Ionospheric response modeling under eclipse conditions: Evaluation of 14 December 2020, total solar eclipse prediction over the South American sector

dc.contributor.affiliationPontificia Universidad Católica del Perú
dc.contributor.authorBravo, M.A.
dc.contributor.authorMolina, M.G.
dc.contributor.authorMartínez-Ledesma, M.
dc.contributor.authorde Haro Barbás, B.
dc.contributor.authorUrra, B.
dc.contributor.authorElías, A.
dc.contributor.authorde Souza, J.
dc.contributor.authorVillalobos, C.
dc.contributor.authorNamour, J.H.
dc.contributor.authorOvalle, E.
dc.contributor.authorVenchiarutti, J.V.
dc.contributor.authorBlunier, S.
dc.contributor.authorValdés-Abreu, J.C.
dc.contributor.authorGuillermo, E.
dc.contributor.authorRojo, E.
dc.contributor.authorde Pasquale, L.
dc.contributor.authorCarrasco, E.
dc.date.accessioned2026-03-13T16:58:33Z
dc.date.issued2022
dc.description.abstractIn this work, we evaluate the SUPIM-INPE model prediction of the 14 December 2020, total solar eclipse over the South American continent. We compare the predictions with data from multiple instruments for monitoring the ionosphere and with different obscuration percentages (i.e., Jicamarca, 12.0°S, 76.8°W, 17%; Tucumán 26.9°S, 65.4° W, 49%; Chillán 36.6°S, 72.0°W; and Bahía Blanca, 38.7°S, 62.3°W, reach 95% obscuration) due to the eclipse. The analysis is done under total eclipse conditions and non-total eclipse conditions. Results obtained suggest that the model was able to reproduce with high accuracy both the daily variation and the eclipse impacts of E and F1 layers in the majority of the stations evaluated (except in Jicamarca station). The comparison at the F2 layer indicates small differences (<7.8%) between the predictions and observations at all stations during the eclipse periods. Additionally, statistical metrics reinforce the conclusion of a good performance of the model. Predicted and calibrated Total Electron Content (TEC, using 3 different techniques) are also compared. Results show that, although none of the selected TEC calibration methods have a good agreement with the SUPIM-INPE prediction, they exhibit similar trends in most of the cases. We also analyze data from the Jicamarca Incoherent Scatter Radar (ISR), and Swarm-A and GOLD missions. The electron temperature changes observed in ISR and Swarm-A are underestimated by the prediction. Also, important changes in the O/N2 ratio due to the eclipse, have been observed with GOLD mission data. Thus, future versions of the SUPIM-INPE model for eclipse conditions should consider effects on thermospheric winds and changes in composition, specifically in the O/N2 ratio.
dc.description.sponsorshipFunding: In this study, data from the Jicamarca Radio Observatory (JRO) Incoherent Scatter Radar has been used. The JRO is a research facility of the Instituto Geofísico del Perú operated with support from the National Science Foundation through Cornell University under award AGS-1732209. Access to the GNSS data was kindly provided by the International GNSS Service (IGS, www.igs.org ), by the Centro Sismológico Nacional (CSN) of the Universidad de Chile ( www.sismologia.cl ), by the Red Argentina de Monitoreo Satelital Continuo (RAMSAC) of the Instituto Geográfico Nacional de la República Argentina ( www.ign.gob.ar ), by the Rede Brasileira de Monitoramento Contínuo dos Sistemas GNSS (RBMC) of the Instituto Brasileiro de Geografia e Estatística (ww2.ibge.gov.br), the Red Geodésica Nacional Activa (REGNA) of the Instituto Geográfico Militar del Uruguay ( ftp://pp.igm.gub.uy ) and from Colombian network (MAGNA, https://geoportal.igac.gov.co ). Cesar Valladares kindly provided access to the Low-Latitude Ionospheric Sensor Network (LISN, http://lisn.igp.gob.pe/ ). LISN is a project led by the University of Texas at Dallas in collaboration with the Geophysical Institute of Perú. We acknowledge Tucumán Space Weather Center (TSWC), Argentina, https://spaceweather.facet.unt.edu.ar/ for providing the AIS-INGV data. We thank the European Space Agency that supports the Swarm mission and acknowledge the engineers and research team of the GOLD mission ( https://gold.cs.ucf.edu/ ). MB acknowledges CONICYT/FONDECYT Postdoctorado 3180742, and together with MS to FONDECYT REGULAR 1211144. MM-L acknowledges the support of ANID/FONDECYT Postdoctorado 3220581 and Comité Mixto ESO-Chile ORP061/19. JV-A acknowledges the support of ANID/Scholarship Program/Doctorado Nacional/2018-21181599. BF, BH, and AG, AE acknowledge Project PIP 2957 (CONICET). JV and SB acknowledge the support of ANID/FONDECYT 1190703 and the US AFOSR PI FA9550-20-1-0189. MM acknowledges project PIUNT 26/E-689. MM, BF, BH, AG, and AE acknowledge project PICT 2018-04447 projects. The authors thank MSc. Eduardo Gutiérrez for his guidance on statistics.
dc.identifier.doihttps://doi.org/10.3389/fspas.2022.1021910
dc.identifier.urihttp://hdl.handle.net/20.500.14657/205937
dc.language.isoeng
dc.publisherFrontiers Media
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.sourceFrontiers in Astronomy and Space Sciences; Vol. 9 (2022)
dc.subjectTEC
dc.subjectEclipse
dc.subjectSolar eclipse
dc.subjectIonosphere
dc.subjectMeteorology
dc.subjectPhysics
dc.subjectEnvironmental science
dc.subjectAstrophysics
dc.subjectAstronomy
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#1.03.08
dc.titleIonospheric response modeling under eclipse conditions: Evaluation of 14 December 2020, total solar eclipse prediction over the South American sector
dc.typehttp://purl.org/coar/resource_type/c_6501
dc.type.otherArtículo
dc.type.versionhttps://vocabularies.coar-repositories.org/version_types/c_970fb48d4fbd8a85/

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