 |
| Titel |
Markov chain analysis of regional climates |
| VerfasserIn |
S. Mieruch, S. Noël, H. Bovensmann, J. P. Burrows, J. A. Freund |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1023-5809
|
| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics ; 17, no. 6 ; Nr. 17, no. 6 (2010-11-19), S.651-661 |
| Datensatznummer |
250013755
|
| Publikation (Nr.) |
 copernicus.org/npg-17-651-2010.pdf |
|
|
|
|
|
| Zusammenfassung |
We present a novel method for regional climate classification that is based
on coarse-grained categorical representations of multivariate climate
anomalies and a subsequent Markov chain analysis. From the estimated
transition matrix several descriptors, such as persistence, recurrence
time and entropy, are derived. These descriptors characterise dynamic
properties of regional climate anomalies and are connected with fundamental
concepts from nonlinear physics like residence times, relaxation process and
predictability. Such characteristics are useful for a comparative analysis of
different climate regions and, in the context of global climate change, for a
regime shift analysis.
We apply the method to the bivariate set of water vapour and temperature
anomalies of two regional climates, the Iberian Peninsula and the islands of
Hawaii in the central Pacific Ocean. Through the Markov chain analysis and
via the derived descriptors we find significant differences between the two
climate regions. Since anomalies are departures from seasonal and long term
components, these differences relate to differences in the short term
stability of both regional climates. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|