An artificial neural network model of electron fluxes in the Earth’s central plasma sheet: a THEMIS survey

Abstract

The Earth’s central plasma sheet plays an important role in mass and energy transport in the whole magnetosphere. Here, we first present a new approach, i.e., an Artificial Neural Network (ANN) model, to investigate the electron number fluxes in the central plasma sheet. With the time series of 8 solar wind/geomagnetic indices and spatial locations as inputs, the model has been trained, validated, and tested with three isolated groups of measurements from Time History of Events and Macroscale Interaction during the Substorm (THEMIS) – A/D/E spacecraft from April 1, 2007 to December 30, 2015. The plasma sheet electron flux is shown to be accurately reproduced by the ANN model with a total correlation coefficient (R) above ∼0.91 and a root-mean-square-error (RMSE) less than 0.36 between the data and model target in a spatial region from radial distance 7 RE to 12 RE (where RE is the Earth’s radius) at the nightside of between 18 MLT through 24 MLT and up to 0.6 MLT (Magnetic Local Time) for energies at 0.06 – 293 keV. Global and spectral distributions of reproduced values can also capture the dawn-dusk asymmetry and the dependence on radial distances of plasma sheet electron fluxes. Our developed artificial neural network (ANN) therefore has a good capability in statistically reproducing the plasma sheet electron fluxes for a variety of substorm activities, and can be readily adopted for building up the boundary conditions for physics-based simulation efforts that model the dynamics of the radiation belt electrons and other parts of the terrestrial magnetosphere.

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Acknowledgements

We would also like to thank Alexander Drozdov and Adam Kellerman for useful discussions. This work was supported by the NSFC grants 4173000045, 41674163, 41474141, and the Hubei Province Natural Science Excellent Youth Foundation (2016CFA044). This research has been partially funded by Deutsche Forschungsgemeinschaft through grant CRC 1294 “Data Assimilation”, Project B06 “Novel methods for the 3D reconstruction of the dynamic evolution of the Van Allen belts using multiple satellite measurements”. The ESA and SST data are obtained from https://spdf.gsfc.nasa.gov/pub/data/themis. The data of geomagnetic indices are available from the NASA OmniWeb (http://cdaweb.gsfc.nasa.gov). The ANN models are available in https://github.com/ZhengyangZou/ANN-model-for-CPS.

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Zou, Z., Shprits, Y.Y., Ni, B. et al. An artificial neural network model of electron fluxes in the Earth’s central plasma sheet: a THEMIS survey. Astrophys Space Sci 365, 100 (2020). https://doi.org/10.1007/s10509-020-03819-0

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Keywords

  • Plasma sheet electron number fluxes
  • Artificial Neural Network model
  • Global distributions
  • Energy spectrum