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姓名	柯緁盈(Chieh-Ying Ke)  查詢紙本館藏	畢業系所	大氣科學學系
論文名稱	WRF-LETKF系統同化反演熱動力場與雷達資料：鋒面雨帶個案之分析探討 (Analysis of Assimilating Retrieval Thermodynamic Fields and radar data by the WRF-LETKF Assimilation System: A Case Study of Frontal Rainband)
相關論文	★ McGill Algorithm for Precipitation nowcasting using Lagrangian Extrapolation(MAPLE)即時預報系統在臺灣複雜地形之可行性評估：颱風與梅雨鋒面個案分析 ★ 利用系集法估計與檢驗對流尺度之預報誤差：SoWMEX IOP8 個案分析 ★ 不同微物理方案在雲可解析模式的系集預報分析: SoWMEX-IOP8 個案 ★ 藉由數值模式水平風場改善雷達回波外延即時預報系統:16個颱風個案統計分析 ★ 分析不同微物理參數化之系集預報誤差: SoWMEX-IOP8 對流個案 ★ 利用雙偏極化雷達觀測資料進行極短期天氣預報評估─2008年西南氣流實驗IOP8期間颮線系統個案 ★ 台灣地區對流胞特性統計分析與即時路徑預報之改善 ★ 評估TAHOPE觀測實驗同化S-PolKa徑向風、回波與折射指數對短期降雨預報的影響：觀測系統模擬實驗(OSSE)之測試 ★ 利用多頻道衛星觀測評估WRF數值模式於不同微物理方案之雲特性:以梅雨鋒面降水系統個案為例 ★ 使用局地系集轉換卡爾曼濾波器同化雙偏極化參數的全新方法：夏季真實個案中的分析場與預報場 ★ 台灣地區強對流胞即時預報與冰雹預警能力之分析與改善 ★ Extreme Heavy Rainfall Event on 01-02 June 2017 over Northern Taiwan Area: Analysis of Radar Observation and Ensemble Simulations ★ Investigating hygroscopic cloud-seeding effects in liquid-water clouds in northern Taiwan: in-situ measurements and model simulation ★ 同化雙偏極化雷達差異反射率之方法與影響評估：2021 年宜蘭降雨觀測實驗 IOP2 個案分析 ★ 利用三維回波移動場改善即時降雨預報並建構系集即時預報系統：臺灣梅雨鋒面及秋季降水個案分析 ★ 1950至2020全球海溫分布模式及其氣候影響:東部型與中部型ENSO的比較分析
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摘要(中)	台灣北部出現豪大雨的梅雨鋒面系統個案 2012 年 6 月 11 日， 10小時累積雨量多處超過400毫米，北部地區許多測站降雨紀錄創下歷史新高，造成北部各地出現淹水災情。本研究選用此個案，從雷達觀測資料分析，反演三維風場與熱動力場分析系統在台灣北部造成強降雨的複雜因素。進一步探討系集同化系統同化雷達資料，同時加入反演三維空間高解析熱動力場對於極端強降雨事件的降雨預報可行性探討。 研究利用高時空解析亦可解析地形的多都卜勒雷達風場反演技術(WISSDOM)與熱動力反演與水氣調整技術(TPTRS)，從反演結果得到三維風場、溫度、壓力與水氣三維結構結構。透過垂直渦度收支分析強降雨期間，對流尺度上地形噴流移動和強度的變化。研究發現，在台灣北部移速慢的梅雨鋒面，冷池前緣發展新的對流，受地形影響和加強的地形噴流形成Y型回波，對流被地形噴流往北推移和主對流合併加強系統，造就此歷史性的短延遲強降雨個案。 研究使用 WRF-LETKF 雷達同化系統，探討多尺度天氣系統中，同化雷達觀測資料之外，加入同化 3D 溫度和水氣資訊，進行可行性的影響評估。設計觀測系統理想模擬實驗，同化的熱動力變數來自理想無偏差或熱動力反演技術得到的熱動力變數。首先，理想實驗中同化兩小時的雷達資料顯示出比一小時更好的結構和短期降雨預測。其次，從同化雷達觀測變數和完美無偏差的熱力變數(溫度與水氣)分析結果顯示，當背景場出現降水位置誤差時，同化雷達資料加入溫度和/或水氣資訊一起同化，可以修正雨帶位置，縮短同化週期，得到較佳的預報分析場，並顯著改善定量降水預報。第三，進行反演熱力變數同化可行性研究。由於反演溫度和水氣存在偏差。加入反演溫度的資料同化實驗，由於溫度存在暖偏差，分析場的結果顯示，提升對流區的垂直運動和層狀區的冰相變數結構，並在極短期強降雨的預報有明顯效益。同化水氣助於重建近地表冷池的範圍和強度，但對三小時降雨預報的改進有限。同時加入同化反演溫度場和水氣場時，此實驗結果取得了最佳的分析，並能顯示降雨預報效益至少維持六小時。綜上所述，同化複雜降水系統中的三維熱力變數，此效益能縮短同化時間，提升最終分析場結構和短期降雨預報。
摘要(英)	A frontal system with extremely heavy rainfall was over Northern Taiwan on 11 June 2012. Through multiple analyses of three different Doppler radars, three-dimensional wind fields are retrieved over the ocean and the complex terrain of Taiwan by Wind Synthesis System using Doppler Measurements (WISSDOM). The pressure and temperature structure are derived from the retrieved wind fields by Terrain-Permitting Thermodynamic Retrieval Scheme (TPTRS). The migration and intensity of the barrier jets at convective scales are revealed by a vorticity budget analysis. It is found that, taken together, the stagnated Mei-Yu front, the location and the strength of the barrier jet and cold pool, as well as orographic blockage over northern Taiwan explain the formation of this quasi-stationary and extremely heavy rainfall case. This study examined the feasibility of assimilating 3D temperature and water-vapor information in addition to radar observations in a multiscale weather system. Using the WRF–LETKF Radar Assimilation System (WLRAS), we performed three sets of observing system simulation experiments to assimilate radar observations with or without thermodynamic variables obtained using different methods. First, assimilating the radar data for 2 h showed better structure and short-term forecast than 1 h. Second, we assimilated radar data and thermodynamic variables from a perfect model simulation. The results of the analysis revealed that when a precipitation position error was present in the background field, assimilating temperature and/or humidity information could correct the dynamic structure and shorten the spin-up assimilation period, resulting in substantial improvements to the quantitative precipitation forecast. Third, we applied a thermodynamics retrieval algorithm for a feasibility study. With a warm and wet bias of the retrieved fields, assimilating the temperature data had significant impact on the final analysis at the mid-level of stratiform areas and the forecast of the heavy rainfall was consequently improved. Assimilating the water vapor information helped reconstruct the range and intensity of the cold pool near the surface, but the improvement of 3-h rainfall forecast was limited. The optimal results of analysis and short-term forecast were achieved when both the retrieved temperature and water vapor fields were assimilated. In conclusion, assimilating thermodynamic variables in the precipitation system is feasible for shortening the spin-up period of data assimilation and improving the final analysis and short-term forecast.
關鍵字(中)	★ 雷達氣象 ★ 熱動力反演 ★ 資料同化 ★ 系集卡爾曼濾波	關鍵字(英)	★ radar meteorology ★ thermodynamic retrieval ★ data assimilation ★ EnKF
論文目次	中文摘要 IV English Abstract V 致謝 VI Table of contents VII List of Figures IX List of Tables VX Chapter 1 Introduction and Motivation 1 1.1 Introduction 1 1.2 Review of radar assimilation 3 1.3 Motivation of the study 6 Chapter 2 Methodology and Data Operator 9 2.1 Wind Synthesis System using Doppler Measurements (WISSDOM) 9 2.2 Terrain-Permitting Thermodynamic Retrieval Scheme (TPTRS) 11 2.3 Moisture and temperature adjustment scheme 13 2.4 WRF-LETKF Radar Assimilation System (WLRAS) 14 2.5 Observation data and Operator 18 Chapter 3 Case study: Mei-Yu front on 11 June 2012 21 3.1 Case review 21 3.2 Evolution of Reflectivity 22 3.3 Result of retrieval by WISSDOM and TPTRS at 1400 UTC 24 3.4 Evolution of Enhanced Barrier jet 26 3.5 Schematic diagrams of the extremely heavy rainfall event 27 Chapter 4 Experiments Design and Validation scores 30 4.1 Experiments design 30 4.2 Validation scores 35 Chapter 5 Result of OSSE and retrieval variables assimilation 37 5.1 Ensemble background error analysis 37 5.2 Performance of the cycling process 38 5.3 Analysis and Short-term forecast of OSSEs 40 5.4 Results of retrieval variables assimilation 47 Chapter 6 Conclusions and Future Works 51 6.1 Conclusions 51 6.2 Future works 53 References 56 Figures 68 Tables 95
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指導教授	鍾高陞(Kao-Shen Chung)	審核日期	2022-8-12
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