Abrupt transitions in time series with uncertainties

Identifying abrupt transitions is a key question in various disciplines. Existing transition detection methods, however, do not rigorously account for time series uncertainties, often neglecting them altogether or assuming them to be independent and qualitatively similar. Here, we introduce a novel...

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Main Authors: Goswami, B., Boers, N., Rheinwalt, A., Marwan, N., Heitzig, J., Breitenbach, S.F.M., Kurths, J.
Format: Article in Journal/Newspaper
Language:English
Published: London : Nature Publishing Group 2018
Subjects:
ice
510
Online Access:https://doi.org/10.34657/3747
https://oa.tib.eu/renate/handle/123456789/5118
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spelling ftleibnizopen:oai:oai.leibnizopen.de:-jiIYIgBdbrxVwz6hj2h 2023-06-11T04:14:43+02:00 Abrupt transitions in time series with uncertainties Goswami, B. Boers, N. Rheinwalt, A. Marwan, N. Heitzig, J. Breitenbach, S.F.M. Kurths, J. 2018 application/pdf https://doi.org/10.34657/3747 https://oa.tib.eu/renate/handle/123456789/5118 eng eng London : Nature Publishing Group CC BY 4.0 Unported https://creativecommons.org/licenses/by/4.0/ Nature Communications 9 (2018), Nr. 1 ice detection method El Nino-Southern Oscillation Holocene ice rafting identification method network analysis Pacific Decadal Oscillation probability density function summer time series uncertainty analysis Article Asian climate community structure El Nino human time series analysis transition temperature uncertainty Atlantic Ocean Atlantic Ocean (North) 510 article Text 2018 ftleibnizopen https://doi.org/10.34657/3747 2023-05-28T23:36:23Z Identifying abrupt transitions is a key question in various disciplines. Existing transition detection methods, however, do not rigorously account for time series uncertainties, often neglecting them altogether or assuming them to be independent and qualitatively similar. Here, we introduce a novel approach suited to handle uncertainties by representing the time series as a time-ordered sequence of probability density functions. We show how to detect abrupt transitions in such a sequence using the community structure of networks representing probabilities of recurrence. Using our approach, we detect transitions in global stock indices related to well-known periods of politico-economic volatility. We further uncover transitions in the El Niño-Southern Oscillation which coincide with periods of phase locking with the Pacific Decadal Oscillation. Finally, we provide for the first time an 'uncertainty-aware' framework which validates the hypothesis that ice-rafting events in the North Atlantic during the Holocene were synchronous with a weakened Asian summer monsoon. publishedVersion Article in Journal/Newspaper North Atlantic LeibnizOpen (The Leibniz Association) Pacific
institution Open Polar
collection LeibnizOpen (The Leibniz Association)
op_collection_id ftleibnizopen
language English
topic ice
detection method
El Nino-Southern Oscillation
Holocene
ice rafting
identification method
network analysis
Pacific Decadal Oscillation
probability density function
summer
time series
uncertainty analysis
Article
Asian
climate
community structure
El Nino
human
time series analysis
transition temperature
uncertainty
Atlantic Ocean
Atlantic Ocean (North)
510
spellingShingle ice
detection method
El Nino-Southern Oscillation
Holocene
ice rafting
identification method
network analysis
Pacific Decadal Oscillation
probability density function
summer
time series
uncertainty analysis
Article
Asian
climate
community structure
El Nino
human
time series analysis
transition temperature
uncertainty
Atlantic Ocean
Atlantic Ocean (North)
510
Goswami, B.
Boers, N.
Rheinwalt, A.
Marwan, N.
Heitzig, J.
Breitenbach, S.F.M.
Kurths, J.
Abrupt transitions in time series with uncertainties
topic_facet ice
detection method
El Nino-Southern Oscillation
Holocene
ice rafting
identification method
network analysis
Pacific Decadal Oscillation
probability density function
summer
time series
uncertainty analysis
Article
Asian
climate
community structure
El Nino
human
time series analysis
transition temperature
uncertainty
Atlantic Ocean
Atlantic Ocean (North)
510
description Identifying abrupt transitions is a key question in various disciplines. Existing transition detection methods, however, do not rigorously account for time series uncertainties, often neglecting them altogether or assuming them to be independent and qualitatively similar. Here, we introduce a novel approach suited to handle uncertainties by representing the time series as a time-ordered sequence of probability density functions. We show how to detect abrupt transitions in such a sequence using the community structure of networks representing probabilities of recurrence. Using our approach, we detect transitions in global stock indices related to well-known periods of politico-economic volatility. We further uncover transitions in the El Niño-Southern Oscillation which coincide with periods of phase locking with the Pacific Decadal Oscillation. Finally, we provide for the first time an 'uncertainty-aware' framework which validates the hypothesis that ice-rafting events in the North Atlantic during the Holocene were synchronous with a weakened Asian summer monsoon. publishedVersion
format Article in Journal/Newspaper
author Goswami, B.
Boers, N.
Rheinwalt, A.
Marwan, N.
Heitzig, J.
Breitenbach, S.F.M.
Kurths, J.
author_facet Goswami, B.
Boers, N.
Rheinwalt, A.
Marwan, N.
Heitzig, J.
Breitenbach, S.F.M.
Kurths, J.
author_sort Goswami, B.
title Abrupt transitions in time series with uncertainties
title_short Abrupt transitions in time series with uncertainties
title_full Abrupt transitions in time series with uncertainties
title_fullStr Abrupt transitions in time series with uncertainties
title_full_unstemmed Abrupt transitions in time series with uncertainties
title_sort abrupt transitions in time series with uncertainties
publisher London : Nature Publishing Group
publishDate 2018
url https://doi.org/10.34657/3747
https://oa.tib.eu/renate/handle/123456789/5118
geographic Pacific
geographic_facet Pacific
genre North Atlantic
genre_facet North Atlantic
op_source Nature Communications 9 (2018), Nr. 1
op_rights CC BY 4.0 Unported
https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.34657/3747
_version_ 1768370972422832128