Regime Change Detection in Irregularly Sampled Time Series

Norbert Marwan, Deniz Eroglu, Ibrahim Ozken, Thomas Stemler, Karl-Heinz Wyrwoll, Jürgen Kurths

Research output: Chapter in Book/Conference paperChapter

Abstract

Irregular sampling is a common problem in palaeoclimate studies. We propose a method that provides regularly sampled time series and at the same time a difference filtering of the data. The differences between successive time instances are derived by a transformation costs procedure. A subsequent recurrence analysis is used to investigate regime transitions. This approach is applied on speleothem-based palaeoclimate proxy data from the Indonesian--Australian monsoon region. We can clearly identify Heinrich events in the palaeoclimate as characteristic changes in dynamics.
Original languageEnglish
Title of host publicationAdvances in Nonlinear Geosciences
EditorsAnastasios A. Tsonis
Place of PublicationCham
PublisherSpringer
Pages357-368
Number of pages12
ISBN (Print)978-3-319-58895-7
DOIs
Publication statusPublished - 2018

Fingerprint

Dive into the research topics of 'Regime Change Detection in Irregularly Sampled Time Series'. Together they form a unique fingerprint.

Cite this