Geo.X - Empirical modeling of the plasmasphere dynamics using neural networks
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Plasmasphere is a torus of cold dense plasma surrounding the Earth and is a very dynamic region; its shape and size are highly susceptible to solar and geomagnetic conditions. Having an accurate model of the plasmasphere is crucial for predicting hazardous events in the near-Earth space environment which can have effect on humans and technology in space and adverse effects on the ground. The distribution of cold plasma particles in the plasmasphere, however, remains poorly quantified, and existing empirical models of plasma density tend to be oversimplified.
The goal of this project is to develop a more quantitatively accurate model of plasma density in the plasmasphere and to quantify its dynamic dependence on solar wind and geomagnetic conditions. We employ neural network-based empirical modeling and train the networks on a large volume of current and historic data from NASA’s Van Allen Probes, THEMIS, MMS missions; the neural networks undergo an extensive process of validation and testing, and the model predicted global evolution is validated by performing comparisons to global images from NASA’s IMAGE mission.
Laufzeit
2015-2017
Zuwendungsgeber
Geo.X PhD fellowship
GFZ - Helmholtz Centre Potsdam - GFZ German Research Centre for Geosciences
Projektverantwortliche
Prof. Dr Y. Shprits (GFZ, Section 2. 7 Space Physics and Space Weather; University of Potsdam, Institute of Physics and Astronomy)
Dr. M. Spasojevic (Stanford University)
ProjektmitarbeiterInnen
Irina Zhelavskaya (GFZ Potsdam, University of Potsdam)
Projektwebseite
ftp://rbm.epss.ucla.edu/ftpdisk1/PINE
Kooperationen
University of Potsdam
Stanford University, CA, USA
Methoden und Geräte
Feedforward neural networks; Internal GFZ computing servers.
Publikationen/Ergebnisse
Zhelavskaya I. S., Y. Y. Shprits, and M. Spasojevic (2017), Empirical modeling of the plasmasphere dynamics using neural networks, J. Geophys. Res., 122, doi:10.1002/2017JA024406.
Zhelavskaya, I. S., M. Spasojevic, Y. Y. Shprits, and W. S. Kurth (2016), Automated determination of electron density from electric field measurements on the Van Allen Probes spacecraft, J. Geophys. Res. Space Physics, 121, 4611–4625, doi:10.1002/2015JA022132.