Randomised multichannel singular spectrum analysis of the 20th century climate data

Teija Seitola; Johan Silén; Heikki Järvinen

doi:10.3402/tellusa.v67.28876

Randomised multichannel singular spectrum analysis of the 20th century climate data

Tellus

Volume 67 (2015): Issue 1

By: Teija Seitola, Johan Silén and Heikki Järvinen

Open Access

|Dec 2015

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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Articles in this issue

DOI: https://doi.org/10.3402/tellusa.v67.28876 | Journal eISSN: 3035-9554

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Language: English

Page range: 28876 - 28876

Submitted on: Jun 24, 2015

Accepted on: Dec 8, 2015

Published on: Dec 1, 2015

Published by: Stockholm University Press

In partnership with: Paradigm Publishing Services

Keywords:

multichannel singular spectrum analysis,

random projection,

dimensionality reduction,

El Niño – southern oscillation,

20th century reanalysis,

HadGEM2-ES,

MPI-ESM-MR

© 2015 Teija Seitola, Johan Silén, Heikki Järvinen, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.

Volume 67 (2015): Issue 1