Randomised multichannel singular spectrum analysis of the 20th century climate data
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dc.contributor.author |
Seitola, Teija |
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dc.contributor.author |
Silen, Johan |
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dc.contributor.author |
Järvinen, Heikki |
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dc.date.accessioned |
2016-05-13T11:25:01Z |
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dc.date.available |
2016-05-13T11:25:01Z |
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dc.date.issued |
2015 |
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dc.identifier.citation |
Seitola , T , Silen , J & Järvinen , H 2015 , ' Randomised multichannel singular spectrum analysis of the 20th century climate data ' , Tellus. Series A: Dynamic Meteorology and Oceanography , vol. 67 , no. 1 , 28876 . https://doi.org/10.3402/tellusa.v67.28876 |
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dc.identifier.other |
PURE: 58721978 |
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dc.identifier.other |
PURE UUID: e71d3ce9-c31e-4032-a75f-bbcf98491bc0 |
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dc.identifier.other |
WOS: 000367311400001 |
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dc.identifier.other |
Scopus: 84980691876 |
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dc.identifier.other |
ORCID: /0000-0003-1879-6804/work/30008067 |
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dc.identifier.uri |
http://hdl.handle.net/10138/162028 |
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dc.description.abstract |
In this article, we introduce a new algorithm called randomised multichannel singular spectrum analysis (RMSSA), which is a generalisation of the traditional multichannel singular spectrum analysis (MSSA) into problems of arbitrarily large dimension. RMSSA consists of (1) a dimension reduction of the original data via random projections, (2) the standard MSSA step and (3) a recovery of the MSSA eigenmodes from the reduced space back to the original space. The RMSSA algorithm is presented in detail and additionally we show how to integrate it with a significance test based on a red noise null-hypothesis by Monte-Carlo simulation. Finally, RMSSA is applied to decompose the 20th century global monthly mean near-surface temperature variability into its low-frequency components. The decomposition of a reanalysis data set and two climate model simulations reveals, for instance, that the 2-6 yr variability centred in the Pacific Ocean is captured by all the data sets with some differences in statistical significance and spatial patterns. |
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dc.format.extent |
17 |
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dc.language.iso |
eng |
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dc.relation.ispartof |
Tellus. Series A: Dynamic Meteorology and Oceanography |
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dc.rights |
cc_by |
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dc.rights.uri |
info:eu-repo/semantics/openAccess |
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dc.subject |
multichannel singular spectrum analysis |
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dc.subject |
random projection |
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dc.subject |
dimensionality reduction |
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dc.subject |
El Nino southern oscillation |
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dc.subject |
20th century reanalysis |
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dc.subject |
HadGEM2-ES |
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dc.subject |
MPI-ESM-MR |
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dc.subject |
NORTHERN-HEMISPHERE |
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dc.subject |
TIME-SERIES |
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dc.subject |
LINDENSTRAUSS |
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dc.subject |
OSCILLATIONS |
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dc.subject |
DYNAMICS |
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dc.subject |
JOHNSON |
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dc.subject |
WEATHER |
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dc.subject |
NOISE |
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dc.subject |
114 Physical sciences |
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dc.title |
Randomised multichannel singular spectrum analysis of the 20th century climate data |
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dc.type |
Article |
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dc.contributor.organization |
Department of Physics |
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dc.description.reviewstatus |
Peer reviewed |
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dc.relation.doi |
https://doi.org/10.3402/tellusa.v67.28876 |
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dc.relation.issn |
0280-6495 |
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dc.rights.accesslevel |
openAccess |
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dc.type.version |
publishedVersion |
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