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  Automated determination of electron density from electric field measurements on the Van Allen Probes spacecraft

Zhelavskaya, I., Spasojevic, M., Shprits, Y., Kurth, W. S. (2016): Automated determination of electron density from electric field measurements on the Van Allen Probes spacecraft. - Journal of Geophysical Research, 121, 5, 4611-4625.
https://doi.org/10.1002/2015JA022132

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https://doi.org/10.5880/GFZ.2.8.2020.002 (Ergänzendes Material)
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Supplemented by Zhelavskaya, I. et al. (2020)

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Zhelavskaya, I.1, Autor              
Spasojevic, M.2, Autor
Shprits, Yuri3, Autor              
Kurth, W. S.2, Autor
2.8 Magnetospheric Physics, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum, Autor              
Affiliations:
10 Pre-GFZ, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum, ou_146023              
2External Organizations, ou_persistent22              
32.3 Earth's Magnetic Field, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum, ou_146030              

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 Zusammenfassung: We present the Neural-network-based Upper hybrid Resonance Determination (NURD) algorithm for automatic inference of the electron number density from plasma wave measurements made on board NASA's Van Allen Probes mission. A feedforward neural network is developed to determine the upper hybrid resonance frequency, fuhr, from electric field measurements, which is then used to calculate the electron number density. In previous missions, the plasma resonance bands were manually identified, and there have been few attempts to do robust, routine automated detections. We describe the design and implementation of the algorithm and perform an initial analysis of the resulting electron number density distribution obtained by applying NURD to 2.5 years of data collected with the Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) instrumentation suite of the Van Allen Probes mission. Densities obtained by NURD are compared to those obtained by another recently developed automated technique and also to an existing empirical plasmasphere and trough density model.

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Sprache(n): eng - Englisch
 Datum: 2016
 Publikationsstatus: Final veröffentlicht
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 Identifikatoren: DOI: 10.1002/2015JA022132
GFZPOF: p3 PT1 Global Processes
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Titel: Journal of Geophysical Research
Genre der Quelle: Zeitschrift, SCI, Scopus
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Seiten: - Band / Heft: 121 (5) Artikelnummer: - Start- / Endseite: 4611 - 4625 Identifikator: CoNE: https://gfzpublic.gfz-potsdam.de/cone/journals/resource/journals268