The Study on the Global Evolution of Energetic Electron Precipitation During Geomagnetic Storm Based on Deep Learning Algorithm

Author:

Chen Zhou12,Tian Hang12,Li Haimeng12ORCID,Tang Rongxin12ORCID,Ouyang Zhihai12,Deng Xiaohua12

Affiliation:

1. Information Engineering School Nanchang University Nanchang China

2. Institute of Space Science and Technology Nanchang University Nanchang China

Abstract

AbstractThe energetic electron precipitation (EEP) plays important role in the magnetosphere‐ionosphere‐thermosphere system. It can lead to the decrease of ring current energy densities, the enhancement of electron density in the lower ionosphere, and the destruction of the ozone layer. In the study, using the Energetic Electron Precipitation flux Deep Neural Networks (EPFN) model, the global dynamic evolution of EEP is reconstructed. It suggests that the model can better capture the variation of global EEP during geomagnetic activity. With that, the morphological evolution of EEP and associated potential mechanisms during different phases of geomagnetic storm are analyzed based on the EPFN model. The model provides a good way to understand the loss processes of ring current electrons during geomagnetic storm.

Publisher

American Geophysical Union (AGU)

Subject

Space and Planetary Science,Geophysics

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