Principal sequence pattern analysis: A new approach to classifying the evolution of atmospheric systems

A new eigentechnique approach, Principal Sequence Pattern Analysis (PSPA), is introduced for the analysis of spatial pattern sequence, as an extension of the traditional Principal Component Analysis set in the T-Mode. In this setting, the variables are sequences of k spatial fields of a given meteor...

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Autores principales: Compagnucci, Rosa H., Araneo, Diego, Canziani, Pablo Osvaldo
Formato: Articulo
Lenguaje:Inglés
Publicado: 2001
Materias:
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/84959
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id I19-R120-10915-84959
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Naturales
Atmospheric circulation
Extended empirical orthogonal function
Principal components analysis
Principal sequence pattern analysis
Synoptic climatology
T-mode approach
spellingShingle Ciencias Naturales
Atmospheric circulation
Extended empirical orthogonal function
Principal components analysis
Principal sequence pattern analysis
Synoptic climatology
T-mode approach
Compagnucci, Rosa H.
Araneo, Diego
Canziani, Pablo Osvaldo
Principal sequence pattern analysis: A new approach to classifying the evolution of atmospheric systems
topic_facet Ciencias Naturales
Atmospheric circulation
Extended empirical orthogonal function
Principal components analysis
Principal sequence pattern analysis
Synoptic climatology
T-mode approach
description A new eigentechnique approach, Principal Sequence Pattern Analysis (PSPA), is introduced for the analysis of spatial pattern sequence, as an extension of the traditional Principal Component Analysis set in the T-Mode. In this setting, the variables are sequences of k spatial fields of a given meteorological variable. PSPA is described and applied to a sample of 256 consecutive daily 1000 hPa geopotential height fields. The results of the application of the technique to 5-day sequences demonstrate the advantages of this procedure in identifying field pattern sequences, thereby allowing the determination of the evolution and development of the systems, together with cyclogenesis and anticyclogenesis processes. In order to complete the study, the more traditional Extended Empirical Orthogonal Function (EEOF) analysis, which is the S-mode equivalent of the PSPA, was applied to the same dataset. For EEOF, it was not possible to identify any real sequences that could correspond to the sequences of patterns yielded by the EEOF. Furthermore, the explained variance distribution in the EEOF was significantly different from that obtained with PSPA. Conversely, the PSPA approach allowed for the identification of the sequences corresponding to those sequences observed in the data. Using diagrams of the squares of the component loadings values, as a function of time, the study of the times of occurrence of dominant field characteristics was also possible. In other words, successful determination of periods where the basic flow was dominant and times when strongly perturbed transient events with a significant meridional component occurred, was facilitated by PSPA.
format Articulo
Articulo
author Compagnucci, Rosa H.
Araneo, Diego
Canziani, Pablo Osvaldo
author_facet Compagnucci, Rosa H.
Araneo, Diego
Canziani, Pablo Osvaldo
author_sort Compagnucci, Rosa H.
title Principal sequence pattern analysis: A new approach to classifying the evolution of atmospheric systems
title_short Principal sequence pattern analysis: A new approach to classifying the evolution of atmospheric systems
title_full Principal sequence pattern analysis: A new approach to classifying the evolution of atmospheric systems
title_fullStr Principal sequence pattern analysis: A new approach to classifying the evolution of atmospheric systems
title_full_unstemmed Principal sequence pattern analysis: A new approach to classifying the evolution of atmospheric systems
title_sort principal sequence pattern analysis: a new approach to classifying the evolution of atmospheric systems
publishDate 2001
url http://sedici.unlp.edu.ar/handle/10915/84959
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