A comparison of two methods for detecting abrupt changes in the variance of climatic time series
Two methods for detecting abrupt shifts in the variance, Integrated Cumulative Sum of Squares (ICSS) and Sequential Regime Shift Detector (SRSD), have been compared on both synthetic and observed time series. In Monte Carlo experiments, SRSD outperformed ICSS in the overwhelming majority of the mode...
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ftdatacite:10.48550/arxiv.1602.09082 2023-05-15T14:57:45+02:00 A comparison of two methods for detecting abrupt changes in the variance of climatic time series Rodionov, Sergei 2016 https://dx.doi.org/10.48550/arxiv.1602.09082 https://arxiv.org/abs/1602.09082 unknown arXiv https://dx.doi.org/10.5194/ascmo-2-63-2016 arXiv.org perpetual, non-exclusive license http://arxiv.org/licenses/nonexclusive-distrib/1.0/ Applications stat.AP Atmospheric and Oceanic Physics physics.ao-ph Methodology stat.ME FOS Computer and information sciences FOS Physical sciences article-journal Article ScholarlyArticle Text 2016 ftdatacite https://doi.org/10.48550/arxiv.1602.09082 https://doi.org/10.5194/ascmo-2-63-2016 2022-04-01T11:41:24Z Two methods for detecting abrupt shifts in the variance, Integrated Cumulative Sum of Squares (ICSS) and Sequential Regime Shift Detector (SRSD), have been compared on both synthetic and observed time series. In Monte Carlo experiments, SRSD outperformed ICSS in the overwhelming majority of the modelled scenarios with different sequences of variance regimes. The SRSD advantage was particularly apparent in the case of outliers in the series. When tested on climatic time series, in most cases both methods detected the same change points in the longer series (252-787 monthly values). The only exception was the Arctic Ocean SST series, when ICSS found one extra change point that appeared to be spurious. As for the shorter time series (66-136 yearly values), ICSS failed to detect any change points even when the variance doubled or tripled from one regime to another. For these time series, SRSD is recommended. Interestingly, all the climatic time series tested, from the Arctic to the Tropics, had one thing in common: the last shift detected in each of these series was toward a high-variance regime. This is consistent with other findings of increased climate variability in recent decades. : 32 pages, 11 figures Text Arctic Arctic Ocean DataCite Metadata Store (German National Library of Science and Technology) Arctic Arctic Ocean |
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DataCite Metadata Store (German National Library of Science and Technology) |
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Applications stat.AP Atmospheric and Oceanic Physics physics.ao-ph Methodology stat.ME FOS Computer and information sciences FOS Physical sciences |
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Applications stat.AP Atmospheric and Oceanic Physics physics.ao-ph Methodology stat.ME FOS Computer and information sciences FOS Physical sciences Rodionov, Sergei A comparison of two methods for detecting abrupt changes in the variance of climatic time series |
topic_facet |
Applications stat.AP Atmospheric and Oceanic Physics physics.ao-ph Methodology stat.ME FOS Computer and information sciences FOS Physical sciences |
description |
Two methods for detecting abrupt shifts in the variance, Integrated Cumulative Sum of Squares (ICSS) and Sequential Regime Shift Detector (SRSD), have been compared on both synthetic and observed time series. In Monte Carlo experiments, SRSD outperformed ICSS in the overwhelming majority of the modelled scenarios with different sequences of variance regimes. The SRSD advantage was particularly apparent in the case of outliers in the series. When tested on climatic time series, in most cases both methods detected the same change points in the longer series (252-787 monthly values). The only exception was the Arctic Ocean SST series, when ICSS found one extra change point that appeared to be spurious. As for the shorter time series (66-136 yearly values), ICSS failed to detect any change points even when the variance doubled or tripled from one regime to another. For these time series, SRSD is recommended. Interestingly, all the climatic time series tested, from the Arctic to the Tropics, had one thing in common: the last shift detected in each of these series was toward a high-variance regime. This is consistent with other findings of increased climate variability in recent decades. : 32 pages, 11 figures |
format |
Text |
author |
Rodionov, Sergei |
author_facet |
Rodionov, Sergei |
author_sort |
Rodionov, Sergei |
title |
A comparison of two methods for detecting abrupt changes in the variance of climatic time series |
title_short |
A comparison of two methods for detecting abrupt changes in the variance of climatic time series |
title_full |
A comparison of two methods for detecting abrupt changes in the variance of climatic time series |
title_fullStr |
A comparison of two methods for detecting abrupt changes in the variance of climatic time series |
title_full_unstemmed |
A comparison of two methods for detecting abrupt changes in the variance of climatic time series |
title_sort |
comparison of two methods for detecting abrupt changes in the variance of climatic time series |
publisher |
arXiv |
publishDate |
2016 |
url |
https://dx.doi.org/10.48550/arxiv.1602.09082 https://arxiv.org/abs/1602.09082 |
geographic |
Arctic Arctic Ocean |
geographic_facet |
Arctic Arctic Ocean |
genre |
Arctic Arctic Ocean |
genre_facet |
Arctic Arctic Ocean |
op_relation |
https://dx.doi.org/10.5194/ascmo-2-63-2016 |
op_rights |
arXiv.org perpetual, non-exclusive license http://arxiv.org/licenses/nonexclusive-distrib/1.0/ |
op_doi |
https://doi.org/10.48550/arxiv.1602.09082 https://doi.org/10.5194/ascmo-2-63-2016 |
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1766329880076615680 |