Disentangling Global Dust‐High Cloud Nonlinear Interactions Through Multivariate Meteorological Constraints Framework

Abstract Dust aerosols, highly efficient ice nucleating particles, significantly influence high cloud properties, thereby impacting climate. As global warming and aridification are projected to increase dust emissions, understanding dust‐high cloud interactions becomes increasingly crucial. However, disentangling dust effects from meteorology influences on high clouds remains challenging. This study employs Principal Component Analysis to derive the first principal component (PC1), a comprehensive indicator that characterizes meteorological conditions dominating high cloud evolution. This allows us to classify atmospheric conditions as weak (characterized by weak updrafts, low humidity, and stable atmosphere), moderate, or favorable (strong updrafts, high humidity, and unstable atmosphere). By strictly constraining both meteorological conditions and ice water path, we establish a framework to isolate dust impacts on high cloud. Our results unveil nonlinear dust‐cloud interactions co‐modulated by meteorology and dust loadings, contrary to previously assumed uniformity. Under weak meteorological conditions, dust impacts vary with loadings: low dust loadings promote larger ice crystals and denser clouds, while high dust levels lead to smaller crystals and thinner clouds. However, under favorable meteorological conditions, dust effects become notably weaker and remain relatively consistent across levels. These findings help explain previously conflicting observations of dust impacts on high clouds and highlight why both meteorological conditions and dust levels must be considered when studying dust‐cloud interactions in a changing climate.