Investigating hygroscopic cloud-seeding effects in liquid-water clouds in northern Taiwan: in-situ measurements and model simulation

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姓名	林凱翊(Kai-I Lin) 查詢紙本館藏	畢業系所	大氣科學學系
論文名稱	(Investigating hygroscopic cloud-seeding effects in liquid-water clouds in northern Taiwan: in-situ measurements and model simulation)
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摘要(中)	全球暖化導致乾旱之強度與頻率增加；於2021年，台灣亦面臨近百年來最為嚴重之乾旱，也因此促使政府嘗試發掘解決辦法，而吸濕性粒子種雲似乎為一種兼具可行性與可能性之方法，用以解決水資源匱乏之問題。本研究嘗試結合現地觀測與數值模擬，探究吸濕性氣膠種雲在種雲過程中所需要的環境條件及雲微物理變化特徵，針對北台灣集水區建立人工種雲與降雨的個案研究，並提出一個有效且具科學基礎的人工種雲策略。在2019-2021年期間，吾人針對台灣乾季共實施了4次東眼山種雲觀測實驗，建立高時間解析度之氣象與氣膠觀測，觀測結果發現：種雲焰劑之施放導致水氣競爭效應以及凝結過程的產生，並且於施放地域生成更多的雨滴。在數值模擬方面，吾人利用WRF模擬2020年10月21-22日之種雲實驗個案，以自行開發之雲微物理參數化方案(WDM6-NCU)進行雲微物理模擬，WDM6-NCU雲微物理參數化方案可利用43個細格描述雲凝結核之粒徑分布，可給定觀測所得之種雲焰劑粒徑分布，更真實及完整地計算雲凝結核之活化過程，模式模擬結果顯示：就人工種雲效率來說，雲內種雲相較於在雲底種雲可以增加更多降水，且增加種雲播撒面積與種雲粒子濃度可以增加數倍的降水生成；對於雲微物理過程，雨滴之碰併過程的增強為造就降水增加之主要原因，且吸濕性粒子大於0.4 μm有助於引發後續一連串成雲降雨過程。整體而言，本研究開發出一套本土化的人工種雲氣象模式，成功地解釋暖雲種雲至降雨之過程，搭配觀測資料之分析與驗證，可做為未來人工種雲實務作業之重要依據。
摘要(英)	Global warming causes droughts to increase in intensity and frequency. In 2021, Taiwan faced the most serious drought in the past hundred years, prompting Taiwan government to seek ways to deal with the problems of water scarcity. Hygroscopic cloud seeding seems to be a possible solution to create more water resources. The goals of this study attempt to investigate the suitable environmental conditions for hygroscopic cloud seeding and its impacts on cloud microphysics by both observation and model simulation. Furthermore, based on a case study of hygroscopic cloud seeding in northern Taiwan catchment, an effective and scientific strategy of hygroscopic cloud seeding seeks to be proposed. During 2019-2021, four Dongyan mountain cloud-seeding experiments were executed with meteorological and aerosol observation, and the results indicate that: the seeding agents can strengthen the competition effect and the condensation process. Moreover, the concentration of raindrops increases after doing cloud seeding. For model simulation, the WRF model with a hybrid cloud-seeding microphysics scheme, WDM6-NCU, which is able to describe seeded CCNs size distribution by 43 bins and precisely evaluate the activation of seeded CCNs, is used to simulate the case on 21-22 October 2020 with a series of sensitivity tests on cloud seeding. Results of model simulation show that: more precipitation is developed in the scenarios seeding at the in-cloud region, and seeding in a bigger domain and higher hygroscopic particles concentration are able to increase several folds of rainfall. Regarding the microphysics processes, the main reason causes the enhancement of precipitation is the strengthening of the accretion process of raindrops, and those hygroscopic particles bigger than 0.4 μm are the main factor contributing to cloud-seeding effects. In conclusion, this study develops a hybrid cloud-seeding microphysics scheme, which successfully explains the process from launching cloud seeding to developing rainfall and matches the features of observation data. In addition, the results of this study can be used as a guidance for the future operation of cloud seeding in Taiwan.
關鍵字(中)	★ 吸濕性粒子種雲 ★ 雲微物理過程 ★ 競爭效應 ★ 尾巴效應	關鍵字(英)	★ Hygroscopic particle seeding ★ cloud microphysical process ★ competition effect ★ tail effect
論文目次	摘要 i Abstract ii Acknowledgment iv Outline v Table list viii Figure list ix Chapter 1. Introduction 1 Chapter 2. Cases overview 5 Chapter 3. Data and method 12 3.1 Dongyan Mountain cloud-seeding experiment 12 3.1.1 Experiment design and data description 12 3.2 Chamber sampling experiment of seeding agent 15 3.2.1 Experimental description and design 15 3.3 Model simulation of Miaopu validation experiment 17 3.3.1 Model configuration 17 3.3.2 The WDM6 scheme (Lim and Hong, 2010) 20 3.3.3 The WDM6-NCU scheme 22 3.3.4 Experiment design 23 Chapter 4. Results and discussion 27 4.1 Dongyan mountain cloud-seeding experiment 27 4.1.1 Case1 on 2020/10/22 28 4.1.2 Case2 on 2021/04/28 31 4.2 Chamber sampling experiment of seeding agent 40 4.2.1 The size distribution and number concentration of the seeding agent 40 4.3 Modeling of Miaopu validation experiment in 1 km horizontal resolution domain 44 4.3.1 Control run (Ctrl) 44 4.3.2 Sensitivity of precipitation 50 4.4 Modeling of Miaopu validation experiment in higher horizontal resolution domain (333 m) 53 4.4.1 Sensitivity of precipitation 53 4.4.2 Seeding effects on the microphysics properties 55 4.5 Discussion and advice for TCSRP 69 Chapter 5. Conclusion and future work 71 5.1 Conclusion 71 5.2 Future work 74 Reference 75
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指導教授	鍾高陞王聖翔(Kao-Shen Chung Sheng-Hsiang Wang)	審核日期	2022-7-14
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