Validation of IRI-2020 and NeQuick2 ionospheric models using ground-based ionosonde measurements in the Ethiopian sector

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Abstract Research on ionospheric models are interesting because they have wide applications in predicting electron density profiles. The main objective of this article is to investigate the performance of the NeQuick2 and IRI-2020 empirical models. Using the electron density and its corresponding height values, we plotted and tabulated the ionosonde electron density profiles with those of the models using Matlab. From these graphs and tables, we have illustrated the performance of the ionospheric models and their correlation with that of the Ionosonde.Both models typically underestimate electron density compared to ionosonde measurements, particularly during certain periods and events, such as the geomagnetic storm. Despite these discrepancies, the NeQuick2 model shows better correlation with ionosonde data, having smaller RMSD values and thus slightly better predictive performance overall. Although the IRI-2020 model often underestimates electron density, it aligns well during specific days and times. Model performance variability is due to factors like the equatorial ionization anomaly and limited input data, especially in regions like Ethiopia. Improving local ionospheric data integration could enhance model accuracy for equatorial regions. While both models have limitations, the NeQuick2 model generally performs better.
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Validation of IRI-2020 and NeQuick2 ionospheric models using ground-based ionosonde measurements in the Ethiopian sector | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Validation of IRI-2020 and NeQuick2 ionospheric models using ground-based ionosonde measurements in the Ethiopian sector Mequanent Abebaw, Nibret Getie, Kindnew Ashagrie This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9378513/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Research on ionospheric models are interesting because they have wide applications in predicting electron density profiles. The main objective of this article is to investigate the performance of the NeQuick2 and IRI-2020 empirical models. Using the electron density and its corresponding height values, we plotted and tabulated the ionosonde electron density profiles with those of the models using Matlab. From these graphs and tables, we have illustrated the performance of the ionospheric models and their correlation with that of the Ionosonde.Both models typically underestimate electron density compared to ionosonde measurements, particularly during certain periods and events, such as the geomagnetic storm. Despite these discrepancies, the NeQuick2 model shows better correlation with ionosonde data, having smaller RMSD values and thus slightly better predictive performance overall. Although the IRI-2020 model often underestimates electron density, it aligns well during specific days and times. Model performance variability is due to factors like the equatorial ionization anomaly and limited input data, especially in regions like Ethiopia. Improving local ionospheric data integration could enhance model accuracy for equatorial regions. While both models have limitations, the NeQuick2 model generally performs better. Physical sciences/Physics Earth and environmental sciences/Space physics NeQuick2 model IRI -2020 model Ionosonde Electron Density ionogram NmF2 values Full Text Additional Declarations No competing interests reported. Supplementary Files refsV.bib Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 09 May, 2026 Reviewers agreed at journal 27 Apr, 2026 Reviewers invited by journal 22 Apr, 2026 Editor assigned by journal 22 Apr, 2026 Editor invited by journal 22 Apr, 2026 Submission checks completed at journal 21 Apr, 2026 First submitted to journal 21 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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