| Popis: |
Raindrop size distribution (DSD) has an essential effect on rainfall kinetic energy estimation (RKEE) and dual-polarization radar quantitative precipitation estimation (QPE); DSD is a key factor for establishing a dual-polarization radar QPE scheme and RKEE scheme, particularly in mountainous areas. To improve the understanding of seasonal DSD-based RKEE, dual-polarization radar QPE, and the impact of rainfall types and classification methods, we investigated RKEE schemes and dual-polarimetric radar QPE algorithms across seasons and rainfall types based on two classic classification methods (BR09 and BR03) and DSD data from a disdrometer in the Tianshan Mountains during 2020–2022. Two RKEE schemes were established: the rainfall kinetic energy flux–rain rate (KEtime–R) and the rainfall kinetic energy content–mass-weighted mean diameter (KEmm–Dm). Both showed seasonal variation, whether it was stratiform rainfall or convective rainfall, under BR03 and BR09. Both schemes had excellent performance, especially the KEmm–Dm relationship across seasons and rainfall types. In addition, four QPE schemes for dual-polarimetric radar—R(Kdp), R(Zh), R(Kdp,Zdr), and R(Zh,Zdr)—were established, and exhibited characteristics that varied with season and rainfall type. Overall, the performance of the single-parameter algorithms was inferior to that of the double-parameter algorithms, and the performance of the R(Zh) algorithm was inferior to that of the R(Kdp) algorithm. The results of this study show that it is necessary to consider different rainfall types and seasons, as well as classification methods of rainfall types, when applying RKEE and dual-polarization radar QPE. In this process, choosing a suitable estimator—KEtime(R), KEmm(Dm), R(Kdp), R(Zh), R(Kdp,Zdr), or R(Zh,Zdr)—is key to improving the accuracy of estimating the rainfall KE and R. |
