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- W2885172887 abstract "Abstract Water vapor supersaturation, as one of the most important environmental parameters during the formation of clouds or fogs, cannot be directly measured, and few studies have been carried out to estimate it in the ambient activation process. In this study, a new method to estimate the water vapor supersaturation based on the inverse application of κ ‐Köhler theory is proposed. Aerosol hygroscopic parameter κ , dry particle size distributions, and wet droplet size distributions were employed and a comparison of predicted droplet number concentration with the measurement results was made to obtain the effective supersaturation during the activation process. Using this method, we acquired the supersaturations varying from 0.01% to 0.05% in a fog episode observed in the North China Plain. In this fog episode, both hydrated unactivated droplets and activated droplets play a part in the total detected droplet number concentrations with the unactivated droplets' ratio decreasing with size. The sensitivity study was also made to evaluate the effects of droplet and aerosol hygroscopic measurement errors on the supersaturation ratio estimation. Water vapor supersaturation obtained with this method can be regarded as an effective value and can be further applied to cloud analysis in the future. This method is only based on conventional measurements of aerosol and droplets and does not rely on any other data, which makes it flexible and easy to perform. Calculated supersaturations and critical diameters can also deepen the understanding of ambient activation process and corresponding interactions between aerosol and droplet characteristics." @default.
- W2885172887 created "2018-08-22" @default.
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- W2885172887 date "2018-09-27" @default.
- W2885172887 modified "2023-10-13" @default.
- W2885172887 title "Method to Estimate Water Vapor Supersaturation in the Ambient Activation Process Using Aerosol and Droplet Measurement Data" @default.
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- W2885172887 doi "https://doi.org/10.1029/2018jd028315" @default.
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