Sensitivity of mixed-phase cloud properties to ice-nucleating particles and model resolution

Mixed-phase cloud thinning (MCT) is an emerging climate intervention strategy that targets supercooled liquid clouds in polar regions during winter. In the absence of sunlight, these clouds exert a net warming effect by trapping outgoing longwave radiation. Seeding polar mixed-phase clouds with ice-nucleating particles (INPs) initiates glaciation, converting persistent, non-precipitating clouds into precipitating ones and reducing their optical thickness. This process enhances the emission of longwave radiation to space, leading to a net cooling of the polar atmosphere. By promoting this radiative cooling, MCT may help restore sea ice and counteract some of the expected warming over polar oceans due to climate change. Initial results suggest that MCT can offset roughly 25% of the expected increase in polar sea-surface temperature from a doubling of CO₂. In this work, we apply different resolutions in ICON-HAM, recognising that model resolution is critical for realistically capturing mixed-phase clouds and their inherent phase heterogeneity. We show how the microphysical properties of mixed-phase clouds respond to varying INP concentrations, showing that their sensitivity is strongly resolution-dependent and highlighting the critical role of model scale in assessing the potential efficacy of MCT.