Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
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Articles | Volume 23, issue 21
Articles | Volume 23, issue 21
https://doi.org/10.5194/acp-23-13973-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/acp-23-13973-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 23, issue 21
Research article
 | 
09 Nov 2023
Research article |  | 09 Nov 2023

Evaluating F2-region long-term trends using the International Reference Ionosphere (IRI) model: is this a feasible approximation for experimental trends?

Bruno S. Zossi, Trinidad Duran, Franco D. Medina, Blas F. de Haro Barbas, Yamila Melendi, and Ana G. Elias

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Cited articles

Altadill, D., Magdaleno, S., Torta, J. M., and Blanch, E.: Global empirical models of the density peak height and of the equivalent scale height for quiet conditions, Adv. Space Res., 52, 1756–1769, https://doi.org/10.1016/j.asr.2012.11.018, 2013. 
Australian Space Weather Forecasting Centre: Index of /wdc/iondata/au, [data set], https://downloads.sws.bom.gov.au/wdc/iondata/au/ (last access: 12 September 2023), 2023a. 
Australian Space Weather Forecasting Centre: Index of /wdc/iondata/medians, [data set], https://downloads.sws.bom.gov.au/wdc/iondata/medians/ (last access: 12 September 2023), 2023b. 
Bilitza, D., Pezzopane, M., Truhlik, V., Altadill, D., Reinisch, B. W., and Pignalberi, A.: The International Reference Ionosphere model: A review and description of an ionospheric benchmark, Rev. Geophys., 60, e2022RG000792, https://doi.org/10.1029/2022RG000792, 2022. 
Brown, S., Bilitza, D., and Yigit, E.: Ionosonde-based indices for improved representation of solar cycle variation in the International Reference Ionosphere model, J. Atmos. Sol.-Terr. Phy., 171, 137–146, https://doi.org/10.1016/j.jastp.2017.08.022, 2018. 
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The International Reference Ionosphere (IRI) is a widely used ionospheric empirical model based on observations from a worldwide network of ionospheric stations. It is reasonable, then, to expect that it captures long-term changes in ionospheric parameters linked to trend forcings like greenhouse gases increasing concentration and the Earth's magnetic field secular variation. We show that the IRI model can be a valuable tool for obtaining preliminary approximations of experimental trends.
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