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以作者查詢圖書館館藏 、以作者查詢臺灣博碩士 、以作者查詢全國書目 、勘誤回報 、線上人數：34 、訪客IP：3.21.46.26
姓名 戴聖倫(Sheng-lun Tai) 查詢紙本館藏 畢業系所 大氣物理研究所 論文名稱 使用四維變分同化都卜勒雷達資料以改進短期定量降雨預報
(Improving short-term quantitaive precipitaion forecast by assimilating doppler radar observations with the four-dimensional variational technique.)相關論文 檔案 [Endnote RIS 格式]
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摘要(中) 前人研究曾經利用美國國家大氣研究中心（NCAR）所發展之都卜勒雷達變分分析系統(Variational Doppler Radar Analysis System, VDRAS），即時分析低層風場及輻合/散場以進行雷暴雨之預報，也曾同化單一或多個都卜勒雷達觀測資料以分析並預報超大胞與颮線系統，但大多使用於廣大開闊的平原地區，本研究則首次將VDRAS 應用在臺灣四面環海且地形複雜的環境。
為了檢視此同化系統應用於臺灣及鄰近地區的表現，吾人選取2008 年SoWMEX/TiMREX（西南氣流實驗）IOP8（第八次密集觀測期）中6 月14 日的鋒面系統作為研究個案，匯集探空、地面測站等觀測資料進行模式中背景場分析，並且利用VDRAS 同化中央氣象局七股及墾丁兩座S-band 都卜勒雷達之觀測資料（包含回波以及徑向風），藉此完成雲模式初始化得到最佳分析場，最後再由分析場進行預報。同時，為了探討地形對於定量降水預報的影響程度，吾人更嘗試將VDRAS 之最佳分析場與具有地形解析能力的WRF 模式進行結合預報，並比較其中差異。
檢視同化後的分析場，發現VDRAS 能合理分析天氣系統的動力及熱力結構；在預報場方面，模式對於主要線狀對流之移動方向有很好的掌握，故兩小時累計降水預報在門檻值6mm 之ETS score 為0.21。如將VDRAS 與WRF 結合進行預報，兩小時累計降水預報ETS score 在6、10、14、18mm 的降雨門檻皆較單獨使用VDRAS 及WRF 的預報為佳，其中與WRF 預報結果差距更加明顯。
摘要(英) In previous research the variational Doppler Radar Analysis System (VDRAS), developed by National Centers for Atmospheric Sciences (NCAR), had been applied in real-time analysis of low-level wind and convergence for nowcasting of thunderstorms. By assimilating single or multiple-Doppler radar observations, VDRAS was also utilized to analyze and forecast the super-cells and squall lines. However, most of those experiments were conducted in a wide open region with flat surface. In this study, it was attempted for the first time to apply VDRAS in Taiwan and her vicinity, where the topography over the island set a complicated geographic environment, and the surrounding oceans limited any type of observations except meteorological radars. These two factors posed a challenging task to the success of the model forecast of meso-scale precipitation systems.
In order to test the performance of VDRAS in Taiwan area, a real case of Mei-Yu front, occurred on 14 June 2008 during Southwest Monsoon Expeiment/Terrain-Influenced Monsoon Rainfall Experiment (SoWMEX/TiMREX) IOP8, was chosen. The background field was prepared using observations from soundings and surface stations. Radar data collected by two Central Weather Bureau S-band radars, located at Cigu and Kenting respectively, were assimilated into VDRAS. Through the minimization of a cost function under the constraint of a numerical model (i.e., the 4DVAR method), an optimal analysis field was obtained for initialization, then followed by model forecasts. Furthermore, in order to investigate the influence on Quantitative Precipitation Forecast (QPF) by terrain effects, a series of forecasting experiments were designed in which the VDRAS analysis fields were carefully merged with Weather Research and Forecasting (WRF) model. The latter is known to have a better capability to resolve complex terrain.
Analysis fields obtained from assimilating radar data showed that VDRAS could produce dynamical and thermodynamic structures of a weather system rather reasonably. The model forecast, starting from the optimal analysis field, also agrees well with observations in terms of the moving direction of the main convective systems. The ETS score of two hours accumulated rainfall forecast at 6-mm threshold is 0.21. It was found that the QPF scores achieved by combining VDRAS and WRF could significantly exceed those of using WRF or VDRAS alone. Apparently this was attributed to the assimilation of radar data into VDRAS and the terrain-resolving capability of WRF.
關鍵字(中) ★ 都卜勒雷達變分分析系統
★ 四維變分同化關鍵字(英) ★ 4DVAR
★ VDRAS論文目次 中文摘要................................................i
英文摘要................................................ii
誌謝........................................................iv
目錄........................................................v
圖表說明................................................vii
第一章：緒論
1-1：前言...............................................1
1-2：文獻回顧.......................................2
1-3：研究目的.......................................3
第二章：雷達資料同化系統
2-1：都卜勒雷達變分分析系統...........4
2-1-1：雲模式........................................4
2-1-2：價值函數....................................5
2-1-3：伴隨模式....................................7
2-2：中尺度背景場................................8
2-3：雷達資料控管與處理....................10
第三章：個案介紹
3-1：2008 年西南氣流實驗..................12
3-2：綜觀天氣........................................12
3-3：雷達合成最大回波........................13
第四章：驗證方法
4-1：定量降水預報校驗........................15
4-1-1：降雨量計算與內插.....................15
4-1-2：校驗得分與指數.........................16
4-2：風場驗證........................................17
第五章：VDRAS 之分析與預報
5-1：模式設定與實驗設計....................19
5-2：中尺度背景場................................20
5-3：分析場............................................21
5-4：預報場............................................24
第六章：VDRAS 與WRF 結合預報
6-1：結合方法........................................27
6-1-1：模式比較.....................................27
6-1-2：資料內插方法.............................28
6-1-3：結合變數處理.............................28
6-1-4：平滑與調整方法.........................30
6-2：實驗設計........................................31
6-3：預報結果........................................32
第七章：結論與未來展望
7-1：總結................................................35
7-2：未來展望........................................36
參考文獻.................................................38
附表.........................................................41
附圖.........................................................43
參考文獻 鄧仁星，2000：RASTA(Radar Analysis System for Taiwan Area)使用說明書。
簡芳菁、洪景山、張文錦、周仲島、林沛練、林得恩、劉素屏，繆睿如、陳致穎，2006：WRF 模式之敏感度測試，第二部分：定量降水預報校驗，大氣科學，第34 期，第3 卷，261-276。
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指導教授 廖宇慶(Yu-chieng Liou) 審核日期 2010-7-26 推文 plurk
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