Evaluation of the Short-Range Weather Application over Taiwan: A Focus on Extreme Precipitation Forecasts

Assessing the performance of a limited-area model (LAM) based on an emerging dynamical core such as the finite-volume cubed-sphere (FV3) in regional forecasting is essential to advancing existing operational systems. In this study, we configure an FV3-LAM using the Short-Range Weather Application and evaluate its performance in forecasting extreme precipitation over Taiwan, referred to as the SRW-TW experiment. We conduct the simulation of SRW-TW over ten selected cases of different rainfall types between 2019 and 2022, and then compare the simulated rainfall with the Quantitative Precipitation Estimation (QPE) and Segregation Using Multiple Sensors (QPESUMS) data and WRF-based forecasts as the ground reference and baseline product, respectively. By examining the simulated rainfall patterns and various performance metrics, we find that SRW-TW exhibits slightly higher correlation coefficient and critical success index values relative to the WRF baseline, although the differences are not statistically significant. However, SRW-TW performs slightly worse than the WRF baseline in terms of bias and frequency bias metrics. Our findings indicate that SRW-TW generates more realistic rainfall patterns but tends to underestimate precipitation, particularly in southwesterly flow-related events. Additionally, forecasting typhoon rainfall and hourly-scale precipitation remains challenging, requiring further model refinement and the potential development of a bias-correction scheme.