Estimating Rain Microphysical Characteristics Using S-Band Dual-Polarization Radar in South Korea

Abstract

Raindrop size distribution (DSD) observed using a disdrometer can be represented by a constrained-gamma (C-G) DSD model based on the empirical relationship between shape (µ) and slope (Λ). The C-G DSD model can be used to retrieve DSDs and rain microphysical parameters from dual-polarization radar measurements of reflectivity (ZH) and differential reflectivity (ZDR). This study presents a new µ–Λ relationship to characterize rain microphysics in South Korea using a two-dimensional video disdrometer (2DVD) and Yong-in S-band dual-polarization radar. To minimize sampling errors from the 2DVD and radar measurements, measured size distributions are truncated by particle size and velocity-based filtering and compared with rain gauge measurement. The calibration biases of radar ZH and ZDR were calculated using the self-consistency constraint and vertical pointing measurements. The derived µ–Λ relationship was verified using the mass-weighted mean diameter (Dm) and standard deviation of the size distribution (σm), calculated from the 2DVD, for comparison with existing µ–Λ relationships for Florida and Oklahoma. The Dm–σm relationship derived from the 2DVD corresponded well with the µ–Λ relationship. The µ–Λ relationship derived for the Korean Peninsula was similar to Florida, and both generally had larger µ values than Oklahoma for the same Λ. The derived µ–Λ relationship was applied to retrieve DSD parameters from polarimetric radar data, and the retrieved DSDs and derived physical parameters were evaluated and compared with the 2DVD measurements. The polarization radar-based C-G DSD model characterized rain microphysics more accurately than the exponential DSD model. The C-G DSD model based on the newly derived µ–Λ relationship performed the best at retrieving rain microphysical parameters.

Characteristics of the Bright Band Based on Quasi-Vertical Profiles of Polarimetric Observations from an S-Band Weather Radar Network

“…Recently, quasi-vertical profiles (QVPs) of polarimetric observations (described in more detail in Section 3) were used to investigate the vertical structure and microphysical processes of the precipitation system [22][23][24][25]. Kumjian et al [22] first used QVP to detect refreezing signals of precipitation during winter storms.…”