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Hyokyung Kim

Publications and source records attributed to Hyokyung Kim.

Path Attenuation Estimates for the GPM Dual-Frequency Precipitation Radar (DPR)

Estimation of path attenuation is a critical part of retrieving precipitation parameters using measurements from the Dual-Frequency Precipitation Radar (DPR) on board the Global Precipitation Measurement Mission (GPM) satellite. In this paper, we describe the latest implementation of the Surface Reference Technique that uses surface scattering properties to infer path attenuation through the precipitation. Both single- and dual-frequency versions of this method are available and while the dual-frequency version appears to be more accurate at moderate rain rates, the single-frequency approach at Ku-band is needed when the Ka-band data are not available. Despite improvements afforded by the dual-frequency version of the method, other methods such as the Hitschfeld-Bordan and standard dual-frequency approaches offer advantages particularly at lighter rain rates and at near-nadir incidence angles over land. Weighted averages of the results from these methods appear to offer the best estimate of path attenuation presently available.

attenuation↗

Assessment of Ku- and Ka-band Dual-Frequency Radar for Snow Retrieval

Dual-frequency Ku/Ka-band radar retrievals of snow parameters such as liquid-equivalent snowfall rate (R) and mass-weighted diameter (Dm) have two principal errors, namely, the differences between the assumed particle size distribution (PSD) model from the actual PSD and inadequacies in characterizing the single-scattering properties of snowflakes. Regarding the first issue, this study, based on radar simulations from a large amount of observed PSD data, shows that there exist relatively high correlations between the estimated snow parameters and their true values derived directly from the measured PSD. For PSD data with R greater than 0.1 mm h−1, a gamma PSD model with a fixed shape factor (μ) equal to 0 (or exponential distribution) provides the best estimates of R and Dm. This is despite negative biases of up to −15 % in R and underestimates and overestimates in Dm for small and large Dm, respectively. The μ = 0 assumption, however, produces relatively poor estimates of normalized intercepts of a gamma PSD (Nw), whereas the best estimates are obtained when μ is considered either 3 or 6. However, the use of an inappropriate scattering table increases the errors in snow retrieval. Simple evaluations are made for cases where the scattering databases used for the algorithm input differ from that used for retrieval. The mismatched scattering databases alone could cause at least 30 %-50 % changes in the estimates of snow water content (SWC) and R and could affect the retrievals of Dm and Nw and their dependence on μ.

Liang Liao↗

Assessment of Ku- and Ka-Band Dual-Frequency Radar for Retrieval of Snow Properties

Current scattering look-up tables for snow assume a constant mass density along with a Gamma particle size distribution (PSD). The first assumption is tested against scattering parameters from simulated particle models generated by Dr. Kwo-Sen Kuo at GSFC and Dr. Guosheng Liu at FSU. Good agreement of the scattering parameters is found with the FSU results if the mass is taken to be the same as the mass of the simulated particle and the mass density is taken to be 0.2 g/cm cu. For the GSFC data base, good agreement is found if the mass density is taken to be between 0.1 and 0.2 g/cm cu. The second assumption of a Gamma PSD is tested against measured PSD's along with a m-d (mass-dimension) relationship. The degree of agreement depends on the value of, the 'shape' parameter in the Gamma distribution but to a lesser degree on the m-d relationship (of the three that were examined). A shortcoming of the simulated snow particle data bases is the lack of large particles. As a consequence, larger values of DFR (dual-frequency ratio) that are commonly seen in airborne and spaceborne measurements cannot be reproduced from the tables. This situation is expected to improve as scattering parameters from larger particles are included in the databases.

Liang Liao↗