The activation ability of aerosols as cloud condensation nuclei (CCN) is crucial in climate and hydrological cycle studies, but their properties are not well known. We investigated the long-term measurements of atmospheric aerosol properties, CCN concentrations (N_CCN) at supersaturation (SS = 0.1%–1.0%), and hygroscopicity at the Department of Energy’s Southern Great Plains (SGP) site to illustrate the dependence of N_CCN on aerosol properties and transport pathways. Cluster analysis was applied to the back trajectories of air masses to investigate their respective source regions. The results showed that aged biomass burning aerosols from Central America were characterized by higher accumulation mode particles (N_accu; median value 805 cm⁻³) and relatively high aerosol hygroscopicity (κ; median value ∼0.25) values that result in the higher CCN activation and relatively high N_CCN (median value 258–1578 cm⁻³ at a SS of 0.1%–1.0%). Aerosols from the Gulf of Mexico were characterized by higher N_accu (∼35%), and N_CCN (230–1721 cm⁻³ at a SS of 0.1%–1.0%) with the lowest κ (∼0.17). In contrast, relatively high nucleation mode particles (N_nucl; ∼20%) and low N_CCN (128–1553 cm⁻³ at a SS of 0.1%–1.0%) with higher κ (∼0.30) values were observed on the aerosols associated with a westerly wind. The results indicate particle size as the most critical factor influencing the ability of aerosols to activate, whereas the effect of chemical composition was secondary. Our CCN closure analysis suggests that chemical composition and mixing state information are more crucial at lower SS, whereas at higher SS, most particles become activated regardless of their chemical composition and size. This study affirms that soluble organic fraction information is required at higher SS for better N_CCN prediction, but both the soluble organics fraction and mixing state are vital to reduce the N_CCN prediction uncertainty at lower SS.

Extreme smog in India widely impacts air quality in late autumn and winter months. While the links between emissions, air quality and health impacts are well‐recognized, the association of smog and its intensification with climatic trends in the lower troposphere, where aerosol pollution and its radiative effects manifest, are not understood well. Here we use long‐term satellite data to show a significant increase in aerosol exceedances over northern India, resulting in sustained atmospheric warming and surface cooling trends over the last two decades. We find several lines of evidence suggesting these aerosol radiative effects have induced a multidecadal (1980–2019) strengthening of lower tropospheric stability and increase in relative humidity, leading to over fivefold increase in poor visibility days. Given this crucial aerosol‐radiation‐meteorological feedback driving the smog intensification, results from this study would help inform mitigation strategies supporting stronger region‐wide measures, which are critical for solving the smog challenge in India.

A growing body of research has underscored the radiative impact of mineral dust in influencing Indian summer monsoon rainfall variability. However, the various aerosol‐cloud‐precipitation interaction mechanisms remain poorly understood. Here we analyze multisatellite observations to examine dust‐induced modification in ice clouds and precipitation susceptibility. We show contrasting dust‐induced changes in ice cloud regimes wherein despite a 25% reduction in ice particle radius in thin ice clouds, we find ~40% increase in ice particle radius and ice water path in thick ice clouds resulting in the cloud deepening and subsequently strengthened precipitation susceptibility, under strong updraft regimes. The observed dust‐ice cloud‐precipitation interactions are supported by a strong correlation between the interannual monsoon rainfall variability and dust frequency. This microphysical‐dynamical coupling appears to provide negative feedback to aerosol‐cloud interactions, which acts to buffer enhanced aerosol wet scavenging. Our results underscore the importance of incorporating meteorological regime‐dependent dust‐ice cloud‐precipitation interactions in climate simulations.