The existence of Birkeland magnetic field‐aligned current (FAC) system was proposed more than a century ago, and it has been of immense interest for investigating the nature of solar wind‐magnetosphere‐ionosphere coupling ever since. In this paper, we present the first application of deep learning architecture for modeling the Birkeland currents using data from the Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE). The model uses a 1‐hr time history of several different parameters such as interplanetary magnetic field (IMF), solar wind, and geomagnetic and solar indices as inputs to determine the global distribution of Birkeland currents in the Northern Hemisphere. We present a comparison between our model and bin‐averaged statistical patterns under steady IMF conditions and also when the IMF is variable. Our deep learning model shows good agreement with the bin‐averaged patterns, capturing several prominent large‐scale features such as the Regions 1 and 2 FACs, the NBZ current system, and the cusp currents along with their seasonal variations. However, when IMF and solar wind conditions are not stable, our model provides a more accurate view of the time‐dependent evolution of Birkeland currents. The reconfiguration of the FACs following an abrupt change in IMF orientation can be traced in its details. The magnitude of FACs is found to evolve with e‐folding times that vary with season and MLT. When IMF Bz turns southward after a prolonged northward orientation, NBZ currents decay exponentially with an e‐folding time of
Science Data Products for AMPERE
Birkeland currents that flow in the auroral zones produce perturbation
magnetic fields that may be detected using magnetometers onboard low-Earth orbit satellites. The Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE) uses magnetic field data from the attitude control system of each Iridium satellite. These data are processed to obtain the location, intensity and dynamics of the Birkeland currents. The methodology is based on an orthogonal basis function expansion and associated data fitting. The theory of magnetic fields and currents on spherical shells provides the mathematical basis for generating the AMPERE science data products. The application of spherical cap harmonic basis and elementary current system methods to the Iridium data are discussed and the procedures for generating the AMPERE science data products are described.
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- Award ID(s):
- 2002574
- NSF-PAR ID:
- 10237581
- Editor(s):
- Dunlop, M.; Lühr, H.
- Date Published:
- Journal Name:
- Ionospheric Multi-Spacecraft Analysis Tools, ISSI Scientific Report Series
- Volume:
- 17
- Page Range / eLocation ID:
- 141 – 165
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract ∼ 25 min, whereas Region 1 currents grow with an e‐folding time of 6–20 min depending on the MLT. -
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1007/978-3-030-26732-2_7
