Measurement report: Observational Analysis of Mode-Dependent Fog Droplet Size Distribution Evolution and Improved Parameterization Using Segmented Gamma Fitting

Abstract. Influenced by numerous physical factors, the evolution of fog droplet size distributions (DSDs) during the fog lifecycle is not yet fully understood and difficult to represent realistically 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 the winters of 2006–2009 and 2017–2018 in Nanjing, China. Among the 27 observed fog events, microphysical properties such as fog number concentration (Nf), liquid water content (LWC), volume-mean radius (Rv) and effective radius (Reff) vary substantially. The unimodal (3 μm), bimodal (3, 21 μm) and trimodal (around 3, 13, 21 μm) DSD were observed. As the fog developed, the DSDs evolved from unimodal to multimodal. The third mode centered at 13 μm in trimodal cases appeared after the other two modes, typically around the time LWC reached its maximum, corresponding to the mature stage of fog. For all mode types, the probability density function decreased with increasing Nf and LWC. Rv is generally greater than 4 μm and Reff greater than 6 μm for trimodal DSDs. Based on the observational findings, a segmented gamma fitting was applied to the mean DSD with partition points at 10 and 21 μm. Comparison between microphysical parameters derived from the fitted DSD and those from observations indicates that the three-segment fitting provides more accurate estimates of Nf and LWC. Moreover, the three-segment gamma fitting substantially improves the representation of Reff, absorption coefficient and optical thickness, with most deviations constrained within 20 %.

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Published
2025-08-20
DOI
https://doi.org/10.5194/egusphere-2025-3632
Primary Topic
Air Quality Monitoring and Forecasting
Type
article
Field-Weighted Citation Impact
0.00

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article

Measurement report: Observational Analysis of Mode-Dependent Fog Droplet Size Distribution Evolution and Improved Parameterization Using Segmented Gamma Fitting

Jingwen Zhang, Xiaoli Liu, Zhenghua An
Air Quality Monitoring and Forecasting
article

Measurement report: Observational Analysis of Mode-Dependent Fog Droplet Size Distribution Evolution and Improved Parameterization Using Segmented Gamma Fitting

Jingwen Zhang, Xiaoli Liu, Zhenghua An
article en

Abstract

Abstract. Influenced by numerous physical factors, the evolution of fog droplet size distributions (DSDs) during the fog lifecycle is not yet fully understood and difficult to represent realistically 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 the winters of 2006–2009 and 2017–2018 in Nanjing, China. Among the 27 observed fog events, microphysical properties such as fog number concentration (Nf), liquid water content (LWC), volume-mean radius (Rv) and effective radius (Reff) vary substantially. The unimodal (3 μm), bimodal (3, 21 μm) and trimodal (around 3, 13, 21 μm) DSD were observed. As the fog developed, the DSDs evolved from unimodal to multimodal. The third mode centered at 13 μm in trimodal cases appeared after the other two modes, typically around the time LWC reached its maximum, corresponding to the mature stage of fog. For all mode types, the probability density function decreased with increasing Nf and LWC. Rv is generally greater than 4 μm and Reff greater than 6 μm for trimodal DSDs. Based on the observational findings, a segmented gamma fitting was applied to the mean DSD with partition points at 10 and 21 μm. Comparison between microphysical parameters derived from the fitted DSD and those from observations indicates that the three-segment fitting provides more accurate estimates of Nf and LWC. Moreover, the three-segment gamma fitting substantially improves the representation of Reff, absorption coefficient and optical thickness, with most deviations constrained within 20 %.

National University of Defense Technology (CN), Nanjing University of Information Science and Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 81%
Air Quality Monitoring and Forecasting
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