A storm-time ring current model(STRIM)
作者机构：School of Space and Earth Sciences Beihang University Key Laboratory of Space Environment Monitoring and Information Processing Ministry of Industry and Information Technology
出 版 物：《Science China Technological Sciences》 (中国科学:技术科学(英文版))
年 卷 期：2024年第67卷第12期
页 面：3890-3908页
核心收录：
学科分类：070802[理学-空间物理学] 07[理学] 0708[理学-地球物理学]
基 金：supported by the National Natural Science Foundation of China (Grant Nos. 41821003 and 41974192) the Fundamental Research Funds for the Central Universities
主 题：kinetic ring current models bounce-averaged Fokker-Planck equation Earth inner magnetosphere ring current dynamics magnetic storms
摘 要：The ring current, one of the most important current systems around the Earth, intensifies during geomagnetic storms and is believed to be the main reason for large-scale magnetic field perturbations in the geospace environment. Understanding how the ring current builds up and evolves during geomagnetic storms is of great importance not only for advancing the knowledge of the Sun-Earth system but also for improving the modeling capability of predicting hazardous space weather events. Focusing on the national strategic needs in the space weather prediction, in this study, we establish a ring current model named storm time ring current model(STRIM). The STRIM comprehensively embraces key physical processes in association with ring current dynamics,including plasma source injections from the nightside plasmasheet and transport around the Earth, charge-exchange with neutral hydrogens, Coulomb collisions with thermal plasma, wave-particle interactions, field line curvature scattering, and precipitation loss down to the upper atmosphere. The electric fields needed for particle motion can be optionally taken from empirical models or self-consistently calculated, while the magnetic field configuration is obtained from Tsyganenko 2005 model. Simulation results are verified against the published literature and validated with in-situ satellite or ground-based observations and are found to have the same high-level capability and fidelity as other well-known published models. We also discuss future tasks of fostering the model s performance and potential applications.
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