Presented on February 21, 2024, by

Shu-Chih Yang, Distinguished Professor
Department Chair of Atmospheric Sciences
Director of GPS Science and Application Research Center
National Central University, Jhongli, Taiwan


A multi-scale radar ensemble data assimilation system has been developed by applying the successive covariance localization (SCL) to the WRF-Radar LETKF assimilation system (WLRAS). The multi-scale WLRAS is applied to study a heavy rainfall event that occurred on 6-7 June 2022 during the IOP3 in the Taiwan-Area Heavy rain Observation and Prediction Experiment (TAHOPE)/Prediction of Rainfall Extremes Campaign In the Pacific (PRECIP) field campaign. Two experiments are conducted and they differ only in using the convective-scale (RDA) or multi-scale corrections (MRDA) in the assimilation of radar radial velocity. The objective of this study is twofold. One is to evaluate the benefit of using multi-scale WLRAS by comparing RDA and MRDA. The other is to understand the mechanisms of the convection development at the western coast of Taiwan as the mei-yu front hovers in northern Taiwan.

Compared to RDA, theMRDA experiment exhibits large-area wind corrections, which help reshape and relocate a low-level meso-vortex offshore of western central Taiwan and enhance the frontal intensity offshore of northwestern Taiwan. Consequently, the MRDA improves the heavy very short-term (6h) rainfall prediction over the coast of western Taiwan and better represents the elongated rainband in northern Taiwan during the 3 to 6-h forecast hours. Sensitivity experiments demonstrate the importance of assimilating the radial wind of Chigu and S-Pol radars in establishing the low-level meso-vortex and convergence zones. Although a significant impact on rainfall prediction can be obtained from updating the moisture variable with the SCL method, the moisture correction at far distances may be less reliable.