Laboratorio de Ionosfera, Atmosfera Neutra y Magnetosfera (LIANM), Facultad de Ciencias Exactas y Tecnología (FACET), Universidad Nacional de Tucumán (UNT), Tucumán, 4000, Argentina
INFINOA, CONICET-UNT, Tucumán, 4000, Argentina
Franco D. Medina
Laboratorio de Ionosfera, Atmosfera Neutra y Magnetosfera (LIANM), Facultad de Ciencias Exactas y Tecnología (FACET), Universidad Nacional de Tucumán (UNT), Tucumán, 4000, Argentina
INFINOA, CONICET-UNT, Tucumán, 4000, Argentina
Trinidad Duran
Departamento de Física, Universidad Nacional del Sur (UNS), Bahía Blanca, 8000, Argentina
Instituto de Física del Sur (CONICET-UNS), Bahía Blanca, 8000, Argentina
Blas F. de Haro Barbas
Laboratorio de Ionosfera, Atmosfera Neutra y Magnetosfera (LIANM), Facultad de Ciencias Exactas y Tecnología (FACET), Universidad Nacional de Tucumán (UNT), Tucumán, 4000, Argentina
INFINOA, CONICET-UNT, Tucumán, 4000, Argentina
Ana G. Elias
Laboratorio de Ionosfera, Atmosfera Neutra y Magnetosfera (LIANM), Facultad de Ciencias Exactas y Tecnología (FACET), Universidad Nacional de Tucumán (UNT), Tucumán, 4000, Argentina
INFINOA, CONICET-UNT, Tucumán, 4000, Argentina
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Total article views: 1,392 (including HTML, PDF, and XML)
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Total article views: 458 (including HTML, PDF, and XML)
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This study explores how solar sunspot number (Sn) compares with other solar indicators like solar radio fluxes in predicting changes in Earth's ionosphere, particularly its critical frequency, over more than 60 years. The work finds that Sn, despite recent fluctuations in other proxies, remains the most stable predictor across all time periods. When adjusting for potential data saturation, Sn outperforms other proxies, providing a more accurate forecast of long-term ionospheric trends.
This study explores how solar sunspot number (Sn) compares with other solar indicators like...