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Complete Global Total Electron Content Map Dataset based on a Video Imputation Algorithm VISTA.

Hu Sun1, Yang Chen1, Shasha Zou2

  • 1Department of Statistics, University of Michigan, Ann Arbor, MI, 48104, USA.

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This study introduces VISTA, a novel algorithm to fill gaps in global ionospheric total electron content (TEC) maps. The enhanced maps reveal detailed structures, improving space weather research.

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Area of Science:

  • Space Physics
  • Geophysics
  • Atmospheric Science

Background:

  • Global Navigation Satellite System (GNSS) signals provide crucial data for ionospheric total electron content (TEC) research.
  • Existing global TEC maps have limitations, including data gaps over oceans and loss of meso-scale structures due to traditional algorithms.

Purpose of the Study:

  • To develop and release a complete global TEC map database using a novel imputation algorithm.
  • To address data gaps and preserve meso-scale ionospheric structures in TEC maps.

Main Methods:

  • Utilized the Madrigal TEC database as a foundation.
  • Developed and applied a novel video imputation algorithm named VISTA (Video Imputation with SoftImpute, Temporal smoothing and Auxiliary data).
  • Introduced the algorithm's pipeline, computational costs, and fine-tuning strategies.

Main Results:

  • Generated complete global TEC maps that reveal significant large-scale TEC structures.
  • Successfully preserved observed meso-scale ionospheric structures within the completed maps.
  • Demonstrated potential applications of the enhanced TEC database.

Conclusions:

  • The VISTA algorithm effectively overcomes limitations of traditional methods for global TEC mapping.
  • The complete TEC database offers improved data for space weather and ionospheric research.
  • The methodology provides a valuable tool for analyzing ionospheric dynamics.