16B.4 A Localized Quantitative Precipitation Estimation for S-Band Polarimetric Radar in Taiwan

Friday, 1 September 2023: 8:45 AM
Great Lakes A (Hyatt Regency Minneapolis)
Yu-Shuang Tang, Central Weather Administration, Taipei, Taiwan; and P. L. Chang, W. Y. Chang, L. Tang, P. F. Lin, J. Zhang, and C. R. Chen

A polarimetric radar quantitative precipitation estimation (QPE) to estimate rain rate (R) from specific attenuation (A) [R(A)] has been applied in Taiwan's operational Multi-Radar Multi-Sensor QPE System. A 3-yrs' (2016-2018) drop size distribution (DSD) dataset from an operational Parsivel network was used to derive a localized coefficient in the R(A) relationship as well as a localized α(K) function where α is a key parameter in the estimation of A and K is the Zdr/Z slope. Experiments from DSD data indicate that the localized α(K) function significantly improves the R(A) QPE. The normalized mean error of rainfall estimation gains about 12 % of improvement. On the other hand, the localized R(A) coefficient shows a less pronounced difference with current operational R(A) coefficients. Experiments using radar observations in Mei-Yu front cases also showed the advantages of the DSD-derived coefficients. For Mei-Yu cases, the localized R(A) algorithm reduces normalized mean error by 13% over the operational R(Z), but with a higher RRMSE. The localized QPE coefficients are then applied to a synthetic QPE system that merges and takes advantages of R(Z), R(A), and R(KDP) and showed about 11% reduction in RRMSE by 3% reduction in normalized mean error Mei-Yu cases. These results indicated great potentials of localized R(A) coefficients derived from the disdrometer data to improve the accuracy of the operational rainfall estimation products.
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