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Hydrometeor classification methods using polarimetric radar variables rely on probability density functions (PDFs) or membership functions derived empirically or by using electromagnetic scattering calculations. This paper describes an objective approach based on cluster analysis to deriving the PDFs. An iterative procedure with K-means clustering and expectation-maximization clustering based on Gaussian mixture models is developed to generate a series of prototypes for each hydrometeor typedoi:10.1175/jtech-d-13-00178.1 fatcat:5bnhonw6tjdkzopxdgbw4xi7la