Understanding cloud droplet relative dispersion is critical for mitigating the confounding effect of aerosol-cloud interactions in the simulation of the global climatic patterns. Diverse dispersion effects, meaning that the correlation between relative dispersion (e) and fog droplet number concentration (N_f) changes from positive to negative as N_f increases at a fixed liquid water content (LWC) condition, were found in the urban fog observed during the winters of 2017 and 2018 in Nanjing, China. The dominant microphysical processes driving the diverse dispersion effects were found to be activation, condensation, deactivation, evaporation, and sedimentation. The critical first bin (diameter range of 2 to 4 mm) strength and volume-mean diameter (D_v) for classifying the diverse dispersion effects are 0.3-0.4 and 10-12 mm, respectively. The mean dispersion offset (DO) was -27.6% for weakening the Twomey effect and 27.5% for enhancing it. Assuming the Gamma distribution for the fog droplet number size distribution, the mean dispersion effect was significantly underestimated at DO < 0. Based on the measured nonmonotonic relationship between e and D_v, we establish e parameterization using a Nelder function, which can be applied to the diverse dispersion effects. The mean deviation for diagnosing DO was less than 10% for DO > 0 and less than 50% for DO < 0. These results could shed new light on understanding the diverse dispersion effects, which cloud help reduce the uncertainties in the simulation of aerosol-cloud interactions.
 

离散度效应,气溶胶-云雾相互作用,云雾微物理