Upgrading CCIR's foF2 maps using available ionosondes and genetic algorithms

Autores
Gularte Scarone, Angela Erika; Carpintero, Daniel Diego; Jaen, Juliana María
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
We have developed a new approach towards a new database of the ionospheric parameter foF2. 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 foF2 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 Atmósfera 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 foF2 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 night-time. 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 foF2 can be perfomed to obtain the ionospheric parameter M(3000)F2.
Fil: Gularte Scarone, Angela Erika. Universidad Nacional de la Plata. Facultad de Ciencias Astronómicas y Geofísicas. Grupo de Geodesia Espacial y Aeronomia; Argentina
Fil: Carpintero, Daniel Diego. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina
Fil: Jaen, Juliana María. Universidad Nacional de la Plata. Facultad de Ciencias Astronómicas y Geofísicas. Grupo de Geodesia Espacial y Aeronomia; Argentina
Materia
F Region
Fof2 Maps
Genetic Algorithm
Ionosphere
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/39900

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oai_identifier_str oai:ri.conicet.gov.ar:11336/39900
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network_name_str CONICET Digital (CONICET)
spelling Upgrading CCIR's foF2 maps using available ionosondes and genetic algorithmsGularte Scarone, Angela ErikaCarpintero, Daniel DiegoJaen, Juliana MaríaF RegionFof2 MapsGenetic AlgorithmIonospherehttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1We have developed a new approach towards a new database of the ionospheric parameter foF2. 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 foF2 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 Atmósfera 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 foF2 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 night-time. 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 foF2 can be perfomed to obtain the ionospheric parameter M(3000)F2.Fil: Gularte Scarone, Angela Erika. Universidad Nacional de la Plata. Facultad de Ciencias Astronómicas y Geofísicas. Grupo de Geodesia Espacial y Aeronomia; ArgentinaFil: Carpintero, Daniel Diego. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; ArgentinaFil: Jaen, Juliana María. Universidad Nacional de la Plata. Facultad de Ciencias Astronómicas y Geofísicas. Grupo de Geodesia Espacial y Aeronomia; ArgentinaElsevier2018-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/39900Gularte Scarone, Angela Erika; Carpintero, Daniel Diego; Jaen, Juliana María; Upgrading CCIR's foF2 maps using available ionosondes and genetic algorithms; Elsevier; Advances in Space Research; 61; 7; 4-2018; 1790-18020273-1177CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.asr.2017.08.019info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0273117717306142info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:17:56Zoai:ri.conicet.gov.ar:11336/39900instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-22 11:17:56.37CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Upgrading CCIR's foF2 maps using available ionosondes and genetic algorithms
title Upgrading CCIR's foF2 maps using available ionosondes and genetic algorithms
spellingShingle Upgrading CCIR's foF2 maps using available ionosondes and genetic algorithms
Gularte Scarone, Angela Erika
F Region
Fof2 Maps
Genetic Algorithm
Ionosphere
title_short Upgrading CCIR's foF2 maps using available ionosondes and genetic algorithms
title_full Upgrading CCIR's foF2 maps using available ionosondes and genetic algorithms
title_fullStr Upgrading CCIR's foF2 maps using available ionosondes and genetic algorithms
title_full_unstemmed Upgrading CCIR's foF2 maps using available ionosondes and genetic algorithms
title_sort Upgrading CCIR's foF2 maps using available ionosondes and genetic algorithms
dc.creator.none.fl_str_mv Gularte Scarone, Angela Erika
Carpintero, Daniel Diego
Jaen, Juliana María
author Gularte Scarone, Angela Erika
author_facet Gularte Scarone, Angela 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 F Region
Fof2 Maps
Genetic Algorithm
Ionosphere
topic F Region
Fof2 Maps
Genetic Algorithm
Ionosphere
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv We have developed a new approach towards a new database of the ionospheric parameter foF2. 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 foF2 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 Atmósfera 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 foF2 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 night-time. 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 foF2 can be perfomed to obtain the ionospheric parameter M(3000)F2.
Fil: Gularte Scarone, Angela Erika. Universidad Nacional de la Plata. Facultad de Ciencias Astronómicas y Geofísicas. Grupo de Geodesia Espacial y Aeronomia; Argentina
Fil: Carpintero, Daniel Diego. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina
Fil: Jaen, Juliana María. Universidad Nacional de la Plata. Facultad de Ciencias Astronómicas y Geofísicas. Grupo de Geodesia Espacial y Aeronomia; Argentina
description We have developed a new approach towards a new database of the ionospheric parameter foF2. 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 foF2 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 Atmósfera 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 foF2 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 night-time. 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 foF2 can be perfomed to obtain the ionospheric parameter M(3000)F2.
publishDate 2018
dc.date.none.fl_str_mv 2018-04
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
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://hdl.handle.net/11336/39900
Gularte Scarone, Angela Erika; Carpintero, Daniel Diego; Jaen, Juliana María; Upgrading CCIR's foF2 maps using available ionosondes and genetic algorithms; Elsevier; Advances in Space Research; 61; 7; 4-2018; 1790-1802
0273-1177
CONICET Digital
CONICET
url http://hdl.handle.net/11336/39900
identifier_str_mv Gularte Scarone, Angela Erika; Carpintero, Daniel Diego; Jaen, Juliana María; Upgrading CCIR's foF2 maps using available ionosondes and genetic algorithms; Elsevier; Advances in Space Research; 61; 7; 4-2018; 1790-1802
0273-1177
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.asr.2017.08.019
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0273117717306142
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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