研究期間：10208~10307;Heavy rainfall is a primary cause of natural hazards such as flash floods and landslides, which are usually accompanied by loss of life and property. Thus, the accuracy of the short-term QPF plays an important role in disaster prevention and mitigation. This project aims to use a WRF-LETKF radar data assimilation system and its OSSE findings with respect to Typhoon Morakot (2009) to optimize the grid setting and physics of the model as well as the observation operator in this system. This system will be applied to more numerical experiments on other selected cases including heavy rainfall events triggered by Mei-Yu fronts. The improvement of the short-term QPF for severe weather systems at meso- and micro-scales including the PQPF performance offered by this ensemble data assimilation system will be examined to evaluate its applicability in real cases. Since LETKF can assign different covariance inflation factors and spatial localization weights to different model variables, we are testing a more proper use of the ensemble-based multivariate correlations and consequently higher analysis accuracy in this system. In addition, the parallel computing efficiency will be enhanced to assimilate more radar data, with larger domains and finer resolutions with a view to facilitating a more complete evaluation of the forecast skills for various types of severe precipitation systems. In the future, this system can provide the research and operational NWP centers of the government with applicable products for the fulfillment of this project goal.