Development and application of a method for the objective differentiation of fog life cycle phases

An objective classification of radiation fog in distinct evolutionary stages during its life cycle based on reliable criteria is essential for various applications, for example for numerical fog modelling and fog forecasting. However, there have been – up to now – merely qualit...

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Bibliographic Details
Main Authors: Frank Maier, Jörg Bendix, Boris Thies
Format: Article
Language:English
Published: Stockholm University Press 2013-06-01
Series:Tellus: Series B, Chemical and Physical Meteorology
Subjects:
Online Access:http://www.tellusb.net/index.php/tellusb/article/download/19971/pdf_1
Description
Summary:An objective classification of radiation fog in distinct evolutionary stages during its life cycle based on reliable criteria is essential for various applications, for example for numerical fog modelling and fog forecasting. However, there have been – up to now – merely qualitative approaches for the distinction of different evolutionary stages in radiation fog. Measurements of the microphysical fog properties with an optical particle counter obtained from droplet measurement technologies together with recordings of the horizontal visibility (VIS) are statistically analyzed to determine individual evolutionary stages of radiation fog with consistent microphysical properties. The developed three-stage approach is based on a statistical change point analysis of the double sum curves of the VIS, the liquid water content, the droplet concentration and the mean radius of the drop size distributions. It could be shown that each of the three recorded radiation fog occurrences could be split into three consecutive phases from formation to dissipation, regardless whether the VIS or the microphysical properties were considered. Having featured consistent microphysical patterns, it could be assumed that the three separated phases of the single fog occurrence could be aggregated for radiation fog. Although this classification is statistically reliable, the dataset still has to be extended for a generalization concerning the separated evolutionary stages.
ISSN:1600-0889