Monitoring Space Weather: Using Automated, Accurate Neural Network Based Whistler Segmentation for Whistler Inversion-Reference-Cited by-同舟云学术

Monitoring Space Weather: Using Automated, Accurate Neural Network Based Whistler Segmentation for Whistler Inversion

Published:2022-02 Issue:2 Volume:20 Page:
ISSN:1542-7390
Container-title:Space Weather
language:en
Short-container-title:Space Weather

Author:

Pataki Bálint Ármin¹^ORCID,Lichtenberger János²³^ORCID,Clilverd Mark⁴^ORCID,Máthé Gergely¹^ORCID,Steinbach Péter⁵^ORCID,Pásztor Szilárd²,Murár‐Juhász Lilla²,Koronczay Dávid²,Ferencz Orsolya²,Csabai István¹^ORCID

Affiliation:

1. Department of Physics of Complex Systems ELTE Eötvös Loránd University Budapest Hungary

2. Space Research Group Department of Geophysics and Space Sciences ELTE Eötvös Loránd University Budapest Hungary

3. Institute of Earth Physics and Space Science Sopron Hungary

4. British Antarctic Survey (UKRI‐NERC) Cambridge UK

5. ELKH‐ELTE Research Group for Geology, Geophysics and Space Sciences Budapest Hungary

Publisher

American Geophysical Union (AGU)

Subject

Atmospheric Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2021SW002981

Reference27 articles.

1. Electron scattering loss in Earth's inner magnetosphere: 1. Dominant physical processes

2. A new nose extension method for whistlers

3. An ISEE/whistler model of equatorial electron density in the magnetosphere

4. Whistler evidence of a ‘knee’ in the magnetospheric ionization density profile

5. Whistlers and VLF noises propagating just outside the plasmapause

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