The present invention relates to a method to classify types of hydrometeors by using a correlation coefficient (hv), measured propagation phase differential (_dp(r)) or characteristic of measured propagation phase differential (_dp), and a signal to noise ratio (SNR) as input variables input feature vector, shortly a radar measurement vector for fuzzy logic method, disclosing a method to classify hydrometers using X band dual polarization radar composed by having object determining steps, comprising steps of: obtaining a signal to noise ratio (SNR), a correlation coefficient (hv), and a measured propagation phase differential (_dp(r)); classifying a melting layer; calculating a melting layer height and a distribution characteristic (melting depth) after classifying the melting layer, determining a two-dimensional fuzzy function in (_dp)-SNR relation and 10^hv-SNR relation, and calculating two fuzzy values (fuzzy function values) by using them; obtaining inference values for each object by using a fuzzy value of height and the prior two fuzzy values (fuzzy function values according to (_dp)-SNR, 10^hv-SNR relations); and managing quality and classifying hydrometers by selecting a maximum inference value (Max(RS)) among inference values of each object.
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