鹿林山春季雲事件之高時間解析雲微物理觀測與分析研究

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林伯勳(Po-Hsun Lin) 查詢紙本館藏

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大氣科學學系

論文名稱

鹿林山春季雲事件之高時間解析雲微物理觀測與分析研究
(In-Situ Observations of Cloud Microphysics at Mt. Lulin during Biomass Burning Transport Events in Spring)

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至系統瀏覽論文 (2026-7-31以後開放)

摘要(中)

人為排放氣膠為雲凝結核的重要來源之一，氣膠濃度的變化透過改變雲滴的大小與數量，可以間接影響大氣輻射收支。目前世界上針對氣膠與雲交互作用的觀測資料尚顯不足，值得注意的是，低層暖雲對氣膠濃度變化特別敏感，但雲微物理特性在不同環境條件皆有著不同的表現，以至於氣膠對雲造成的衝擊與變化目前仍然充滿爭議。本研究目的為建構一套高時間解析度之氣膠-雲監測系統，包含雲滴譜儀(Cloud Droplet Probe, CDP)和光學式氣膠粒徑儀(Grimm 11-D)，於2024年3月1日至12日架設於鹿林山大氣背景站(LABS)，針對含有大量生質燃燒氣膠的暖雲進行現地觀測，並建立一套資料QC的程序，以確保觀測結果不受外在因素干擾(如：環境風速影響、鏡頭汙損)，觀測資料足以解析雲系統中的氣膠和雲微物理(如：數量濃度、有效直徑、液態水含量等)隨時序變化及依條件分類表現，以了解受到大量氣膠影響後雲系統的特徵。
資料分析結果顯示，隨著氣膠質量濃度(PM2.5)的增加雲滴數量濃度(Nd)並非呈現單調增加的趨勢；液態水含量(LWC)則是在高PM2.5負載中顯著減少，初步支持了氣膠造成雲消散的論點。本研究中使用Nd計算氣膠-雲交互作用指數(Aerosol-Cloud-Interaction Index, ACI Index)，視為氣膠轉換成雲凝結核的活化率，其特點為不需限定在相同雲液態水含量條件，得以更加廣泛的分析氣膠-雲交互作用的現象。因此分析雲系統內的氣膠與雲微物理變化時，與過去的研究不同(設定在相同LWC下，僅利用氣膠濃度的差異分析ACI)，須一併將雲水含量(如：LWC、Nd)的變因納入考量，所以本研究進一步引入LPR (log(LWC/PM2.5))與NPR (log(Nd/PM2.5))指數，代表系統中每單位的氣膠所含的雲液態水濃度。結果顯示，液態水含量相對於氣膠濃度，在充足的條件下(LPR ≥ -1.5、NPR ≥ 1.8)計算出ACI介於0.11-0.14，且ln(Nd)與ln(PM2.5)呈現高相關性，氣膠濃度增加對雲滴數量的增多顯著影響；相較之下，液態水含量缺少的條件下，特別當LPR介於-3至-1.5時，ACI趨近於0、相關係數為-0.01，說明更多的氣膠對雲滴數量增多毫無幫助。本研究首次於鹿林山針對生質燃燒氣膠影響之暖雲進行觀測實驗與分析，結果說明臺灣三月的雲系在高濃度的東南亞生質燃燒氣膠影響下，雲量的減少(LWC、N¬d下降)比Twomey效應更為顯著，且進一步利用雲系統中的液態水-氣膠濃度比例結合ACI指數分析，發現液態水含量充足與否也會影響到增加的氣膠是否會活化成雲凝結核(ACI > 0)，相較於侷限在相同雲液態水含量下分析，同時納入雲液態水含量與氣膠濃度二者變因，可以更加全面地闡述雲系統內的氣膠與雲之間的交互作用結果。

摘要(英)

Anthropogenic aerosols are an important source of cloud condensation nuclei (CCN), and high aerosol loading could indirectly affect radiation forcing (RF) by changing cloud droplet size and number concentration. At present, there is a lack of observation on aerosol-cloud interaction (ACI), especially in the case of low-level warm clouds, which are sensitive to changes in aerosol concentration. However, cloud microphysical properties are different in different environments, and the impact of aerosol on cloud is still controversial. The objective of this study is to analyze the development and changes of aerosol and cloud microphysics (i.e., number concentration, effective diameter, liquid water concentration, etc.) within warm cloud over a period of several hours, to understand the characteristics of the cloud system after being affected by a large amount of aerosol. Therefore, a high-time-resolution aerosol-cloud monitoring system was constructed and set up to observe warm clouds with high loading of biomass burning aerosols at the Lulin Atmospheric Background Station (LABS) from 1st to 12th March 2024, including Cloud Droplet Probe (CDP) and Optical Particle Counter (Grimm 11-D), and a quality control (QC) procedure was established for cloud microphysics data during the observation period to ensure that the observation results were not disturbed by external factors (e.g., ambient wind speed influence, monitor unclean).
The result shows that the cloud droplet number concentration (Nd) does not increase monotonically with the increase of the aerosol mass concentration (PM2.5), while the liquid water content (LWC) decreases significantly at high PM2.5, which initially supports that aerosol contributes to cloud dissipation. To conduct a more comprehensive analysis of the aerosol-cloud interaction phenomenon, Nd is used to calculate Aerosol-Cloud Interaction Index (ACI Index), which is regarded as the activation rate of aerosol to CCN. One of the key characteristics of ACINd index is that it does not need to be limited under the same cloud water content. Therefore, when analyzing ACI in cloud systems, it is necessary to consider not only the variations in aerosol concentration (i.e., PM2.5) but also the variations in cloud water content (i.e., LWC, Nd). Accordingly, this study introduces LPR (log(LWC/PM2.5)) and NPR (log(Nd/PM2.5)) indices, which represent the concentration of cloud liquid water in the cloud for unit of aerosol in the system. The results demonstrate that when cloud water content is sufficient in relation to PM2.5 (LPR ≥ -1.5, NPR ≥ 1.8), ACI ranges from 0.11 to 0.14 with high correlation between ln(Nd) and ln(PM2.5¬), indicating that an increase in aerosol concentration has a significant impact on the growth of cloud droplets. Conversely, when cloud water content is shortage (LPR is between -3 and -1.5), the ACI is close to 0, and the correlation coefficient is -0.01. This suggests that an increase in aerosol does not contribute to the formation of cloud droplets. This study conducted the first observation of warm cloud under the influence of biomass burning aerosol at Mt. Lulin. The finding revealed that the reduction of cloud (decrease of LWC and Nd) is more significant than Twomey effect in the March cloud system in Taiwan under high loading of biomass burning aerosol. Further analysis of cloud liquid water to aerosol concentration ratio and ACI index in the cloud system demonstrates that the sufficiency of cloud water content also affected whether the increased aerosol would be activated into CCN (ACI > 0). The present study suggests that the inclusion of both cloud water content and aerosol concentration provides a more comprehensive description of aerosol-cloud interactions in cloud systems.

關鍵字(中)

★ 氣膠與雲交互作用
★ 雲微物理

關鍵字(英)

★ Aerosol-Cloud Interaction
★ Cloud Microphysics

論文目次

摘要 i
Abstract iii
致謝 v
目錄 vi
圖目錄 viii
表目錄 xii
第一章前言 1
1-1 研究動機 1
1-2 研究目的 2
第二章文獻回顧 4
2-1 氣膠與雲與輻射效應 4
2-2 氣膠-雲交互作用指數(Aerosol-Cloud Interaction Index, ACI Index) 5
2-3 氣膠與雲微物理相關研究 6
2-4 中南半島氣膠傳輸與衝擊相關研究 9
第三章研究方法 10
3-1 觀測地點 11
3-2 氣膠-雲微物理監測系統 12
3-3-1 雲滴譜儀(Cloud Droplet Probe) 14
3-3-2 氣膠粒徑儀(11-D Optical Particle Counter) 17
3-3 HYSPLIT模式 18
3-4 氣膠系統(Aerosol System) 19
3-5 雲水資料選用 20
3-5-1 暖雲資料選取 20
3-5-2 雲微物理參數計算 22
3-5-3 CDP抽氣風管風速修正計算 24
3-6 氣膠資料選用 25
3-6-1 氣膠資料選取 25
3-6-2 氣膠參數計算 27
3-7 氣膠與雲資料分析方法 28
3-7-1 ACI指數計算 28
3-7-2 氣膠與雲水含量濃度比例關係計算 28
3-7-3 平均值標準誤差(Standard Error of the Mean) 29
第四章雲水資料修正與檢驗 32
4-1 雲滴譜儀設備風管內風速修正 33
4-2 CDP鏡頭汙損對資料影響性分析 35
第五章結果與討論 39
5-1 天氣、氣膠與雲微物理特徵分析 39
5-1-1 綜觀天氣分析 39
5-1-2 氣膠來源與光學特性分析 48
5-1-3 雲微物理特徵分析 56
5-2 氣膠濃度對雲微物理影響 60
5-2-1 不同氣膠濃度區間內雲微物理與水氣含量比較 60
5-2-2 連續雲事件內LPR、NPR與ACI關係比較 62
5-2-3 LPR、NPR區間與ACI分析 67
5-2-4 LPR區間與ACI值對天氣條件敏感度分析 72
5-3 雲液態水-氣膠比例與氣膠-雲交互作用 78
5-3-1 雲水含量充足之降水前個案分析(Case 1、Case 4) 80
5-3-2 雲水含量充足之毛雨與非降水個案分析(Case 2、Case 3) 85
5-3-3 雲水含量缺乏之個案分析(Case 5、Case 6、Case 7) 91
第六章結論與未來展望 97
6-1 結論 97
6-2 未來展望 100
第七章參考文獻 102

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指導教授

王聖翔

審核日期

2024-8-5

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