A Deep Learning‐Based Approach for Modeling the Dynamics of AMPERE Birkeland Currents
Author:
Affiliation:
1. Bradley Department of Electrical and Computer Engineering Virginia Tech Blacksburg VA USA
2. The Johns Hopkins University Applied Physics Laboratory Laurel MD USA
Funder
National Science Foundation
Publisher
American Geophysical Union (AGU)
Subject
Space and Planetary Science,Geophysics
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1029/2020JA027908
Reference86 articles.
1. Development of large-scale Birkeland currents determined from the Active Magnetosphere and Planetary Electrodynamics Response Experiment
2. Statistical Birkeland current distributions from magnetic field observations by the Iridium constellation
3. Temporal and Spatial Development of Global Birkeland Currents
4. Birkeland current system key parameters derived from Iridium observations: Method and initial validation results
5. Sensing global Birkeland currents with iridium® engineering magnetometer data
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