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- Title
Evaluating F2 region long term trends using the IRI model: A feasible approximation for experimental trends?
- Authors
Zossi, Bruno S.; Duran, Trinidad; Medina, Franco D.; de Haro Barbas, Blas F.; Melendi, Yamila; Elias, Ana G.
- Abstract
The International Reference Ionosphere (IRI) is a widely used empirical model of the ionosphere based on observations from a worldwide network of ionospheric stations. Therefore, it is reasonable to expect that it captures long-term changes in key ionospheric parameters, such as foF2 and hmF2 linked to trend forcings like greenhouse gases increasing concentration and the Earth's magnetic field secular variation. Despite the numerous reported trends in foF2 and hmF2 derived from experimental data and model results, there are persistent inconsistencies that require continuous refinement of trend estimation methods and regular data updates. This ongoing effort is crucial to address the inherent challenges posed by the weak signal-to-noise ratio associated with studying long-term trends in the ionosphere. Furthermore, the experimental verification of these trends remains challenging, primarily due to time and spatial coverage limitations of measured data series. Achieving these needs for long-term trend accurate detection requires extensive global coverage and resolution of ionospheric measurements together with long enough periods spanning multiple solar cycles to properly filter out variations of shorter term than the sought trend. Considering these challenges, IRI-modeled foF2 and hmF2 parameters offer a valuable alternative for assessing trends and obtaining a first approximation of a plausible global picture representative of experimental trends. This work presents these global trend patterns considering the period 1960-2022 using the IRI-Plas 2020 version, which are consistent with other model predictions. A verification was performed for foF2 trends, considering data from 9 mid-latitude stations, and a reasonable level of agreement was observed. It is concluded that IRI model can be a valuable tool for obtaining preliminary approximations of experimental trends.
- Subjects
IONOSPHERIC techniques; GEOMAGNETISM; IONOSPHERE; SIGNAL-to-noise ratio; GREENHOUSE gases
- Publication
Atmospheric Chemistry & Physics Discussions, 2023, p1
- ISSN
1680-7367
- Publication type
Article
- DOI
10.5194/egusphere-2023-1335