Bayesian method of radar classification of dangerous meteorological phenomena of cumulonimbus clouds

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Bayesian method improves classification reliability of dangerous meteorological phenomena in cumulonimbus clouds, highlighting turbulence effects.

The proposed classification method increases the reliability of identifying hazardous meteorological phenomena like thunderstorms.
Using the maximum likelihood criterion, the method incorporates reflectivity and atmospheric turbulence as key classification features.
Analysis shows that combining multiple features leads to more accurate classification outcomes for dangerous weather conditions.
This work emphasizes the need for optimized classification criteria to enhance aviation safety during severe weather events.

Vasiliev et al. (2025) studied this question.

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Bayesian method improves classification reliability of dangerous meteorological phenomena in cumulonimbus clouds, highlighting turbulence effects.