09:00 〜 09:20
[PEM19-01] Quantifying Energetic Electron Precipitation Driven by Various Types of Whistler-mode Waves
★Invited Papers
*Wen Li1, Qianli Ma1, Longzhi Gan1, Abhinav Prasad1, Luisa Capannolo1, Yukitoshi Nishimura1 (1. Boston University)
[E] 口頭発表
セッション記号 P (宇宙惑星科学) » P-EM 太陽地球系科学・宇宙電磁気学・宇宙環境
2026年5月29日(金) 09:00 〜 10:30 304 (幕張メッセ国際会議場)
座長:新堀 淳樹(名古屋大学宇宙地球環境研究所)
The inner magnetosphere is a highly dynamic and variable region filled with cold plasma, energetic particles, and wave activities, which is primarily influenced by changes in energy input from the solar wind, the plasma supply from the ionosphere, and electrodynamic magnetosphere-ionosphere coupling. This complex and dynamically coupled plasma-neutral system is shaped by various processes that interconnect different regions, scales, and energy domains of the geospace environment. To achieve a comprehensive understanding of this dynamic environment, it is crucial to conduct integrated studies utilizing coordinated observations from multi-point satellite measurements, ground-based networks, and theoretical modeling. During the 24th and 25th solar cycles, advancements in this area have been facilitated by multiple satellite missions (including Arase, the Van Allen Probes, MMS, THEMIS, DSX, and CubeSats), as well as coordinated ground-based observations (such as PWING, THEMIS-GBO, SuperDARN, EISCAT, magnetometers, and riometers) and numerical simulations (encompassing global kinetic models, MHD models, PIC, hybrid models, and particle tracing simulations).
This session invites submissions of papers highlighting recent research findings related to the inner magnetosphere and its interactions with adjacent regions, including the ionosphere and the outer magnetosphere. We welcome relevant data analysis and contributions from various models and simulations. The results of recent severe storm events, such as those in May and October 2024, are also highly welcome. We encourage papers that discuss new projects, such as sounding rocket experiments, data assimilation and machine learning approaches, and CubeSat projects, as well as insights into future spacecraft missions.
09:00 〜 09:20
*Wen Li1, Qianli Ma1, Longzhi Gan1, Abhinav Prasad1, Luisa Capannolo1, Yukitoshi Nishimura1 (1. Boston University)
09:20 〜 09:40
*Weichao Tu1, Zhi Gu Li1 (1. University of Michigan Ann Arbor)
09:40 〜 10:00
*Robyn M Millan1, Wen Li2, Thomas Sotirelis4, John Sample3, Eric Engel3, Luisa Capannolo2, Qianli Ma2, Longzhi Gan2, Sasha Ukhorskiy4, Jingxuan Li1 (1. Dartmouth College, 2. Boston University, 3. Montana State University, 4. Johns Hopkins Applied Physics Lab)
10:00 〜 10:15
*Kaine Bunting1, Nigel Meredith1, Jacob Bortnik2, Qianli Ma2,3, Ryoma Matsuura2, Xiao-Chen Shen3 (1. British Antarctic Survey, 2. University of California, Los Angeles, 3. Boston University)
10:15 〜 10:30
*三好 由純1、栗田 怜2、新堀 淳樹1、山本 和弘1、Jun Chae-Woo1、松田 昇也3、齊藤 慎司4、片岡 龍峰5、ワン デドン6、篠原 育7、高島 健7、三谷 烈史7、東尾 奈々7、松岡 彩子2、笠原 禎也3、土屋 史紀8、熊本 篤志8、堀 智昭1、寺本 万里子9、北村 成寿1 (1. 名古屋大学宇宙地球環境研究所、2. 京都大学、3. 金沢大学、4. 情報通信研究機構、5. OIST、6. GFZ Potsdam、7. 宇宙航空研究開発機構、8. 東北大学、9. 九州工業大学)
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