Sampling Rate-Corrected Analysis of Irregularly Sampled Time Series

dc.authorid Eroglu, Deniz/0000-0001-6725-6949
dc.authorid Marwan, Norbert/0000-0003-1437-7039
dc.authorid Braun, Tobias/0000-0002-3095-8960
dc.authorid Breitenbach, Sebastian/0000-0001-9615-2065
dc.authorwosid Eroglu, Deniz/GVS-9233-2022
dc.authorwosid Marwan, Norbert/D-9576-2011
dc.authorwosid Fernandez, Cinthya/IXN-1160-2023
dc.contributor.author Braun, Tobias
dc.contributor.author Eroğlu, Deniz
dc.contributor.author Fernandez, Cinthya N.
dc.contributor.author Eroglu, Deniz
dc.contributor.author Hartland, Adam
dc.contributor.author Breitenbach, Sebastian F. M.
dc.contributor.author Marwan, Norbert
dc.contributor.other Molecular Biology and Genetics
dc.date.accessioned 2023-10-19T15:11:33Z
dc.date.available 2023-10-19T15:11:33Z
dc.date.issued 2022
dc.department-temp [Braun, Tobias; Marwan, Norbert] Leibniz Assoc, Potsdam Inst Climate Impact Res PIK, D-14473 Potsdam, Germany; [Fernandez, Cinthya N.] Ruhr Univ Bochum, Inst Geol Mineral & Geophys, D-44801 Bochum, Germany; [Eroglu, Deniz] Kadir Has Univ, Fac Engn & Nat Sci, TR-34083 Istanbul, Turkey; [Hartland, Adam] Univ Waikato, Sch Sci, Environm Res Inst, Hamilton 3240, Waikato, New Zealand; [Breitenbach, Sebastian F. M.] Northumbria Univ, Dept Geog & Environm Sci, Newcastle Upon Tyne NE1 8ST, Tyne & Wear, England; [Marwan, Norbert] Univ Potsdam, Inst Geosci, D-14473 Potsdam, Germany en_US
dc.description.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 Nino-Southern Oscillation and tropical cyclone activity. en_US
dc.description.sponsorship Deutsche Forschungsgemeinschaft [MA4759/11-1]; Nonlinear empirical mode analysis of complex systems; European Union [691037]; TUB.ITAK [118C236]; BAGEP Award of the Science Academy; German Academic Exchange Service (DAAD); Royal Society of New Zealand [RIS-UOW1501]; Rutherford Discovery Fellowship program [RDF-UOW1601]; Marie Curie Actions (MSCA) [691037] Funding Source: Marie Curie Actions (MSCA) en_US
dc.description.sponsorship 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 TUB.ITAK (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. en_US
dc.identifier.citationcount 6
dc.identifier.doi 10.1103/PhysRevE.105.024206 en_US
dc.identifier.issn 2470-0045
dc.identifier.issn 2470-0053
dc.identifier.issue 2 en_US
dc.identifier.pmid 35291153 en_US
dc.identifier.scopus 2-s2.0-85125576290 en_US
dc.identifier.scopusquality Q1
dc.identifier.uri https://doi.org/10.1103/PhysRevE.105.024206
dc.identifier.uri https://hdl.handle.net/20.500.12469/5074
dc.identifier.volume 105 en_US
dc.identifier.wos WOS:000766300100009 en_US
dc.identifier.wosquality Q1
dc.khas 20231019-WoS en_US
dc.language.iso en en_US
dc.publisher Amer Physical Soc en_US
dc.relation.ispartof Physical Review E en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.scopus.citedbyCount 7
dc.subject Recurrence Plots En_Us
dc.subject Spectral-Analysis En_Us
dc.subject Algorithms En_Us
dc.subject Statistics En_Us
dc.subject Estimators En_Us
dc.subject Climate En_Us
dc.subject Recurrence Plots
dc.subject Spectral-Analysis
dc.subject Algorithms
dc.subject Statistics
dc.subject Estimators
dc.subject Climate
dc.title Sampling Rate-Corrected Analysis of Irregularly Sampled Time Series en_US
dc.type Article en_US
dc.wos.citedbyCount 6
dspace.entity.type Publication
relation.isAuthorOfPublication 5bae555f-a8aa-4b95-bcfe-54cc47812e13
relation.isAuthorOfPublication.latestForDiscovery 5bae555f-a8aa-4b95-bcfe-54cc47812e13
relation.isOrgUnitOfPublication 71ce8622-7449-4a6a-8fad-44d881416546
relation.isOrgUnitOfPublication.latestForDiscovery 71ce8622-7449-4a6a-8fad-44d881416546

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