Adaptive filtering and prediction of the Southern Oscillation index | Zendy

Keppenne Christian L. | Zendy; Ghil Michael | Zendy

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Adaptive filtering and prediction of the Southern Oscillation index

Author(s) -

Keppenne Christian L.,

Ghil Michael

Publication year - 1992

Publication title -

journal of geophysical research: atmospheres

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.67

H-Index - 298

eISSN - 2156-2202

pISSN - 0148-0227

DOI - 10.1029/92jd02219

Subject(s) - singular spectrum analysis , oscillation (cell signaling) , autoregressive model , principal component analysis , southern oscillation , time series , series (stratigraphy) , spectral analysis , el niño southern oscillation , multivariate enso index , climatology , mathematics , geology , physics , statistics , singular value decomposition , algorithm , chemistry , paleontology , biochemistry , quantum mechanics , spectroscopy

Singular spectrum analysis (SSA), a variant of principal component analysis, is applied to a time series of the Southern Oscillation index (SOI). The analysis filters out variability unrelated to the Southern Oscillation and separates the high‐frequency, 2‐ to 3‐year variability, including the quasi‐biennial oscillation, from the lower‐frequency 4‐ to 6‐year El Niño cycle. The maximum entropy method (MEM) is applied to forecasting the prefiltered SOI. Prediction based on MEM‐associated autoregressive models has useful skill for 30–36 months. A 1993–1994 La Niña event is predicted based on data through February 1992.

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