Optimization of Fuzzy Logic-based Hydrometeor Classification using 2DVD Observations over the Korean Peninsula

  The Korean Peninsula is characterized by a diverse range of precipitation types, including hail, heavy rainfall, sleet, snow, and freezing rain. These conditions necessitate accurate Hydrometeor Classification (HC) to ensure public safety and effective infrastructure management. The Weather Radar Center (WRC) of the Korea Meteorological Administration (KMA) operates a dual-polarization radar network and provides real-time HC products. In this study we introduce an advanced HC techniques optimized for the meteorological characteristics of South Korea based on dual-polarization radar.

  The HC algorithm is based on fuzzy logic, integrating dual-polarization variables with numerical model temperature data. To ensure the reliability of the dual-polarization variables, we corrected the attenuation in reflectivity (ZH) and differential reflectivity (ZDR) caused by beam blockage and radome attenuation. Furthermore, as the correlation coefficient (ρhv) tends to decrease with radar range, it was adjusted in low Signal-to-Noise Ratio (SNR) regions. Bilateral filtering was also employed to suppress observational noise. Based on these quality-controlled inputs, the fuzzy logic algorithm utilizes membership functions (MBFs) and weights for each radar variable and temperature to determine the most probable hydrometeor type for each radar bin. The MBFs were localized and optimized using drop size distribution data from a 2-Dimensional Video Disdrometer (2DVD). To mitigate discontinuities in classified hydrometeors caused by model-derived temperature, the melting layer height derived from dual-polarization variables was incorporated, enabling more precise discrimination between liquid and solid phases. Additionally, spatial continuity was enhanced through a mode filter technique.

  The improved HC algorithm was evaluated using ground-based hail observations from weather stations and more accurately distinguished hail from heavy rain. Furthermore, in temperature advection cases, the incorporation of the melting layer height allowed for more consistent classification of both liquid and solid phases. These results suggest that the proposed method improves the relibality of HC and has the potential to enhance real-time weather monitoring and hazard mitigation.