同化都卜勒雷達資料改善模式預報之研究

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题名:	同化都卜勒雷達資料改善模式預報之研究
作者:	尤心瑜;Hsin-yu Yu
贡献者:	大氣物理研究所
日期:	2009-06-18
上传时间:	2009-09-22 09:43:53 (UTC+8)
出版者:	國立中央大學圖書館
摘要:	本研究目的為探討:同化都卜勒雷逹資料及其所反演的大氣狀態變數，於改善劇烈風暴發展預報的可行性。而此研究方法的流程共包含以下三部份：雙都卜勒雷達風場反演、熱動力反演及水汽調整。研究共設計6組實驗，而所有的實驗都是在 OSSE實驗架構下進行，其測試內容如下:(a)研究方法完整流程的測試、(b)同化次數及同化時間間距的測試、(c)探討探空資料在同化過程中所扮演的角色、(d)測試同化都卜勒雷逹資料及反演氣壓場，並於同化過程中利用垂直動量方程式來得到溫度場，看其對模擬結果的影響。實驗結果顯示，經同化都卜勒雷逹觀測資料及其反演的大氣狀態變數後，的確改善初始條件微弱風暴的降水預報結果。於同化次數及同化時間間距的測試，則發現兩者對於改善預報降水的敏感度較低；而在同化過程中，給予探空資料將提升同化結果的準確度，並在此同化之後，再進行一次沒有探空資料的同化，於預報結果有更進一步的改善。而未來最重要的工作目標，則是將本研究方法，應用在真實個案上，期望在實際作業上能改善定量降水的預報能力。 The purpose of this study is to explore the feasibility of assimilating atmospheric state variables observed as well as derived from Doppler radar data to improve the prediction of a thunderstorm development. In the methodology, the complete algorithm is composed of three steps, namely (1) wind retrieval, (2) thermodynamic retrieval, and (3) moisture adjustment. The performance of the proposed method is investigated by six experiments, and all of them are conducted under the framework of OSSE (Observation System Simulation Experiment). From these experiments, it is attempted to address the following issues: (1) verification of proposed method (2) the impact of the assimilation frequency and assimilation time interval, (3) influence of assimilating with/without sounding data, and (4) influence of assimilating Doppler radar data and retrieval pressure field only. In (4), the vertical momentum equation is utilized to obtain the absolute potential temperature fields. The results demonstrate that the accuracy of storm rainfall prediction can be improved after assimilating observed/retrieved atmosphere state variables from Doppler radar data. However, the impact on rainfall prediction from the assimilation frequency and time interval is insignificant. By contrast, the model forecast can be improved substantially if the data from a sounding released within the analysis domain is available. Furthermore, after the first assimilation with sounding, if one conducts a second assimilation even without the information from sounding observations, additional improvements can be achieved. The application of this method to real case study would be a natural extension of this study in the future.
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