Upgrading CCIR’s fo F2 maps using available ionosondes and genetic algorithms

We have developed a new approach towards a new database of the ionospheric parameter f oF 2. This parameter, being the frequency of the maximum of the ionospheric electronic density profile and its main modeller, is of great interest not only in atmospheric studies but also in the realm of radio pro...

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Autores: Gularte Scarone, Ángela Erika, Carpintero, Daniel Diego, Jaen, Juliana María
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2018
País:Argentina
Recursos:Universidad Nacional de La Plata
Repositorio:SEDICI (UNLP)
Idioma:inglés
OAI Identifier:oai:sedici.unlp.edu.ar:10915/146954
Acesso em linha:http://sedici.unlp.edu.ar/handle/10915/146954
Access Level:acceso abierto
Palavra-chave:Geofísica
fo F2 maps
Genetic algorithm
Ionosphere
F region
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spelling Upgrading CCIR’s fo F2 maps using available ionosondes and genetic algorithmsGularte Scarone, Ángela ErikaCarpintero, Daniel DiegoJaen, Juliana MaríaGeofísicafo F2 mapsGenetic algorithmIonosphereF regionWe have developed a new approach towards a new database of the ionospheric parameter f oF 2. This parameter, being the frequency of the maximum of the ionospheric electronic density profile and its main modeller, is of great interest not only in atmospheric studies but also in the realm of radio propagation. The current databases, generated by CCIR (Committee Consultative for Ionospheric Radiowave propagation) and URSI (International Union of Radio Science), and used by the IRI (International Reference Ionosphere) model, are based on Fourier expansions and have been built in the 60s from the available ionosondes at that time. The main goal of this work is to upgrade the databases by using new available ionosonde data. To this end we used the IRI diurnal/spherical expansions to represent the f oF 2 variability, and computed its coefficients by means of a genetic algorithm (GA). In order to test the performance of the proposed methodology, we applied it to the South American region with data obtained by RAPEAS (Red Argentina para el Estudio de la Atmo´ sfera Superior, i.e. Argentine Network for the Study of the Upper Atmosphere) during the years 1958–2009. The new GA coefficients provide a global better fit of the IRI model to the observed f oF 2 than the CCIR coefficients. Since the same formulae and the same number of coefficients were used, the overall integrity of IRI’s typical ionospheric feature representation was preserved. The best improvements with respect to CCIR are obtained at low solar activities, at large (in absolute value) modip latitudes, and at nighttime. The new method is flexible in the sense that can be applied either globally or regionally. It is also very easy to recompute the coefficients when new data is available. The computation of a third set of coefficients corresponding to days of medium solar activity in order to avoid the interpolation between low and high activities is suggested. The same procedure as for f oF 2 can be perfomed to obtain the ionospheric parameter M(3000)F2.Facultad de Ciencias Astronómicas y Geofísicas2018info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf1790-1802http://sedici.unlp.edu.ar/handle/10915/146954enginfo:eu-repo/semantics/altIdentifier/issn/0273-1177info:eu-repo/semantics/altIdentifier/doi/10.1016/j.asr.2017.08.019info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International (CC BY 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2024-05-08T13:15:58Zoai:sedici.unlp.edu.ar:10915/146954Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292024-05-08 13:15:58.75SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Upgrading CCIR’s fo F2 maps using available ionosondes and genetic algorithms
title Upgrading CCIR’s fo F2 maps using available ionosondes and genetic algorithms
spellingShingle Upgrading CCIR’s fo F2 maps using available ionosondes and genetic algorithms
Gularte Scarone, Ángela Erika
Geofísica
fo F2 maps
Genetic algorithm
Ionosphere
F region
title_short Upgrading CCIR’s fo F2 maps using available ionosondes and genetic algorithms
title_full Upgrading CCIR’s fo F2 maps using available ionosondes and genetic algorithms
title_fullStr Upgrading CCIR’s fo F2 maps using available ionosondes and genetic algorithms
title_full_unstemmed Upgrading CCIR’s fo F2 maps using available ionosondes and genetic algorithms
title_sort Upgrading CCIR’s fo F2 maps using available ionosondes and genetic algorithms
dc.creator.none.fl_str_mv Gularte Scarone, Ángela Erika
Carpintero, Daniel Diego
Jaen, Juliana María
author Gularte Scarone, Ángela Erika
author_facet Gularte Scarone, Ángela Erika
Carpintero, Daniel Diego
Jaen, Juliana María
author_role author
author2 Carpintero, Daniel Diego
Jaen, Juliana María
author2_role author
author
dc.subject.none.fl_str_mv Geofísica
fo F2 maps
Genetic algorithm
Ionosphere
F region
topic Geofísica
fo F2 maps
Genetic algorithm
Ionosphere
F region
description We have developed a new approach towards a new database of the ionospheric parameter f oF 2. This parameter, being the frequency of the maximum of the ionospheric electronic density profile and its main modeller, is of great interest not only in atmospheric studies but also in the realm of radio propagation. The current databases, generated by CCIR (Committee Consultative for Ionospheric Radiowave propagation) and URSI (International Union of Radio Science), and used by the IRI (International Reference Ionosphere) model, are based on Fourier expansions and have been built in the 60s from the available ionosondes at that time. The main goal of this work is to upgrade the databases by using new available ionosonde data. To this end we used the IRI diurnal/spherical expansions to represent the f oF 2 variability, and computed its coefficients by means of a genetic algorithm (GA). In order to test the performance of the proposed methodology, we applied it to the South American region with data obtained by RAPEAS (Red Argentina para el Estudio de la Atmo´ sfera Superior, i.e. Argentine Network for the Study of the Upper Atmosphere) during the years 1958–2009. The new GA coefficients provide a global better fit of the IRI model to the observed f oF 2 than the CCIR coefficients. Since the same formulae and the same number of coefficients were used, the overall integrity of IRI’s typical ionospheric feature representation was preserved. The best improvements with respect to CCIR are obtained at low solar activities, at large (in absolute value) modip latitudes, and at nighttime. The new method is flexible in the sense that can be applied either globally or regionally. It is also very easy to recompute the coefficients when new data is available. The computation of a third set of coefficients corresponding to days of medium solar activity in order to avoid the interpolation between low and high activities is suggested. The same procedure as for f oF 2 can be perfomed to obtain the ionospheric parameter M(3000)F2.
publishDate 2018
dc.date.none.fl_str_mv 2018
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/146954
url http://sedici.unlp.edu.ar/handle/10915/146954
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/0273-1177
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.asr.2017.08.019
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
Creative Commons Attribution 4.0 International (CC BY 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
Creative Commons Attribution 4.0 International (CC BY 4.0)
dc.format.none.fl_str_mv application/pdf
1790-1802
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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