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Local Mapping of Polar Ionospheric Electrodynamics
  • +6
  • Karl Laundal,
  • Jone Peter Reistad,
  • Hatch Spencer Mark,
  • Michael Madelaire,
  • Simon James Walker,
  • Amalie Øie Hovland,
  • Anders Ohma,
  • Merkin Viacheslav G.,
  • Kareem Sorathia
Karl Laundal
University in Bergen

Corresponding Author:[email protected]

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Jone Peter Reistad
Birkeland Centre for Space Science, University of Bergen
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Hatch Spencer Mark
Birkeland Centre for Space Science
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Michael Madelaire
Birkeland Centre for Space Science, University of Bergen
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Simon James Walker
University in Bergen
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Amalie Øie Hovland
University of Bergen
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Anders Ohma
Birkeland Centre for Space Science, Department of Physics and Technology, University of Bergen
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Merkin Viacheslav G.
The Johns Hopkins University Applied Physics Laboratory
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Kareem Sorathia
The Johns Hopkins University Applied Physics Laboratory
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Abstract

An accurate description of the state of the ionosphere is crucial for understanding the physics of Earth’s coupling to space, including many potentially hazardous space weather phenomena. To support this effort, ground networks of magnetometer stations, optical instruments, and radars have been deployed. However, the spatial coverage of such networks is naturally restricted by the distribution of land mass and access to necessary infrastructure. We present a new technique for local mapping of polar ionospheric electrodynamics, for use in regions with high data density, such as Fennoscandia and North America. The technique is based on spherical elementary current systems (SECS), which were originally developed to map ionospheric currents. We expand their use by linking magnetic field perturbations in space and on ground, convection measurements from space and ground, and conductance measurements, via the ionospheric Ohm’s law. The result is a technique that is similar to the Assimilative Mapping of Ionospheric Electrodynamics (AMIE) technique, but tailored for regional analyses of arbitrary spatial extent and resolution. We demonstrate our technique on synthetic data, and with real data from three different regions. We also discuss limitations of the technique, and potential areas for improvement.