The dynamics of severe convective storms depend, to some extent, on the distribution and type of hydrometeors within the storm. In order to estimate the three-dimensional distribution of hydrometeors using X-band radar data, it is necessary to correct for attenuation before applying any hydrometeor classification system. Since 2002, a mobile, dual-polarized Doppler weather radar designed at the University of Massachusetts Amherst has been used to collect high-resolution data in severe convective storms in the Plains. This study tests several attenuation correction procedures using dual-polarization measurements, along with a dual-frequency method using WSR-88D and KOUN data. After correcting for attenuation and differential attenuation, a fuzzy logic hydrometeor classification algorithm, modified for X-band with KOUN data as a reference, is used to attempt a retrieval of hydrometeor types in observed severe convective storms. Hydrometeor classification of high-resolution radar data in close proximity to supercells and tornadoes may help shed light on the dynamical processes of the production of cold pools in supercells, as well as provide a form of verification to which numerical models can be compared.