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I-Han Chen
Yi-Jui Su
Hsiao-Wei Lai
Jing-Shan Hong
Chih-Hsin Li
Pao-Liang Chang
, and
Ying-Jhang Wu


A 16-member Convective-scale Ensemble Prediction System (CEPS) developed at the Central Weather Bureau (CWB) of Taiwan is evaluated for probability forecasts of convective precipitation. To address the issues of limited predictability of convective systems, the CEPS provides short-range forecasts using initial conditions from a rapid-updated ensemble data assimilation system. This study aims to identify the behavior of the CEPS forecasts, especially the impact of different ensemble configurations and forecast lead times. Warm-season afternoon thunderstorms (ATs) from 30 June to 4 July 2017 are selected. Since ATs usually occur between 13 and 20 LST, this study compares deterministic and probabilistic quantitative precipitation forecasts (QPFs) launched at 05,08, and 11 LST.

This study demonstrates that initial and boundary perturbations (IBP) are crucial to ensure good spread-skill consistency over the 18-h forecasts. On top of IBP, additional model perturbations have insignificant impacts on upper-air and precipitation forecasts. The deterministic QPFs launched at 11 LST outperform those launched at 05 and 08 LST, likely because the most-recent data assimilation analyses enhance the practical predictability. However, it cannot improve the probabilistic QPFs launched at 11 LST due to inadequate ensemble spreads resulting from limited error growth time. This study points out the importance of sufficient initial condition uncertainty on short-range probabilistic forecasts to exploit the benefits of rapid-update data assimilation analyses.

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