Fractional State Space Analysis of Temperature Time Series, FCAA
Main Author: | |
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Publication Date: | 2015 |
Other Authors: | |
Format: | Article |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | http://hdl.handle.net/10400.22/8822 |
Summary: | Atmospheric temperatures characterize Earth as a slow dynamics spatiotemporal system, revealing long-memory and complex behavior. Temperature time series of 54 worldwide geographic locations are considered as representative of the Earth weather dynamics. These data are then interpreted as the time evolution of a set of state space variables describing a complex system. The data are analyzed by means of multidimensional scaling (MDS), and the fractional state space portrait (fSSP). A centennial perspective covering the period from 1910 to 2012 allows MDS to identify similarities among different Earth’s locations. The multivariate mutual information is proposed to determine the “optimal” order of the time derivative for the fSSP representation. The fSSP emerges as a valuable alternative for visualizing system dynamics. |
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Fractional State Space Analysis of Temperature Time Series, FCAAMultidimensional scalingTime seriesFractional calculusState space portraitClusteringAtmospheric temperatures characterize Earth as a slow dynamics spatiotemporal system, revealing long-memory and complex behavior. Temperature time series of 54 worldwide geographic locations are considered as representative of the Earth weather dynamics. These data are then interpreted as the time evolution of a set of state space variables describing a complex system. The data are analyzed by means of multidimensional scaling (MDS), and the fractional state space portrait (fSSP). A centennial perspective covering the period from 1910 to 2012 allows MDS to identify similarities among different Earth’s locations. The multivariate mutual information is proposed to determine the “optimal” order of the time derivative for the fSSP representation. The fSSP emerges as a valuable alternative for visualizing system dynamics.De GruyterREPOSITÓRIO P.PORTOMachado, J. A. TenreiroLopes, António M.2016-12-14T15:45:05Z2015-122015-12-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/8822eng1314-22241311-045410.1515/fca-2015-0088info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-04-02T03:28:04Zoai:recipp.ipp.pt:10400.22/8822Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T00:57:14.777760Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
Fractional State Space Analysis of Temperature Time Series, FCAA |
title |
Fractional State Space Analysis of Temperature Time Series, FCAA |
spellingShingle |
Fractional State Space Analysis of Temperature Time Series, FCAA Machado, J. A. Tenreiro Multidimensional scaling Time series Fractional calculus State space portrait Clustering |
title_short |
Fractional State Space Analysis of Temperature Time Series, FCAA |
title_full |
Fractional State Space Analysis of Temperature Time Series, FCAA |
title_fullStr |
Fractional State Space Analysis of Temperature Time Series, FCAA |
title_full_unstemmed |
Fractional State Space Analysis of Temperature Time Series, FCAA |
title_sort |
Fractional State Space Analysis of Temperature Time Series, FCAA |
author |
Machado, J. A. Tenreiro |
author_facet |
Machado, J. A. Tenreiro Lopes, António M. |
author_role |
author |
author2 |
Lopes, António M. |
author2_role |
author |
dc.contributor.none.fl_str_mv |
REPOSITÓRIO P.PORTO |
dc.contributor.author.fl_str_mv |
Machado, J. A. Tenreiro Lopes, António M. |
dc.subject.por.fl_str_mv |
Multidimensional scaling Time series Fractional calculus State space portrait Clustering |
topic |
Multidimensional scaling Time series Fractional calculus State space portrait Clustering |
description |
Atmospheric temperatures characterize Earth as a slow dynamics spatiotemporal system, revealing long-memory and complex behavior. Temperature time series of 54 worldwide geographic locations are considered as representative of the Earth weather dynamics. These data are then interpreted as the time evolution of a set of state space variables describing a complex system. The data are analyzed by means of multidimensional scaling (MDS), and the fractional state space portrait (fSSP). A centennial perspective covering the period from 1910 to 2012 allows MDS to identify similarities among different Earth’s locations. The multivariate mutual information is proposed to determine the “optimal” order of the time derivative for the fSSP representation. The fSSP emerges as a valuable alternative for visualizing system dynamics. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-12 2015-12-01T00:00:00Z 2016-12-14T15:45:05Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.22/8822 |
url |
http://hdl.handle.net/10400.22/8822 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
1314-2224 1311-0454 10.1515/fca-2015-0088 |
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info:eu-repo/semantics/openAccess |
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openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
De Gruyter |
publisher.none.fl_str_mv |
De Gruyter |
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RCAAP |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
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