本研究探討使用四維變分方法(Four-Dimensional Variational Doppler Radar Analysis System :VDRAS)來同化雷達資料時，對短期數值天氣預報改善的程度。最終的目標在於建立一套適合台灣地區特殊地理條件的短期(0~6小時)定量降水預報方案。本研究規畫執行兩年，預期所要達到之研究目標如下： (1) 探討各種因素，如雷達與分析區域的相對位置、雷達資料的觀測誤差、不完整的資料覆蓋、雷達掃描策略、最佳的同化窗口、以及資料同化的策略等對雷達資料同化的結果會產生何種影響。 (2) 將V DRAS同化系統中的微物理過程由暖雨(warm rain)延伸到包含冰相的冷雨(cold rain)過程。 (3) 測試將VDRAS與另一個模式(如: WRF)嵌套後的效果。 (4) 使用真實的個案來測試本方法，這些真實個案的資料可以是在2008年西南氣流實驗當中，由NCAR S-POL、TEAM-R、氣象局七股雷達或墾丁雷達所觀測的結果。真實個案測試的重點在於探討短期定量降水預報的準確度。In this research we will assess the improvement of the short-term numerical weather prediction by assimilating Doppler radar data using the four-dimensional Variational Doppler Radar Analysis System (VDRAS). The major purpose is to construct a 0-6 hr QPF algorithm suitable for Taiwan’s geographic characteristics. This proposal is designed for the next two years. The research topics we would like to explore are listed in the following: (1) Study various factors that could affect the results of the radar data assimilation, such as radar viewing angle, radar data observational errors, incomplete data coverage, radar scanning strategy, optimal assimilation window, data assimilation strategy, etc. (2) Improve the VDRAS microphysical scheme by extending it from warm rain process to cold rain process. (3) Nesting VDRAS with another numerical model (e.g. WRF). (4) Testing VDRAS in real scenarios such as the cases collected during TIMREX/SOWMEX by NCAR S-POL, TEAM-R, RCCG or GCKT. The focus of these real case studies will be the short-term quantitative precipitation forecast (QPF). 研究期間 : 9808 ~ 9907
