Measurement report: Observational analysis of mode-dependent fog droplet size distribution evolution and improved parameterization using segmented gamma and lognormal fitting

Fog droplet size distributions (DSDs) evolve under the influence of many physical processes, yet their development through the fog lifecycle remains insufficiently understood and challenging to represent in numerical models, constraining the accuracy of fog forecasting. To improve understanding of the fog evolution, field observations under a polluted background were conducted during winters from 2006–2009 and 2017–2018 in Nanjing, China. Among the 27 observed fog events, microphysical properties including fog droplet number concentration (Nf), liquid water content (LWC), volume-mean radius (Rv), and effective radius (Reff) varied substantially. Unimodal, bimodal, and trimodal DSDs were observed, with mode separating diameters of 2 µm for unimodal; 2 and 6–18 µm for bimodal; and 2, 6–12, and 18–26 µm for trimodal DSDs. Both the number of modes and the mode separating diameters vary over the fog life cycle, with more frequent and pronounced changes occurring during fog formation and dissipation or during periods of strong fluctuations in Nf and LWC. Compared with unimodal DSDs, bimodal and trimodal DSDs exhibited broader PDF distributions of LWC, Rv and Reff. Based on these observational features, segmented gamma and lognormal fits were applied to mean DSDs using partition points at 10 and 20 µm. Comparisons between microphysical parameters derived from the fitted DSD and observations show that three-segment fitting improved estimates of Nf and LWC, while substantially enhanced the representation of Reff, absorption coefficient, and optical thickness, reducing deviations from up to 90 % to within 20 %.