Retrieval of Fine-Scale Microphysical Characterization of Clouds with Combination of Terahertz Radar Observation and Multi-Component Gaussian Decomposition

Cloud microphysical evolution plays a central role in controlling cloud radiative effects and precipitation initiation, governed by interacting processes such as condensation, collision–coalescence, size sorting, and evaporation. Cloud radars provide vertically resolved observations and Doppler spectra contain information beyond bulk moments through their linkage to hydrometeor fall speeds and vertical air motion. Compared with microwave cloud radars, Terahertz cloud radars improve the observability of fine-scale spectral morphology and its rapid variability through enhanced Doppler sensitivity, finer spatial resolution, and higher attainable temporal sampling for a given velocity resolution. However, limited by the device technology and system complexity, researches on terahertz cloud radar have not been reported until the past few years. While, the fairly small amount of works published up to now have already demonstrated the significant advantages of the terahertz radar in Doppler-spectral observations of clouds. Motivated by these capabilities, we develop the retrieval of fine-scale microphysical characterization of clouds with combination of terahertz radar observation and multi-component Gaussian decomposition. The multi-peaked Doppler spectral morphology is converted into component-wise microphysics to derive liquid water content, total number concentration, and mass-weighted mean diameter. Dominant-component statistics further summarize time-resolved spectral evolution and support stage-dependent interpretation of a warm-cloud drizzle lifecycle. The results highlight the potential of terahertz spectral-morphology analysis for constraining warm-cloud initiation pathways and informing subgrid parameterizations.