Data‐Driven Modeling of Atomic Oxygen Airglow over a Period of Three Solar Cycles-Reference-Cited by-同舟云学术

Data‐Driven Modeling of Atomic Oxygen Airglow over a Period of Three Solar Cycles

Published:2021-03 Issue:3 Volume:126 Page:
ISSN:2169-9380
Container-title:Journal of Geophysical Research: Space Physics
language:en
Short-container-title:JGR Space Physics

Author:

Mackovjak Š.¹²^ORCID,Varga M.³^ORCID,Hrivňak S.²,Palkoci O.²,Didebulidze G. G.⁴^ORCID

Affiliation:

1. Department of Space Physics Institute of Experimental Physics Slovak Academy of Sciences Košice Slovakia

2. GlobalLogic Slovakia s.r.o. Košice Slovakia

3. Department of Cybernetics and Artificial Intelligence Faculty of Electrical Engineering and Informatics Technical University of Košice Košice Slovakia

4. Georgian National Astrophysical Observatory Ilia State University Tbilisi Georgia

Funder

European Space Agency

Vedecká Grantová Agentúra MŠVVaŠ SR a SAV

Shota Rustaveli National Science Foundation

Publisher

American Geophysical Union (AGU)

Subject

Space and Planetary Science,Geophysics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2020JA028991

Reference56 articles.

1. Performance and science reach of the Probe of Extreme Multimessenger Astrophysics for ultrahigh-energy particles

2. Study of atomic oxygen greenline dayglow emission in thermosphere during geomagnetic storm conditions

3. DATA MINING AND MACHINE LEARNING IN ASTRONOMY

4. International Reference Ionosphere 2016: From ionospheric climate to real‐time weather predictions

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