Forecasting the underlying potential governing the time series of a dynamical system
We introduce a technique of time series analysis, potential forecasting, which is based on dynamical propagation of the probability density of time series. We employ polynomial coefficients of the orthogonal approximation of the empirical probability distribution and extrapolate them in order to for...
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ftawi:oai:epic.awi.de:33300 2023-05-15T15:01:28+02:00 Forecasting the underlying potential governing the time series of a dynamical system Livina, Valerie Lohmann, Gerrit Mudelsee, Manfred Lenton, T. M. 2013-09-15 https://epic.awi.de/id/eprint/33300/ http://www.sciencedirect.com/science/article/pii/S037843711300349X https://hdl.handle.net/10013/epic.41767 unknown ELSEVIER SCIENCE BV Livina, V. , Lohmann, G. orcid:0000-0003-2089-733X , Mudelsee, M. orcid:0000-0002-2364-9561 and Lenton, T. M. (2013) Forecasting the underlying potential governing the time series of a dynamical system , Physica A-Statistical Mechanics and Its Applications, 392 , pp. 3891-3902 . hdl:10013/epic.41767 EPIC3Physica A-Statistical Mechanics and Its Applications, ELSEVIER SCIENCE BV, 392, pp. 3891-3902, ISSN: 0378-4371 Article isiRev 2013 ftawi 2021-12-24T15:38:45Z We introduce a technique of time series analysis, potential forecasting, which is based on dynamical propagation of the probability density of time series. We employ polynomial coefficients of the orthogonal approximation of the empirical probability distribution and extrapolate them in order to forecast the future probability distribution of data. The method is tested on artificial data, used for hindcasting observed climate data, and then applied to forecast Arctic sea-ice time series. The proposed methodology completes a framework for ‘potential analysis’ of tipping points which altogether serves anticipating, detecting and forecasting nonlinear changes including bifurcations using several independent techniques of time series analysis. Although being applied to climatological series in the present paper, the method is very general and can be used to forecast dynamics in time series of any origin. Article in Journal/Newspaper Arctic Sea ice Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) Arctic |
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Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) |
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ftawi |
language |
unknown |
description |
We introduce a technique of time series analysis, potential forecasting, which is based on dynamical propagation of the probability density of time series. We employ polynomial coefficients of the orthogonal approximation of the empirical probability distribution and extrapolate them in order to forecast the future probability distribution of data. The method is tested on artificial data, used for hindcasting observed climate data, and then applied to forecast Arctic sea-ice time series. The proposed methodology completes a framework for ‘potential analysis’ of tipping points which altogether serves anticipating, detecting and forecasting nonlinear changes including bifurcations using several independent techniques of time series analysis. Although being applied to climatological series in the present paper, the method is very general and can be used to forecast dynamics in time series of any origin. |
format |
Article in Journal/Newspaper |
author |
Livina, Valerie Lohmann, Gerrit Mudelsee, Manfred Lenton, T. M. |
spellingShingle |
Livina, Valerie Lohmann, Gerrit Mudelsee, Manfred Lenton, T. M. Forecasting the underlying potential governing the time series of a dynamical system |
author_facet |
Livina, Valerie Lohmann, Gerrit Mudelsee, Manfred Lenton, T. M. |
author_sort |
Livina, Valerie |
title |
Forecasting the underlying potential governing the time series of a dynamical system |
title_short |
Forecasting the underlying potential governing the time series of a dynamical system |
title_full |
Forecasting the underlying potential governing the time series of a dynamical system |
title_fullStr |
Forecasting the underlying potential governing the time series of a dynamical system |
title_full_unstemmed |
Forecasting the underlying potential governing the time series of a dynamical system |
title_sort |
forecasting the underlying potential governing the time series of a dynamical system |
publisher |
ELSEVIER SCIENCE BV |
publishDate |
2013 |
url |
https://epic.awi.de/id/eprint/33300/ http://www.sciencedirect.com/science/article/pii/S037843711300349X https://hdl.handle.net/10013/epic.41767 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Sea ice |
genre_facet |
Arctic Sea ice |
op_source |
EPIC3Physica A-Statistical Mechanics and Its Applications, ELSEVIER SCIENCE BV, 392, pp. 3891-3902, ISSN: 0378-4371 |
op_relation |
Livina, V. , Lohmann, G. orcid:0000-0003-2089-733X , Mudelsee, M. orcid:0000-0002-2364-9561 and Lenton, T. M. (2013) Forecasting the underlying potential governing the time series of a dynamical system , Physica A-Statistical Mechanics and Its Applications, 392 , pp. 3891-3902 . hdl:10013/epic.41767 |
_version_ |
1766333497025232896 |