Sampling rate-corrected analysis of irregularly sampled time series

Braun, Tobias, Fernandez, Cinthya N., Eroglu, Deniz, Hartland, Adam, Breitenbach, Sebastian and Marwan, Norbert (2022) Sampling rate-corrected analysis of irregularly sampled time series. Physical Review E, 105 (2). 024206. ISSN 2470-0045

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Official URL: https://doi.org/10.1103/PhysRevE.105.024206

Abstract

The analysis of irregularly sampled time series remains a challenging task requiring methods that account for continuous and abrupt changes of sampling resolution without introducing additional biases. The edit distance is an effective metric to quantitatively compare time series segments of unequal length by computing the cost of transforming one segment into the other. We show that transformation costs generally exhibit a nontrivial relationship with local sampling rate. If the sampling resolution undergoes strong variations, this effect impedes unbiased comparison between different time episodes. We study the impact of this effect on recurrence quantification analysis, a framework that is well suited for identifying regime shifts in nonlinear time series. A constrained randomization approach is put forward to correct for the biased recurrence quantification measures. This strategy involves the generation of a type of time series and time axis surrogates which we call sampling-rate-constrained (SRC) surrogates. We demonstrate the effectiveness of the proposed approach with a synthetic example and an irregularly sampled speleothem proxy record from Niue island in the central tropical Pacific. Application of the proposed correction scheme identifies a spurious transition that is solely imposed by an abrupt shift in sampling rate and uncovers periods of reduced seasonal rainfall predictability associated with enhanced El Niño-Southern Oscillation and tropical cyclone activity.

Item Type: Article
Additional Information: Funding information: This research was supported by the Deutsche Forschungsgemeinschaft in the context of the DFG Project No. MA4759/11-1 “Nonlinear empirical mode analysis of complex systems: Development of general approach and application in climate.” It also received financial support from the European Union's Horizon 2020 Research and Innovation program (Marie Sklodowska-Curie Grant Agreement No. 691037). D.E. acknowledges funding by TÜBİTAK (Grant No. 118C236) and the BAGEP Award of the Science Academy. C.N.F. acknowledges financial support from the German Academic Exchange Service (DAAD). A.H. acknowledges support from the Royal Society of New Zealand (Grant No. RIS-UOW1501), and the Rutherford Discovery Fellowship program (Grant No. RDF-UOW1601). The authors declare that they have no conflict of interest.
Subjects: F800 Physical and Terrestrial Geographical and Environmental Sciences
Department: Faculties > Engineering and Environment > Geography and Environmental Sciences
Depositing User: John Coen
Date Deposited: 18 Mar 2022 08:37
Last Modified: 31 Mar 2022 13:45
URI: http://nrl.northumbria.ac.uk/id/eprint/48691

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