4.1 Article

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

期刊

JOURNAL OF THE METEOROLOGICAL SOCIETY OF JAPAN
卷 98, 期 6, 页码 1129-1146

出版社

METEOROLOGICAL SOC JAPAN
DOI: 10.2151/jmsj.2020-057

关键词

dual-frequency radar; snow; particle size distribution; single particle scattering; Global Precipitation Measurement; Dual-frequency Precipitation Radar snow retrieval

资金

  1. NASA Headquarters under NASA's Precipitation Measurement Mission (PMM) Grant [NNH 18ZDA001N-PMMST]

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Dual-frequency Ku/Ka-band radar retrievals of snow parameters such as liquid-equivalent snowfall rate (R) and mass-weighted diameter (D-m) 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 (mu) equal to 0 (or exponential distribution) provides the best estimates of R and D-m. This is despite negative biases of up to -15 % in R and underestimates and overestimates in D-m for small and large D-m, respectively. The mu = 0 assumption, however, produces relatively poor estimates of normalized intercepts of a gamma PSD (N-w), whereas the best estimates are obtained when mu 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 D-m and N-w and their dependence on mu

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