• Title of article

    A neural network-based ionospheric model for Arecibo Original Research Article

  • Author/Authors

    M. Friedrich، نويسنده , , M. Fankhauser، نويسنده , , E. Oyeyemi، نويسنده , , L.A. McKinnell، نويسنده ,

  • Issue Information
    دوهفته نامه با شماره پیاپی سال 2008
  • Pages
    6
  • From page
    776
  • To page
    781
  • Abstract
    The Arecibo Observatory (18°N, 66°W) has the world’s largest single dish antenna (300 m diameter). Beyond radio astronomy it can also operate as an incoherent scatter radar and in that mode its figure-of-merit makes it also one of the most powerful world-wide. For the present purpose all electron density data available on the web, from the beginning with the first erratic measurements in 1966 up to 2004 inclusive, were downloaded. The measurements range from about 100 km to beyond 700 km and are essentially evenly distributed, i.e. not dedicated to measure specific geophysical events. From manually edited/inspected data a neural network (NN) was established with season, hour of the day, solar activity and Kp as the input parameters. The performance of this model is checked against a – likewise NN based – global model of foF2, a measure of the maximum electron density of the ionosphere. Considering the diverse data sources and assumptions of the two models it can be concluded that they agree remarkably well.
  • Keywords
    IRI , Arecibo , Neural network , Ionosphere
  • Journal title
    Advances in Space Research
  • Serial Year
    2008
  • Journal title
    Advances in Space Research
  • Record number

    1132299