大氣電學是研究地表以上、大氣層到電離層底部中發生的各種電學現象及其生成和相互作用的物理過程。地表與電離層底部之間的300kV電壓差驅使了電荷在其中流動並構成了電循環，這循環可以由歐姆定律所模擬的大域電路(global electrical circuit, GEC)來做解釋，其中包含了三個主要參數：大氣電場(atmospheric electric field)、大氣電流(atmospheric current)以及大氣導電率(atmospheric conductivity)。其中，地表的大氣電場量測可以做為閃電危害的預警之用，而至今也已經被大量應用於生活中以增加戶外活動的安全性並為企業降低設備損害及營運風險，如航空產業，太空產業。除此之外，近年來的研究顯示地震發生前後之地表電場的變化可能是研究地震前兆的一種有效的方式，這也成為一個新興的重要探索課題。
本工作中自主開了一套具有高時間解析度、高精準度、高度靈敏以及量測範圍可調整的電場量測儀器(electric field mill, EFM)，並於觀測區域中架設多個觀測站點以建構地表電場監控網絡。同時，為降低人為活動以及周遭環境對於地表電場觀測的擾動，站點的架設位置通常會選擇在較為空曠且無人之區域，因此每個EFM測站都具有獨立的電力系統以及無線網路傳輸系統，並透過處理器進行次系統整合、資料處理以及系統排成，以達成遠端獨立觀測之目的。有別於過去只依靠單一測站觀測，透過多個站點對於單一電場擾動事件進行觀測可以從不同的時間以及空間對於事件做全方位的分析，此作法可以有效提升電場資料的可信度以及可用度。
現階段的觀測網絡由架設於台南市區的三個站點所組成(成功大學、東區、新化區)，每個站點相距約為10km，而其中兩個站點位於地震帶上方(後甲里斷層、新化斷層)以就近觀測地震活動對於地表電場的影響。該觀測網路於2021年初觀測至2022年底，累積觀測了超過800天的電場晝夜變化。於天氣晴朗下的地表電場觀測結果指出，小區域的電場觀測與全球的電場晝夜變化(Carnegie Curve)不具備相同趨勢，而是由當地因素(如氣候、空氣汙染、環境)主導小區域電場的變化，其中又以與日照強度及PM2.5等因子展現出較強的正關聯性。此外，在伴隨降雨的擾動電場觀測事件中，透過地表電場波形的分析並對應過去研究所歸納出的分類，可以發現本研究中觀測到的單胞雷雨雲擾動事件達90%發生於雷雨雲系統發展的成熟期與消散期，這與過去研究指出的雲對地放電傾向的發生階段相符。
緊接著，透過本工作中多站觀測的優勢，藉由三個站點對於單胞雷雨雲擾動過程中的相對時間及空間資訊，來還原出雲層內部的電荷分佈結構。此演算法成功分析出於系統運作期間內觀測到的數個具有較顯著電場波形變化的單胞雷雨雲電荷結構，並還原出雷雨雲經過測站上方對於地表電場的擾動情形，且還原出的電場模式相似度皆高過85%。相較於過去要探索雲層內部電荷結構僅能仰賴困難且危險的現地量測才能執行，此方式僅需多個地表觀測站的電場資料就能重新建構出完整的雲內電荷結構，對於閃電預警的精準度和實用度的提升是一項重要的技術性突破。
由於觀測網絡處於地震發生頻繁的台灣，本工作也篩選出於運作期間經歷的10個具有不同特性的地震以進行地震前兆之分析。在M=3.1地震事件中，位於震央上方的測站觀測到在地震前3.5天電場相較於其他測站約有0.5倍標準差的負偏差，並在地震發生後回升至相同水平。這一結果與目前最廣為接受的結論一致，即岩石擠壓導致地表氡(radon)濃度增加，進而使地表導電率增加以及電場減弱。然而，另一個台灣近10年來最大的M=6.8強震中卻沒有觀測到上述的現象，取而代之的則是在地震後明顯的正突波，並在數小時後消失。這些結果或許能指出，相較於地震強度，距離震央的距離才是能否觀測到地震前兆的主要因素。

The concept of a global atmospheric electrical circuit explains the generation and variation of the atmospheric electric field (hereafter E-field), which exists under all meteorological conditions and drives the charge flow around the Earth worldwide. Thus far, many natural phenomena have been observed accompanied by surface E-field disturbances, such as lightning, thunderstorms, and even earthquakes; therefore, E-field observations are also widely used in disaster warnings. This work is dedicated to establishing a dense surface E-field monitoring network through accurate and stand-alone observation stations and expanding the application of E-field observation in disaster warning through data analysis.
This work presents a self-developed electric field mill (hereafter EFM) for atmospheric electric field measurements on the Earth’s surface, and the characteristics of high speed, high precision, sensitivity, and adjustable measurement range make EFM suitable for various observation requirements. Furthermore, the instrument was upgraded to a stand-alone operating E-field observation station by adding mechanical structure and subsystems (e.g., renewable energy system, 4G wireless transmitter, processor board, and weather sensor). Since 2021, Tainan City has successfully set up three E-field observation stations and recorded more than 800 days of E-field data. Each station was functionally tested with an in-lab E-field calibrator before setup, and outdoor calibrations are performed regularly during the system operation to maintain the accuracy of measurements.
The observation data could be divided into fair-weather E-field and disturbed E-field accompanied by precipitation through the automatic data pipeline. The analysis results indicated that the small-area E-field variation did not follow the Carnegie curve because local effects (aerosols, weather conditions, and environment) masked the variations of the global electrical circuit. In addition, the analysis of the disturbed E-field showed that more than 90% of the single-cell thunderstorms observed in the surface E-field could be classified as mature and dissipating stages. Each disturbance lasted approximately 34 minutes and was accompanied by an average of 1.4 times E-field phase reversals. Among them, the negative reversal of the surface electric field caused by the negative charge layer was relatively strong and frequent. Eventually, triangulation was used to reconstruct the charge structure of four distinctive single-cell thunderstorm events and restore the surface E-field responses during the passage of clouds. The correlation coefficients between the simulation and the observation were higher than 85%, and the trajectory and speed of the thunderclouds could be successfully reproduced. Furthermore, some preliminary conclusions about earthquake precursors were drawn by analyzing the surface E-field.

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