect structural deficiencies and assess their impact on parametric uncertainty. We propose a workflow to identify structural inconsistencies between observational constraints and diagnose potential structural deficiencies. Using a perturbed parameter ensemble, we sample uncertainty in aerosols, clouds, and radiation in the UK Earth System Model (UKESM), and evaluate model bias against in-situ observations of sulfate aerosol, sulfur dioxide, aerosol optical depth, and particle number concentration across Europe. Applying observational constraints reveals inconsistencies that no combination of the perturbed parameters can resolve. For example, sulfate concentrations in different regions cannot be matched simultaneously, and enforcing a compromise between regions reduces skill across most variables. Additional examples include an inter-region inconsistency in SO2 and an inter-variable inconsistency between aerosol optical depth and sulfate. By examining the parameter sets retained by constraints, we trace inconsistencies to the parameterisations that may cause them and propose targeted changes to address the underlying deficiency. This approach offers a pathway for evidence-based model development that supports more robust uncertainty reduction and improves climate projection skill.

Aerosol–cloud interactions and ice production processes are important factors that influence mixed-phase cold-air outbreak (CAO) clouds and their contribution to cloud-phase feedback. Recent case studies of CAO events suggest that increases in ice-nucleating particle (INP) concentrations cause a reduction in cloud total water content and albedo at the top of the atmosphere. However, no study has compared the sensitivities of CAO clouds to these processes under different environmental conditions. Here, we use a high-resolution nested model to quantify and compare the responses of cloud microphysics and dynamics to cloud droplet number concentration (Nd), INP concentration, and efficiency of the Hallett–Mossop (HM) secondary ice production process in two CAO events over the Labrador Sea, representing intense (cold, March) and weaker (warmer, October) mixed-phase conditions. Our results show that variations in INP concentrations strongly influence both cases, while changing Nd and the HM process efficiency affects only the warmer October case. With a higher INP concentration, cloud cover and albedo at the top of the atmosphere increase in the cold March case, while the opposite responses are found in the warm October case. We suggest that the CAO cloud response to the parameters is different in ice-dominated and liquid-dominated regimes and that the determination of the regime is strongly controlled by the cloud temperature and the characteristics of ambient INP, which both control the glaciation of clouds. This study provides an instructive perspective to understand how these cloud microphysics affect CAO clouds under different environmental conditions and serves as an important basis for future exploration of the cloud microphysics parameter space.