Improvement of a Dual-Polarization Radar Operator for Ice-phase Microphysical Terms

Dual-polarization (dual-pol) radar variables provide information about the quantity, type, size, and water content of hydrometeors. Assimilating these dual-pol radar variables into numerical weather prediction models can enhance forecast accuracy. Observation operators are essential for radar data assimilation. This study focuses on applying a realistic dual-pol radar observation operator to more accurately calculate dual-pol radar variables. Jung et al. (2008)’s dual-pol radar observation operators tended to overestimate radar variables near 0°C in convective precipitation and simulate unrealistic dual-pol radar variables in subfreezing regions. To address this, the improved operator (KNU dual-pol radar observation operator; K-DROP) limits the distribution of mixed-phase hydrometeors, which have both solid and liquid properties, in areas with strong updrafts and downdrafts, improving the overestimation of radar variables near the melting layer. Additionally, by applying the snow axis ratio of observed during winter to the K-DROP, the issue of differential reflectivity (Z_DR) being calculated as a constant value in subfreezing regions has been improved. By incorporating the observed maximum radius of hydrometeors into the K-DROP, the overestimation of reflectivity (Z_H) in subfreezing regions, the overestimation of Z_DR in warm regions, and the underestimation of specific differential phase (K_DP) in subfreezing regions and overestimation in warm regions are improved. Compared to the previous operator, the enhanced version produces more realistic dual-pol radar variables.