Improved Parameterization of Cloud Droplet Spectral Dispersion Expected to Reduce Uncertainty in Evaluating Aerosol Indirect Effects

Relative dispersion (epsilon), as a parameter characterizing droplet spectral shape, exerts a considerable impact on cloud radiation and precipitation processes, and its accurate parameterization is urgently needed in models. Current epsilon parameterizations, which are based on droplet number concentration or simply set as constants, are inadequate to satisfy the demand. This study shows, utilizing in-situ cloud and fog observations from five underlying surface regions (urban, suburban, mountainous, coastal and rainforest) of China, that epsilon uniformly and stably manifests as initially increasing then decreasing as volume-mean diameter increases across these regions. Based on this relationship, a epsilon parameterization is established, which exhibits improved predictive capabilities in evaluating both cloud albedo effect and cloud lifetime effect. The parameterization is expected to enhance cloud simulation accuracy and minimize discrepancy between observed and simulated cloud radiation and precipitation, particularly for weather and climate models that commonly use the double-moment cloud microphysical schemes.