Clouds are ubiquitous and play an important role in modulating Earth's climate by modulating incoming and outgoing radiation. A challenge in understanding the impact of clouds arises from the multi-scale nature of cloud processes, which span from aerosol activation at the nanometer scale to the dynamics of cloud systems at the scale of hundreds of kilometers. Key microphysical processes, including droplet collision-coalescence, ice crystal formation, and their modulation by turbulence, occur at scales smaller than 100\;m, which poses a challenge to observe or simulate them. The uncertainty is further exacerbated by turbulent interactions with the environment through entrainment, mixing of air, and radiative changes within the cloud. Hence, we need to improve our understanding on the small-scale to increase our confidence in climate projections.
The superposition of small-scale processes calls for an integrated approach that combines laboratory experiments, field observations, and numerical modeling. Field observations characterize cloud processes within their natural, dynamic environment using a combination of remote sensing and in-situ measurements. Recent advances in observational platforms (e.g., uncrewed aerial systems), measurement techniques (e.g., multi-frequency cloud radar), and experimental designs have enhanced these capabilities. Controlled laboratory experiments allow for the isolation and systematic study of specific cloud processes under defined and repeatable conditions. High-resolution, process-oriented numerical modeling enables the study of fundamental interactions, can test hypotheses, and synthesizes datasets. These models need constraints and validation by data from both laboratory and field campaigns.
This session invites contributions that advance the understanding of small-scale cloud processes. A particular emphasis is placed on synergistic studies that combines laboratory experiments, field observations and/or numerical modeling .