A neural network-based ionospheric model for Arecibo

• Published in: Advances in space research Vol. 42; no. 4; pp. 776 - 781
• Main Authors: Friedrich, M., Fankhauser, M., Oyeyemi, E., McKinnell, L.A.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 18-08-2008; Elsevier Science
• Subjects: Arecibo; Astronomy; Earth, ocean, space; Exact sciences and technology; External geophysics; Ionosphere; IRI; Neural network; IRI; Neural network; Arecibo; Ionosphere; Solar activity; Neural networks; Incoherent scattering; Models; Electron density; Performance; Space research; Diameter
• ISSN: 0273-1177; 1879-1948
• DOI: 10.1016/j.asr.2007.07.018

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.