Upgrading CCIR’s fo F2 maps using available ionosondes and genetic algorithms
- Autores
- Gularte Scarone, Ángela 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 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 Geofísicas - Materia
-
Geofísica
fo F2 maps
Genetic algorithm
Ionosphere
F region - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by/4.0/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/146954
Ver los metadatos del registro completo
id |
SEDICI_af668269f2eecd4f4da7ccc93d5843ee |
---|---|
oai_identifier_str |
oai:sedici.unlp.edu.ar:10915/146954 |
network_acronym_str |
SEDICI |
repository_id_str |
1329 |
network_name_str |
SEDICI (UNLP) |
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:UNLP2025-09-29T11:37:32Zoai: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:13292025-09-29 11:37:32.588SEDICI (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 |
dc.description.none.fl_txt_mv |
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. Facultad de Ciencias Astronómicas y Geofísicas |
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 |
reponame_str |
SEDICI (UNLP) |
collection |
SEDICI (UNLP) |
instname_str |
Universidad Nacional de La Plata |
instacron_str |
UNLP |
institution |
UNLP |
repository.name.fl_str_mv |
SEDICI (UNLP) - Universidad Nacional de La Plata |
repository.mail.fl_str_mv |
alira@sedici.unlp.edu.ar |
_version_ |
1844616251795570688 |
score |
13.070432 |