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PyIRI: Whole-Globe Approach to the International Reference Ionosphere Modeling Implemented in Python
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  • Victoriya Forsythe,
  • Dieter Bilitza,
  • Angeline Gail Burrell,
  • Kenneth F. Dymond,
  • Bruce Aaron Fritz,
  • Sarah E McDonald
Victoriya Forsythe
U.S. Naval Research Laboratory

Corresponding Author:[email protected]

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Dieter Bilitza
George Mason University
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Angeline Gail Burrell
US Naval Research Laboratory
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Kenneth F. Dymond
Naval Research Laboratory
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Bruce Aaron Fritz
U.S. Naval Research Laboratory
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Sarah E McDonald
Naval Research Laboratory
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Abstract

The International Reference Ionosphere (IRI) model is widely used in the ionospheric community and considered the gold standard for empirical ionospheric models. The development of this model was initiated in the late 1960s using the FORTRAN language; for its programming approach, the model outputs were calculated separately for each given geographic location and time stamp. The Consultative Committee on International Radio (CCIR) and International Union of Radio Science (URSI) coefficients provide the skeleton of the IRI model, as they define the global distribution of the maximum usable ionospheric frequency foF2 and the propagation factor M(3000)F2. At the U.S. Naval Research Laboratory (NRL), a novel Python tool was developed that enables global runs of the IRI model with significantly lower computational overhead. This was made possible through the Python rebuild of the core IRI component (which calculates ionospheric critical frequency using the CCIR or URSI coefficients), taking advantage of NumPy matrix multiplication instead of using cyclic addition. This paper explains in detail this new approach and introduces all components of the PyIRI package.
28 Sep 2023Submitted to ESS Open Archive
28 Sep 2023Published in ESS Open Archive