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1. Identificação
Tipo de ReferênciaArtigo em Evento (Conference Proceedings)
Sitemtc-m21d.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP3W34T/4878NQ5
Repositóriosid.inpe.br/mtc-m21d/2022/12.13.19.35
Repositório de Metadadossid.inpe.br/mtc-m21d/2022/12.13.19.35.48
Última Atualização dos Metadados2023:01.03.16.46.27 (UTC) administrator
Chave SecundáriaINPE--PRE/
Chave de CitaçãoMindlinGoyHurTedZil:2022:SiChSe
TítuloA Simple Characterization of Sea Surface Temperature Patterns that Represent the Seasonal Evolution of El Niño Southern Oscillation Flavors
Ano2022
Data de Acesso18 maio 2024
Tipo SecundárioPRE CI
2. Contextualização
Autor1 Mindlin, Julia
2 Goyal, Rishav
3 Hurtado, Santiago Ignacio
4 Tedeschi, Renata Gonçalves
5 Zilli, Marcia
Grupo1
2
3
4 DIPTC-CGCT-INPE-MCTI-GOV-BR
Afiliação1 Universidad de Buenos Aires
2 University of New South Wales
3 National University of La Plata
4 Instituto Nacional de Pesquisas Espaciais (INPE)
5 University of Oxford
Nome do EventoAGU Fall Meeting
Localização do EventoChicago, IL
Data12-16 Dec. 2022
Editora (Publisher)AGU
Histórico (UTC)2022-12-13 19:35:48 :: simone -> administrator ::
2023-01-03 16:46:27 :: administrator -> simone :: 2022
3. Conteúdo e estrutura
É a matriz ou uma cópia?é a matriz
Estágio do Conteúdoconcluido
Transferível1
Tipo do ConteúdoExternal Contribution
ResumoIn the last decade, much of the attention on El NinoSouthern Oscillation (ENSO), especially its teleconnections, has focused on differentiating among the events' "flavors". Despite that, the definition of each flavor, useful when classifying events and performing composite analysis, is highly variable in the literature. Furthermore, most of the literature focuses on preferential seasons when the sea surface temperature (SST) anomalies are maximized, resulting in deep convection and Rossby Wave triggering. This work uses k-means clustering algorithms to distinguish significantly different patterns for SST monthly variability considering four SST datasets with varying spatial resolution: Kaplan Extended SST v2, HadlSST, COBE-SST2, ERSSTv5. SST anomalies are clustered over the entire tropical Pacific Ocean (140E,15S to 280E,15N) rather than restricting it to arbitrary regions as in traditional ENSO indices. The analysis also treats ENSO as an evolving system by considering the entire year, classifying monthly SST anomalies into a limited number (seven) of SST patterns (clusters). We first train the clustering algorithm with satellite-era data (1979-2013), identifying seven patterns tested against white noise using a classifiability index. The number of patterns is similar across datasets, attesting to the robustness of the identified patterns. After that, we classify the dataset (1900-2020) based on these SST patterns and investigate the seasonal evolution of transition probabilities of the SST patterns, providing a picture of the seasonal evolution of the flavors. Given the robustness and simplicity of the method, it is easily applicable to classify ENSO flavors in a variety of datasets, including historical and future projections of SST. It also allows a simple representation of nonlinearity between positive and negative ENSO, with a classification method valid for any month of the year.
ÁreaMET
ArranjoA Simple Characterization...
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4. Condições de acesso e uso
Grupo de Usuáriossimone
Visibilidadeshown
Permissão de Atualizaçãonão transferida
5. Fontes relacionadas
Unidades Imediatamente Superiores8JMKD3MGPCW/46KUATE
Acervo Hospedeirourlib.net/www/2021/06.04.03.40
6. Notas
Campos Vaziosarchivingpolicy archivist booktitle callnumber copyholder copyright creatorhistory descriptionlevel dissemination doi e-mailaddress edition editor electronicmailaddress format isbn issn keywords label language lineage mark mirrorrepository nextedition notes numberoffiles numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project publisheraddress readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarymark serieseditor session shorttitle size sponsor subject targetfile tertiarymark tertiarytype type url versiontype volume
7. Controle da descrição
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