A multivariate frequency-domain approach to long-lead climatic forecasting

Balaji Rajagopalan, Michael E. Mann, Upmanu Lall

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

Guided by the increasing awareness and detectability of spatiotemporally organized climatic variability at interannual and longer timescales, the authors motivate the paradigm of a climate system that exhibits excitations of quasi-oscillatory eigenmodes with characteristic timescales and large-scale spatial patterns of coherence. It is assumed that any such modes are superposed on a spatially and temporally autocorrelated stochastic noise background. Under such a paradigm, a previously described (Mann and Park) multivariate frequency-domain approach is promoted as a particularly effective means of spatiotemporal signal identification and reconstruction, and an associated forecasting methodology is introduced. This combined signal detection/forecasting scheme exhibits significantly greater skill than conventional forecasting approaches in the context of a synthetic example consistent with the adopted paradigm. The example application demonstrates statistically significant skill at 5-10-yr lead times. Applications to operational long-range climatic forecasting are motivated and discussed.

Original languageEnglish (US)
Pages (from-to)58-74
Number of pages17
JournalWeather and Forecasting
Volume13
Issue number1
DOIs
StatePublished - Mar 1998

All Science Journal Classification (ASJC) codes

  • Atmospheric Science

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