PyIRI: Whole-Globe Approach to the International Reference Ionosphere Modeling Implemented in Python

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 useable ionospheric frequency foF2 and the propagation factor M(3,000)F2. At the U.S. Naval Research Laboratory, 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. The International Reference Ionosphere (IRI) estimates the number of electrons in the upper atmosphere, which is important to know for the ground- and space-based communication and investigation. Scientists and communication specialists often use IRI to plan future and ongoing operations. The core software of the IRI model was written in the late 1960s, when arrays and matrices were not practical to implement given computational limitations. This means that IRI evaluates the electron density at each geographic location and desired time separately. This causes a long processing time for high-resolution, global IRI runs, even with modern computers. We have introduced modern programming approaches to the IRI code by building a Python tool, PyIRI, that enables estimation of the electron density at all desired geographic locations and for the duration of the whole day in one computational operation. With PyIRI, it takes just a few seconds to obtain the electron density for a day over the entire globe. Python tool for rapid global ionospheric electron density estimates Novel approach to running the core of the International Reference Ionosphere model 24-hr global electron density in a few seconds