| 摘要: | 研究期間：10208~10307;For next five years, a network of three C-band dual polarization radars for accurate rainfall estimation will be set up in northern, central and southern Taiwan commonly by the Water Resources Agency (WRA) and Central Weather Bureau (CWB) to provide abundant polarimetric radar quantitative precipitation estimate (QPE). This project will utilize the multi-parameter multi-band rainfall estimation method, developed with the National Central University (NCU) C-band and X-band dual polarization radars (CPOL and TEAM-R), and S-band radar data to verify the precipitation estimation technique of this radar network. Dual polarimetric radars offer measurements such as reflectivity (Z), differential reflectivity (ZDR), differential phase (ΦDP), specific differential phase (KDP) and co-polar correlation coefficient (ρHV). In recent decades, a number of rainfall estimation algorithms utilizing these polarimetric parameters, e.g. R(Z), R(Z,ZDR) and R(KDP), are applied to dual polarization radars with different wavelengths and accurate results are obtained. In the first year (2013) of this project, the T-matrix scattering simulation will be applied to the calculation of polarimetric parameters with different raindrop size distributions at various bands (S, C, X). At the same time the CPOL and TEAM-R radar data as well as the disdrometerand rainguage data will be used to evaluate the accuracy of the precipitation estimation algorithm and the validity of the C-band and X-band radar attenuation correction statistics. This provides a valuable reference for the attenuation correction procedures of the new C-band radar network of WRA in the future. In the second and third year (2014, 2015), TEAM-R will be deployed beside new upgrade polarimetric Wu-Fen-Shan (WFS) radar and New Taipei city WRA precipitation radar for synchronized observations and verification. In recent years, many researchers developed different cloud microphysics schemes. In this project, the radar retrieval results can be compared with the drop size distribution, liquid water content and rainfall simulated by cloud-resolving models. By cooperation with model developers, we can suggest a more proper configuration of cloud microphysics schemes to enhance their capabilities of quantitative precipitation estimation and forecasting. Further verifications will be made in future rainfall experiments. |
