Principal component analysis in the modeling of HILDCAAs during the Solar Minimum of Cycle 23/24

Página do item simplificado
dc.contributor.authorKlausner, Virginia
dc.contributor.authorLamin, Isabelle Cristine Pellegrini
dc.contributor.authorOjeda-González, Arian
dc.contributor.authorMacedo, Humberto Gimenes
dc.contributor.authorCândido, Claudia Maria Nicoli
dc.contributor.authorPrestes, Alan
dc.contributor.authorCezarini, Marina Vedelago
dc.date.accessioned2025-04-08T14:23:09Z
dc.date.available2025-04-08T14:23:09Z
dc.date.issued22021
dc.description.abstractIn this article, we propose a new approach to model the high-intensity, long-duration, continuous AE (Auroral Electrojet) activity (HILDCAA) by relaxing one of the criteria originally designed, based on the interplanetary features during the unusual Solar Minimum of Cycle 23/24 (SMC23/24). This relaxation does not intend to suppress or modify the original HILDCAAs’ conception, but propose a new view of the same phenomena by enlarging the sample of events, which in turn may improve space weather monitoring and prediction programs. To assess and classify the Alfvénity associated with HILDCAAs, the values of 4h-Windowed Pearson Cross-Correlation (4WPCC) between the IMF components and the solar wind speed components observed in situ at the Lagrangian point L1 (1 AU) were evaluated. The principal component analysis (PCA) was performed on the dataset and, from the first three principal components, which represent 65% of the accumulative percent variance, we applied principal component regression (PCR) in each of the following parameters: the AE index, the Interplanetary Magnetic Field (IMF) components, the plasma density, the solar wind speed, the temperature, the IMF magnitude, and the SYM-H geomagnetic index. Furthermore, we applied Multiple Linear Regression (MLR) to establish a linear model to express the AE index in terms of the PCR-based model parameters. The AE MLR-based model demonstrated to hold a prognosis potential for HILDCAAs. Despite that, this model is only suitable for the SMC23/24. In this sense, this model might be implemented a real-time analysis for short-term HILDCAA prognosis in the near future.
dc.description.physical12 p.
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.description.uriFAPESP (2018/02692-0) CNPq (147392/2017-9, 118040/2017-0, 305249/2018-5, 431396/2018-3)
dc.format.mimetypePDF
dc.identifier.affiliationUniversidade do Vale do Paraíba
dc.identifier.affiliationInstituto Nacional de Pesquisas Espaciais
dc.identifier.bibliographicCitationKLAUSNER, Virginia et al. Principal component analysis in the modeling of HILDCAAs during the Solar Minimum of Cycle 23/24. Journal of Atmospheric and Solar-Terrestrial Physics, v. 213, p. 1-12, 2021. Disponível em:
dc.identifier.doi10.1016/j.jastp.2020.105516
dc.identifier.urihttps://repositorio.univap.br/handle/123456789/822
dc.language.isoen_US
dc.publisherElsevier
dc.rights.holderJournal of Atmospheric and Solar-Terrestrial Physics
dc.subject.keywordPrincipal component analysis
dc.subject.keywordAlfvénicity
dc.subject.keywordSolar minimum of cycle
dc.titlePrincipal component analysis in the modeling of HILDCAAs during the Solar Minimum of Cycle 23/24
dc.typeArtigos de Periódicos

Arquivos

Pacote Original
Agora exibindo 1 - 1 de 1
Nenhuma Miniatura disponível
Nome:
Principal component analysis in the modeling of HILDCAAs during the Solar Minimum of Cycle 23:24.pdf
Tamanho:
8.83 MB
Formato:
Adobe Portable Document Format
Descrição:
Acesso via Portal Capes
Baixar
Licença do Pacote
Agora exibindo 1 - 1 de 1
Nenhuma Miniatura disponível
Nome:
license.txt
Tamanho:
1.71 KB
Formato:
Item-specific license agreed upon to submission
Descrição:
Baixar

Coleções

Produção acadêmica-PPGFA