Predictions of the Maximum Amplitude, Time of Occurrence, and Total Length of Solar Cycle 24

Autores
Uzal, Lucas César; Piacentini, Ruben Dario Narciso; Verdes, Pablo Fabian
Año de publicación
2012
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In this work we predict the maximum amplitude, its time of occurrence, and the total length of Solar Cycle 24 by linear regression to the curvature (second derivative) at the preceding minimum of a smoothed version of the sunspots time series. We characterise the predictive power of the proposed methodology in a causal manner by an incremental incorporation of past solar cycles to the available data base. In regressing maximum cycle intensity to curvature at the leading minimum, we obtain a correlation coefficient R≈0.91 and for the upcoming Cycle 24 a forecast of 78 (90 % confidence interval: 56 ? 106). The ascent time also appears to be highly correlated to the second derivative at the starting minimum (R≈−0.77), predicting maximum solar activity for October 2013 (90 % confidence interval: January 2013 to September 2014). Solar Cycle 24 should come to an end by February 2020 (90 % confidence interval: January 2019 to July 2021), although in this case correlational evidence is weaker (R≈−0.56).
Fil: Uzal, Lucas César. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
Fil: Piacentini, Ruben Dario Narciso. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Física de Rosario. Universidad Nacional de Rosario. Instituto de Física de Rosario; Argentina
Fil: Verdes, Pablo Fabian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
Materia
ASCENT TIME
MAXIMUM ACTIVITY PREDICTION
SOLAR CYCLE 24
TOTAL CYCLE LENGTH
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:11336/162820
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Predictions of the Maximum Amplitude, Time of Occurrence, and Total Length of Solar Cycle 24Uzal, Lucas CésarPiacentini, Ruben Dario NarcisoVerdes, Pablo FabianASCENT TIMEMAXIMUM ACTIVITY PREDICTIONSOLAR CYCLE 24TOTAL CYCLE LENGTHhttps://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1In this work we predict the maximum amplitude, its time of occurrence, and the total length of Solar Cycle 24 by linear regression to the curvature (second derivative) at the preceding minimum of a smoothed version of the sunspots time series. We characterise the predictive power of the proposed methodology in a causal manner by an incremental incorporation of past solar cycles to the available data base. In regressing maximum cycle intensity to curvature at the leading minimum, we obtain a correlation coefficient R≈0.91 and for the upcoming Cycle 24 a forecast of 78 (90 % confidence interval: 56 ? 106). The ascent time also appears to be highly correlated to the second derivative at the starting minimum (R≈−0.77), predicting maximum solar activity for October 2013 (90 % confidence interval: January 2013 to September 2014). Solar Cycle 24 should come to an end by February 2020 (90 % confidence interval: January 2019 to July 2021), although in this case correlational evidence is weaker (R≈−0.56).Fil: Uzal, Lucas César. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Piacentini, Ruben Dario Narciso. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Física de Rosario. Universidad Nacional de Rosario. Instituto de Física de Rosario; ArgentinaFil: Verdes, Pablo Fabian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaSpringer2012-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/162820Uzal, Lucas César; Piacentini, Ruben Dario Narciso; Verdes, Pablo Fabian; Predictions of the Maximum Amplitude, Time of Occurrence, and Total Length of Solar Cycle 24; Springer; Solar Physics; 279; 2; 6-2012; 551-5600038-0938CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007/s11207-012-0030-9info:eu-repo/semantics/altIdentifier/doi/10.1007/s11207-012-0030-9info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:22:17Zoai:ri.conicet.gov.ar:11336/162820instacron: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 11:22:17.763CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Predictions of the Maximum Amplitude, Time of Occurrence, and Total Length of Solar Cycle 24
title Predictions of the Maximum Amplitude, Time of Occurrence, and Total Length of Solar Cycle 24
spellingShingle Predictions of the Maximum Amplitude, Time of Occurrence, and Total Length of Solar Cycle 24
Uzal, Lucas César
ASCENT TIME
MAXIMUM ACTIVITY PREDICTION
SOLAR CYCLE 24
TOTAL CYCLE LENGTH
title_short Predictions of the Maximum Amplitude, Time of Occurrence, and Total Length of Solar Cycle 24
title_full Predictions of the Maximum Amplitude, Time of Occurrence, and Total Length of Solar Cycle 24
title_fullStr Predictions of the Maximum Amplitude, Time of Occurrence, and Total Length of Solar Cycle 24
title_full_unstemmed Predictions of the Maximum Amplitude, Time of Occurrence, and Total Length of Solar Cycle 24
title_sort Predictions of the Maximum Amplitude, Time of Occurrence, and Total Length of Solar Cycle 24
dc.creator.none.fl_str_mv Uzal, Lucas César
Piacentini, Ruben Dario Narciso
Verdes, Pablo Fabian
author Uzal, Lucas César
author_facet Uzal, Lucas César
Piacentini, Ruben Dario Narciso
Verdes, Pablo Fabian
author_role author
author2 Piacentini, Ruben Dario Narciso
Verdes, Pablo Fabian
author2_role author
author
dc.subject.none.fl_str_mv ASCENT TIME
MAXIMUM ACTIVITY PREDICTION
SOLAR CYCLE 24
TOTAL CYCLE LENGTH
topic ASCENT TIME
MAXIMUM ACTIVITY PREDICTION
SOLAR CYCLE 24
TOTAL CYCLE LENGTH
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv In this work we predict the maximum amplitude, its time of occurrence, and the total length of Solar Cycle 24 by linear regression to the curvature (second derivative) at the preceding minimum of a smoothed version of the sunspots time series. We characterise the predictive power of the proposed methodology in a causal manner by an incremental incorporation of past solar cycles to the available data base. In regressing maximum cycle intensity to curvature at the leading minimum, we obtain a correlation coefficient R≈0.91 and for the upcoming Cycle 24 a forecast of 78 (90 % confidence interval: 56 ? 106). The ascent time also appears to be highly correlated to the second derivative at the starting minimum (R≈−0.77), predicting maximum solar activity for October 2013 (90 % confidence interval: January 2013 to September 2014). Solar Cycle 24 should come to an end by February 2020 (90 % confidence interval: January 2019 to July 2021), although in this case correlational evidence is weaker (R≈−0.56).
Fil: Uzal, Lucas César. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
Fil: Piacentini, Ruben Dario Narciso. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Física de Rosario. Universidad Nacional de Rosario. Instituto de Física de Rosario; Argentina
Fil: Verdes, Pablo Fabian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
description In this work we predict the maximum amplitude, its time of occurrence, and the total length of Solar Cycle 24 by linear regression to the curvature (second derivative) at the preceding minimum of a smoothed version of the sunspots time series. We characterise the predictive power of the proposed methodology in a causal manner by an incremental incorporation of past solar cycles to the available data base. In regressing maximum cycle intensity to curvature at the leading minimum, we obtain a correlation coefficient R≈0.91 and for the upcoming Cycle 24 a forecast of 78 (90 % confidence interval: 56 ? 106). The ascent time also appears to be highly correlated to the second derivative at the starting minimum (R≈−0.77), predicting maximum solar activity for October 2013 (90 % confidence interval: January 2013 to September 2014). Solar Cycle 24 should come to an end by February 2020 (90 % confidence interval: January 2019 to July 2021), although in this case correlational evidence is weaker (R≈−0.56).
publishDate 2012
dc.date.none.fl_str_mv 2012-06
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/11336/162820
Uzal, Lucas César; Piacentini, Ruben Dario Narciso; Verdes, Pablo Fabian; Predictions of the Maximum Amplitude, Time of Occurrence, and Total Length of Solar Cycle 24; Springer; Solar Physics; 279; 2; 6-2012; 551-560
0038-0938
CONICET Digital
CONICET
url http://hdl.handle.net/11336/162820
identifier_str_mv Uzal, Lucas César; Piacentini, Ruben Dario Narciso; Verdes, Pablo Fabian; Predictions of the Maximum Amplitude, Time of Occurrence, and Total Length of Solar Cycle 24; Springer; Solar Physics; 279; 2; 6-2012; 551-560
0038-0938
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007/s11207-012-0030-9
info:eu-repo/semantics/altIdentifier/doi/10.1007/s11207-012-0030-9
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 Springer
publisher.none.fl_str_mv Springer
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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score 12.982451

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