Abstract: By using the X-band dual polarization radar observation data from the National (Weining) Hail Suppression Experimental Base,based on the de-folding of radar differential propagation phase shift,comprehensive wavelet denoising,and adaptive attenuation correction of radar reflectivity,the Barnes interpolation method is used to interpolate the polarization parameters,and the recognition of cloud water particles based on fuzzy logic algorithm is fully considers the particle ambient temperature.The improved hydrometeor recognition algorithm was used to observe and test a hailstorm process.The results showed that the identification of high-altitude hail occurred 26 minutes earlier than the observed hail time on the ground.The identified hail period and area were in good agreement with the ground observation,and the rationality of the improved hydrometeor recognition algorithm has been fully verified.At the same time,the identified distribution of particles at different heights is consistent with the actual development stages of hailstorms.The changes among high-density graupel,low-density graupel,supercooled water,and hail particles during the evolution of hailstorms are consistent with the microphysical mechanisms of hail formation.The improved hydrometeor recognition algorithm based on X-band dual polarization radar can provide theoretical basis and technical support for early identification and warning of hailstorms,artificial hail suppression operations,and evaluation of hail suppression operation effectiveness.