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研究生: 李杰霖
Li, Jie-Lin
論文名稱: 磁暴期間大氣密度擾動影響低軌衛星軌道
The Impact of Atmosphere Density Disturbances on Low Earth Orbit Satellites Orbits During Geomagnetic Storms
指導教授: 林建宏
Lin, Chien-Hung
學位類別: 碩士
Master
系所名稱: 理學院 - 地球科學系
Department of Earth Sciences
論文出版年: 2024
畢業學年度: 112
語文別: 中文
論文頁數: 107
中文關鍵詞: 大氣密度軌道模擬磁暴
外文關鍵詞: Atmospheric density, Orbital simulation, Geomagnetic storms
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  • 太陽活動週期的變化自 2020 年後進入第 25 週期,而 2023 年後是太陽較活躍的時刻並預計在 2024 年夏天達高峰,閃焰、日冕巨量噴發等現象將變得更頻繁,太陽活躍的同時代表地球發生磁暴事件的頻率會顯著增加。隨著近年低軌道衛星數量遽增,磁暴事件對衛星造成的影響更顯重要。於 2022 年 1 月時太陽爆發了一系列的日冕巨量噴發(Corona mass ejection)導致地球發生輕度磁暴,當時 SpaceX 發射了 49 顆Starlink 低軌衛星,在這場磁暴事件中有 38 顆墜落至大氣層中,而造成墜落的原因正是大氣密度的增強使得衛星阻力增加並高度下降,此外衛星任務操作所使用的密度模型未能充分顯示出真實的大氣密度變化,以致無法降低磁暴所引發的災損。對於熱氣層的中性大氣密度量測只有少數特定的衛星可執行,因此對於該區域的大氣變化目前仍未有足夠的理解。本研究為了瞭解磁暴時的大氣密度變化,透過三種不同的熱氣層模型(NRLMSISE、TIEGCM、WACCMX)分別對 2023 年的不同磁暴事件進行模擬,並藉由福衛七號具備在軌精密軌道資料之優勢,利用 HPOP(High Precision Orbit Propagator)軌道力學模型計算福衛七號(COSMIC-2 / FORMOSAT-7)的軌道變化與磁暴產生熱氣層之關聯性分析。為了解決大氣阻力中彈道係數不確定之因素導致軌道精確度下降,採用兩行軌道要素(Two-line element set)推估彈道係數的方法求出結合不同大氣模型之係數。根據結果發現擬合出的彈道係數於各大氣模型中皆有助於提升軌道預測的準確度,此外透過分析的磁暴事件發現,具有較長時長的磁暴事件對軌道高度下降的影響大於短時間密度急遽變化的磁暴,最後根據各大氣模型的密度分布結果顯示,磁暴時於夜側地區的大氣密度增加量是高於日側地區的,但仍以日側的熱氣層大氣密度具有最大值。

    The solar activity has entered its 25th cycle since 2020. After 2023, it marks a period of intensified solar activity and is projected to reach its maximum at Summer 2024, during which, phenomena such as solar flares and coronal mass ejections (CMEs) is expected to become more frequently occurred. Increased solar activity might trigger a significant rise in the geomagnetic storm events on Earth. With the rapid increase in low Earth orbit satellites nowadays, the impact of geomagnetic storms on satellites has become increasingly important. In January 2022, a series of CMEs led to a minor geomagnetic storm on Earth. At that time, SpaceX launched forty nine Starlink low Earth orbit satellites, of which thirty eight re-entered the atmosphere due to the increased atmospheric density driven by the geomagnetic storm, causing increased satellite drag and lowered the altitudes of the satellites.
    This study aims to better understand atmospheric density variations during geomagnetic storms by simulating geomagnetic storm events occurred in 2023 by using thermospheric models, NRLMSISE, NCAR TIEGCM and, WACCMX. It also takes advantage that FORMOSAT-7/COSMIC-2 (F7/C2) has the precise orbit determination (POD) that provides the updated accurate satellite positions for validation. The HPOP (High Precision Orbit Propagator) is then applied to calculate the orbital changes of the F7/C2 satellites. To address the issue of decreased orbital accuracy caused by the uncertainty in the drag coefficient, the two-line element set method is applied to estimate the ballistic coefficient in combination with the various thermospheric models. The results indicate that the fitted ballistic coefficients enhance the accuracy of orbit predictions. Additionally, analysis of geomagnetic storm events reveals that long-duration storms have a more significant impact on orbital altitude decrease compared to storms with rapid but short-lived density changes. Finally, density distribution resulting from various thermospgeric models show that the increase in atmospheric density on the nightside during geomagnetic storms is higher than on the dayside, though the maximum density is still observed on the dayside.

    摘要 I 英文延伸摘要 II 誌謝 VIII 目錄 IX 表目錄 XI 圖目錄 XIII 第一章 緒論 1 1.1 低軌道衛星 1 1.2 磁暴與熱氣層簡介 3 1.3 研究動機 5 1.4 文獻回顧 6 第二章 分析衛星軌道方法 11 2.1 衛星軌道簡介 11 2.2 軌道力學模型 14 2.2.1 軌道各式擾動源 16 2.2.2 大氣阻力 18 2.2.3 推估彈道係數 19 2.2.4 數值求解方法 21 2.3 大氣模型 23 2.3.1 海軍研究實驗室質譜儀不相干散射擴展模型(NRLMSISE) 24 2.3.2 熱層電離層電動力學大氣環流模型(TIEGCM) 25 2.3.3 全大氣社區氣候及其熱層和電離層擴展模型(WACCM-X) 26 第三章 研究結果與討論 27 3.1 研究流程設計 27 3.2 概述2023年磁暴事件 29 3.2.1 2023/02/27 磁暴事件 29 3.2.2 2023/03/24 磁暴事件 31 3.2.3 2023/04/23 磁暴事件 32 3.3 概述2003/10/29極端磁暴 33 3.4 地磁擾動寧靜期 35 3.4.1 大氣密度沿軌道變化及軌道高度分析 36 3.4.2 軌道預測準確性(模擬磁暴期間擬合彈道係數) 41 3.4.3 軌道預測準確性(模擬磁暴前擬合彈道係數) 44 3.5 磁暴事件模擬結果 46 3.5.1 全球中性密度分布 46 3.5.2 大氣密度沿軌道變化及軌道高度分析 60 3.5.3 軌道預測準確性(磁暴期間擬合彈道係數) 69 3.5.4 軌道預測準確性(磁暴前擬合彈道係數) 78 第四章 結論 83 參考文獻 85

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