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Titel |
Cyclic Markov chains with an application to an intermediate ENSO model |
VerfasserIn |
R. A. Pasmanter, A. Timmermann |
Medientyp |
Artikel
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Sprache |
Englisch
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ISSN |
1023-5809
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Digitales Dokument |
URL |
Erschienen |
In: Nonlinear Processes in Geophysics ; 10, no. 3 ; Nr. 10, no. 3, S.197-210 |
Datensatznummer |
250007990
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Publikation (Nr.) |
copernicus.org/npg-10-197-2003.pdf |
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Zusammenfassung |
We develop the
theory of cyclic Markov chains and apply it to the El Niño-Southern
Oscillation (ENSO) predictability problem. At the core of Markov chain
modelling is a partition of the state space such that the transition rates
between different state space cells can be computed and used most
efficiently. We apply a partition technique, which divides the state space
into multidimensional cells containing an equal number of data points.
This partition leads to mathematical properties of the transition matrices
which can be exploited further such as to establish connections with the
dynamical theory of unstable periodic orbits. We introduce the concept of
most and least predictable states. The data basis of our analysis consists
of a multicentury-long data set obtained from an intermediate coupled
atmosphere-ocean model of the tropical Pacific. This cyclostationary
Markov chain approach captures the spring barrier in ENSO predictability
and gives insight also into the dependence of ENSO predictability on the
climatic state. |
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