Aerosol-cloud interactions (ACI) are a major source of uncertainty in climate science, critically affecting our ability to project near-term climate evolution and assess societal risks. These interactions influence effective radiative forcing, cloud dynamics, and precipitation patterns, yet remain insufficiently constrained due to limitations in observations, modeling, and process understanding. This uncertainty hampers robust policy advice across multiple domains—from estimating remaining carbon budgets and climate sensitivity, to anticipating regional extreme events and evaluating climate interventions such as solar radiation modification. In many cases, the influence of ACI is either underappreciated or excluded from decision-making frameworks due to its complexity and lack of quantification. This perspective outlines a path forward to overcome these barriers by leveraging emerging opportunities in satellite remote sensing, ground-based and airborne observations, high-resolution climate modeling, and machine learning. We identify key areas where rapid progress is feasible, including improved retrievals of cloud microphysical properties, better representation of natural aerosols in a warming world, and enhanced integration of observational and modeling communities. Even as anthropogenic aerosol and its impacts on clouds is reducing owing to emissions controls, addressing ACI uncertainties remains essential for refining climate projections, supporting effective mitigation and adaptation strategies, and delivering actionable science to policymakers in a rapidly changing climate system.

In response to continued greenhouse gas (GHG) increases, the Atlantic Meridional Overturning Circulation (AMOC) is expected to weaken through the 21st century. However, AMOC impacts associated with efforts to improve air quality are less well understood. Here, eight models from the Regional Aerosol Model Intercomparison Project are examined to quantify mid-21st century AMOC changes resulting from global and regional anthropogenic aerosol and precursor gas (AA) emissions reductions (industrial and biomass burning), by comparing strong air pollution control shared socioeconomic pathway (SSP1-2.6) to a baseline with weak air pollution control (SSP3-7.0). Global AA reductions and subsequent warming yield multi-model mean AMOC weakening of 6% ( (Formula presented) (Formula presented) Sv; 1 Sv = 106 m3 s−1) by the last 12 years of the simulation (2039–2050). This is ⅓ of the magnitude of the corresponding weakening associated with the high GHG emissions scenario SSP3-7.0. Of the regional perturbations, combined North American and European AA reductions drive the largest AMOC weakening, followed by combined African and Middle Eastern reductions and then East Asian reductions, with South Asian reductions yielding non-significant weakening. Across these experiments, AMOC weakening is significantly correlated with the North Atlantic Ocean aerosol effective radiative forcing ( (Formula presented) (Formula presented) ) and aerosol optical depth response ( (Formula presented) (Formula presented) ). AMOC weakening under AA reductions is associated with a thermally driven reduction in buoyancy in the subpolar North Atlantic, which is largely driven by surface shortwave radiation increases, consistent with the forcing from AA reductions. Africa + Middle East AA reductions also involve excitation of a negative North Atlantic Oscillation pattern, which contributes to AMOC weakening. Our results show that efforts to improve air quality, particularly around the Atlantic basin but also far away in East Asia, will contribute to future AMOC weakening.

The Regional Aerosol Model Intercomparison Project (RAMIP) is designed to quantify the forcing and climate impacts of mid-21st century anthropogenic aerosol and precursor gas (AA) emissions reductions (both industrial and biomass burning), by comparing a weak (SSP3-7.0) versus strong (SSP1-2.6) level of air quality control aerosol emissions pathway. AA emissions reductions experiments include global (GLO), East Asia (EAS), South Asia, Africa and the Middle East (AFR), and North America and Europe (NAE). Here, we use RAMIP time-slice simulations with fixed sea surface temperatures and sea-ice distributions from nine models to quantify the aerosol effective radiative forcing (ERF), including aerosol radiation (ERF_ari) and aerosol cloud interactions (ERF_aci). The multi-model global mean net ERF_ari+aci is 0.77 ± 0.25 W m⁻² for GLO, and three of the four regional perturbations yield a significant positive net ERF_ari+aci (up to 0.15 ± 0.07 W m⁻² for EAS). In all cases, net ERF_ari+aci is dominated by aerosol-cloud interactions, which are largely due to reduced cloud scattering. Of the four regions, NAE yields the largest forcing efficiency whereas AFR yields the weakest. Although the areas outside our four target regions contribute 25% to the GLO aerosol optical depth reduction, they disproportionately contribute 44% to the GLO net ERF_ari+aci. The multimodel regional mean net ERF_ari+aci for three regional perturbations is much larger (up to  1.64 ± 1.36 W m⁻² for EAS) than the corresponding global mean value. However, these regional values are even larger (up to 2.69 ± 1.72 W m⁻² for EAS) under global aerosol reductions, implying remote emission reductions represent a sizable contribution (up to 1.05 ± 0.56 W m⁻² for EAS). These large regional ERFs will in turn drive relatively large regional climate impacts, which continue to be underappreciated in most policy discussions.

Decreases in anthropogenic aerosols will reduce fine particulate matter (PM2.5); however, meteorological feedbacks alter dust emissions, modifying air quality gains. We use eight Earth System Models from the Regional Aerosol Model Intercomparison Project (RAMIP) simulations to assess African climate and air quality responses to anthropogenic aerosol emission perturbations, including meteorological feedbacks on dust emissions. By 2050, African and global emissions reductions drive the largest continent-average PM2.5 decrease (0.92 ± 0.17 μg m−3; 5% and 1.35 ± 0.50 μg m−3; 7%, respectively) relative to SSP3-7.0, though regional dust increases partially offset these reductions. Anthropogenic emissions reductions in the U.S. and Europe also lower African PM2.5 by 0.29 ± 0.32 μg m−3 (2%) due to teleconnections of Northern Hemisphere warming influencing the Intertropical Convergence Zone. Inter-model variability in dust and total PM2.5 reflects differences in meteorological responses and dust emission parameterizations. Meteorological responses explain 90% of dust emissions variability across regions. Aerosol-driven climate feedbacks on dust account for up to 70% of total PM2.5 changes in the Sahara and Namib, offsetting up to 20% of anthropogenic PM2.5 reductions across Africa. Under 2050 global and Africa-wide anthropogenic aerosol reductions, 96,000 (95% CI: 54,000–137,000) and 84,000 (95% CI: 43,000–125,000) PM2.5-related deaths are avoided in Africa, respectively. Dust PM2.5 contributes an uncertain 3.4% of the avoided deaths under global reductions and has no net effect under Africa-wide reductions. Aerosol-driven climate feedbacks may partially offset direct air quality gains, though their continental-scale contribution remains small and uncertain.

Anthropogenic aerosol emissions are projected to decline rapidly in the near future as air quality regulations strengthen. Crucially, however, the response of large-scale atmospheric circulation to these reductions remains a major source of uncertainty. Here, we use multi-model ensembles from Regional Aerosol Model Intercomparison Project to provide a diagnostic assessment of tropical circulation changes in response to global and regional aerosol reductions during 2015–2050. We find that global aerosol reductions lead to a poleward expansion of the Northern Hemisphere (NH) tropical width by 0.10° ± 0.08°, a weakening of the NH Hadley Circulation (HC) by 1.77 ± 1.09 10⁹ kg s⁻¹ and a strengthening of the Southern Hemisphere HC by 2.53 ± 1.30 10⁹ kg s⁻¹. The Intertropical Convergence Zone (ITCZ) also shows a northward shift by 0.19° ± 0.10°. These meridional circulation changes consistently emerge across the regional experiments, with aerosol reductions over East Asia and North America + Europe contributing the most. Although the response of the zonal Pacific Walker circulation to global aerosol reductions is not statistically significant, models show a strengthening tendency that is significant under Africa + Middle East aerosol reductions. Notably, the ITCZ response to greenhouse gas forcing is weak and uncertain, whereas aerosol reductions produce a stronger and more robust response, even in the regional experiments. Our results suggest that both global and regional aerosol reduction significantly contribute to large-scale tropical circulation changes.

Anthropogenic aerosol and associated precursor gas emissions are already declining in many regions and are likely to decline significantly by 2050, with major implications for regional climate. Unlike greenhouse gases, aerosol impacts are spatially heterogeneous and can influence climate both near emission sources and through remote teleconnections. This is particularly important for the South Asian monsoon system, where both local and remote aerosol changes can significantly affect precipitation patterns. Using simulations from the Regional Aerosol Model Intercomparison Project, we examine how local and remote aerosol emission reductions influence South Asian climate across both pre-monsoon and monsoon seasons, including weakening of the elevated heat pump (EHP) mechanism during pre-monsoon months. Our analysis employs 10-member ensembles from 10 CMIP6-era models to compare three experiments with global, South Asian, and East Asian aerosol reductions relative to a high-emission baseline (SSP3-7.0). This experimental design allows us to isolate and quantify the distinct impacts of regional emission changes. Results reveal that global aerosol reductions produce a larger all-India precipitation increase ( (Formula presented) (Formula presented) mm day (Formula presented) (Formula presented) ) than South Asian reductions alone ( (Formula presented) (Formula presented) mm day (Formula presented) (Formula presented) ), with the strongest regional responses over the northern Bay of Bengal, the Western Ghats and Indo-Gangetic Plains. East Asian reductions show uncertain but modest precipitation reductions of (Formula presented) (Formula presented) over parts of west-central and eastern Indian regions. Pre-monsoon carbonaceous aerosol reductions systematically weaken the EHP, cooling the mid-troposphere over the Himalayan foothills by up to (Formula presented) (Formula presented) K and producing localised anomalous descent that opposes the climatological pre-monsoon ascent. Substantial inter-model diversity exists in the spatial patterns and magnitudes of these responses, highlighting key uncertainties in aerosol–monsoon interactions. The South Asian precipitation response is driven by enhanced land–sea thermal contrast, while the pre-monsoon EHP weakening is attributable exclusively to local South Asian carbonaceous aerosol forcing rather than remote teleconnections. These findings have direct implications for air quality and climate adaptation planning across South Asia as regional aerosol emissions diverge under different development pathways.

Employing high-resolution Large Eddy Simulation (LES) coupled with interactive aerosol and cloud microphysics schemes, this study investigates the influence of aerosol and droplet microphysics on the life cycle and properties of wintertime radiation fog in the Po Valley, Italy. For the simulated case, the results show that the main drivers of radiation fog onset and dissipation are nocturnal longwave cooling and surface warming, respectively. Increasing aerosol loading increases droplet number concentration, liquid water content, and fog optical thickness, which reduces droplet sedimentation rates and prolongs fog duration by up to 54 min. Overall, the microphysical influence of aerosols and droplets weakens under heavily polluted conditions. We also show that non-activated hydrated aerosols have a limited influence on total liquid water content and fog-layer mixing. However, they critically affect visibility and fog duration prediction, underscoring the importance of explicitly incorporating hydrated particles in fog forecasting and accurately representing aerosol composition. Additional sensitivity experiments reveal that the prescribed droplet spectral shape parameters significantly influence fog characteristics. Parameter settings that represent a broad droplet size spectrum overestimate the number of large droplets compared to observations, which increases mean droplet sedimentation rates and decreases mean liquid water content by up to 104 % and 78 %, respectively, compared to the settings that best represent the observed spectrum.

Uncertainty in estimations of the net contribution of anthropogenic aerosol particles, particularly of aerosol-cloud interactions (ACIs) to the Earth’s radiation budget, limits our ability to understand past and project future climate change. Earth System Models (ESMs) are among the key tools for assessing the magnitude and impacts of changes in various forcing agents on the global climate system. Hence, improving aerosol and cloud descriptions in ESMs is an important way forward to increase the confidence in estimates of climate impacts of aerosol perturbations in the past, present and future. In the framework of the FORCeS project, experimental and theoretical approaches were combined to bridge the current key gaps in the fundamental understanding of essential aerosol and cloud processes and their descriptions in selected European ESMs. Regarding aerosol types and processes, we focused on organic aerosol, particulate nitrate, absorbing aerosols, and ultrafine aerosol sources including new particle formation and growth. In terms of cloud processes, we targeted cloud droplet activation, hydrometeor growth and evaporation, ice formation and multiplication as well as aerosol processing and scavenging by clouds. The selection was made based on the identified knowledge gaps in the scientific understanding of these processes and/or their current representation in ESMs, as well as a novel perturbed parameter ensemble approach to detecting potential structural deficiencies in an ESM. Here, we review the state-of-the-art, outline our approach for arriving at recommendations for improving the representation of key aerosol and cloud processes within ESMs, and then provide such recommendations applicable in models operating at the Earth system scale. The limitations of the recommendations, applicability, as well as alternative approaches and future research directions are discussed. Overall, the findings highlight the need for continuous efforts towards smart ways for representing the aerosol number size distribution as well as consistent representations of key parameters (e.g., liquid water content and cloud droplet number concentration). Furthermore, we provide guidance for future ESM evaluation emphasising, in particular, the need for exploring the consistency of key parameters, process-based (as opposed to parameter-based), and the complementarity of in-situ and remote-sensed measurements for model evaluation.

Polar amplification (PA) is a robust feature of climate change in coupled atmosphere–ocean general circulation models (AOGCMs), yet its magnitude varies substantially across models. Prior work showed that PA and its drivers, primarily positive feedbacks, are strongly linked to the degree of sea ice loss. Here, we assess to what extent this intermodel spread narrows when sea ice and sea surface temperatures (SSTs) are prescribed in a coordinated set of atmosphere-only GCM (AGCM) simulations. Three AGCMs are forced with SST and sea ice fields from the SSP5-8.5 scenario of a single reference model. Comparisons between AGCM and AOGCM ensembles reveal that prescribing sea surface boundary conditions substantially reduces the spread in PA and associated amplifying feedbacks. This indicates that much of the divergence in coupled model projections arises from feedbacks operating on different patterns of SST warming and sea ice melt. Cloud feedbacks, in particular, exhibit strong sensitivity to SST warming patterns in regions that contribute prominently to intermodel differences in climate sensitivity, especially the southern midlatitudes. Remaining spread in AGCMs isolates intrinsic atmospheric model differences. The Arctic cloud feedback emerges as a major residual uncertainty, reflecting its state dependence on cloud properties such as liquid water path. Decomposing the AGCM response further shows that roughly three-quarters of Arctic amplification is driven by processes related to sea ice melt. Nevertheless, a weakened Arctic amplification persists without evolving future sea ice via temperature feedbacks. In contrast, Antarctic amplification remains more uncertain and is closely linked to historical sea ice amount, which partly determines the sea ice trajectory in future climates.

Ongoing deforestation and global warming are driving critical changes in the Amazon rainforest, a region essential to the global climate system. Model and observational studies have found drier conditions and changes in rainfall patterns in the Amazon; however, fewer studies have examined the role of clouds. Using the state-of-the-art CLARA-A3 satellite climate data record and ERA5 reanalysis data between 1982 and 2020, this study analyzes spatiotemporal trends in cloud cover and surface properties. Our results show a slight but statistically insignificant increase in total cloud cover across the Amazon, but regional and seasonal variations are pronounced. The northern Amazon exhibits a significant increase in high-level cloud fractional cover during the dry–wet transition, while the southern Amazon shows significant declining trends during the dry season across all cloud types. A significant correlation is observed between El Niño–Southern Oscillation and high-level cloud cover variability, especially in the northeastern Amazon, while mid- and low-level clouds show a weak relationship with sea surface temperature variability. Consistent trends in surface heat fluxes and humidity, likely tied to land use and surface changes, may influence these lower cloud layers. However, the application of multiple linear regression reveals the analyzed variables poorly predict medium- and low-level cloud cover, leaving the exact drivers of the observed cloud cover trends uncertain. These findings are consistent with prior research on hydroclimatic trends, implying a drier dry season and a wetter wet season. Further research is recommended to clarify causality and implications for the Amazon climate system.