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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/61884


    Title: 四維變分都卜勒雷達分析系統於複雜地形之定量降雨預報研究
    Authors: 廖宇慶;蔣育真
    Contributors: 國立中央大學大氣科學學系
    Keywords: 大氣科學
    Date: 2014-03-10
    Issue Date: 2014-03-11 09:44:33 (UTC+8)
    Publisher: 交通部中央氣象局
    Abstract: 研究期間:10301~10312;Due to the particular geography and topography, the quantitative precipitation forecast (QPF) of severe weather in Taiwan becomes much more challenging. Currently, there are nine ground based weather radars around the island and also one mobile dual-polarimetric doppler radar in service. Therefore, it will be a significant issue related with both research and operation that how to optimally use those numerous radar data to further improve the performance of precipitation forecast in Taiwan. The tool used in this project is Variational Doppler Radar Analysis System (VDRAS), which assimilates radar data by four-dimensional variational data assimilation(4DVAR)technique. Many successful applications done by VDRAS were already shown including nowcasting in Sydney Olympic Games (Crook and Sun, 2002), forecast of thunderstorm in STEPS field experiment (Sun, 2005), Squall line forecasting in IHOP experiment (Sun and Zhang, 2008), the Pentagon shield field program (Warner et al., 2007) and nowcasting for Beijing Olympic Games (Sun et.al., 2010). From the above, VDRAS has become a mature and robust system. However, it couldn’t resolve terrain effect by its cloud model even now. In order to apply VDRAS to QPF in Taiwan, Tai et. al (2011) found reinitialize the WRF by VDRAS analysis and then forecast by WRF model could improve the performance of short-term QPF. But it would be better VDRAS can analyze with terrain effect. In this case, we try to apply immersed boundary method to construct the ability of resolving terrain effects without modifying coordinates. In the future, VDRAS can assimilate radar data and forecast in complex terrain areas like Taiwan to provide a more suitable plan for short-term QPF (0 to 3 hours).
    Relation: 財團法人國家實驗研究院科技政策研究與資訊中心
    Appears in Collections:[大氣科學學系] 研究計畫

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