Vertical Profile Characteristics of Deep Convective Clouds in East Asia

Quantifying the microphysical profiles of deep convective clouds (DCCs) is essential for diagnosing cloud life cycles and their climatic impacts. However, existing satellite products suffer from physical discontinuities and a “representation gap” within the mixed-phase region (−20°C to 0°C), hindering the characterization of full-profile structures. To address this, we developed a multi-strategy fusion algorithm leveraging the RO_ice_phase_fraction parameter (Radar-Only ice phase weighting) as a temperature-dependent factor to reconstruct physically consistent and vertically continuous profiles. Using 2015–2017 CloudSat/CALIPSO data, we identified 86,274 single-layer mixed-phase DCC profiles in East Asia and established a characterization framework based on empirical orthogonal function (EOF) analysis and a “Fourier-Exponential Decay Composite Model”. The results indicate high structural orderliness for cloud water content (CWC) and particle number concentration (CN), with their first modes (EOF1) explaining over 70% and 60% of the total variance, respectively. Conversely, effective radius (CER) exhibits higher spatial heterogeneity. Our analysis reveals that East Asian terrestrial DCCs are strongly modulated by anthropogenic aerosols, showing distinct “high CN, small CER” signatures in North and Northeast China, with a regime shift from “cold-season background” to “aerosol forcing” during the winter-to-spring transition. Fitting evaluations confirm the model’s robustness, with over 84% of CN and CER samples achieving high quality ( r^2 ≥ 0.7). This study reveals the “drastic” forced-dominant nature of terrestrial DCCs versus the “steady-state” features of oceanic convection, providing a standardized tool for refining cloud microphysics parameterization schemes.