dc.contributor.author | Livina, VN | |
dc.contributor.author | Lohmann, G | |
dc.contributor.author | Mudelsee, M | |
dc.contributor.author | Lenton, Timothy M. | |
dc.date.accessioned | 2014-06-24T11:58:53Z | |
dc.date.issued | 2013-09-15 | |
dc.description.abstract | 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. | en_GB |
dc.description.sponsorship | NERC | en_GB |
dc.description.sponsorship | AXA Research Fund | en_GB |
dc.description.sponsorship | European Commission | en_GB |
dc.identifier.citation | Vol. 392, Issue 18, pp. 3891 - 3902 | en_GB |
dc.identifier.doi | 10.1016/j.physa.2013.04.036 | |
dc.identifier.grantnumber | NE/F005474/1 | en_GB |
dc.identifier.grantnumber | 289447 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/15093 | |
dc.language.iso | en | en_GB |
dc.publisher | Elsevier | en_GB |
dc.relation.url | http://www.sciencedirect.com/science/article/pii/S037843711300349X | en_GB |
dc.rights | This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-No Derivative Works License, which
permits non-commercial use, distribution, and reproduction in any medium, provided the original author and source are credited. | en_GB |
dc.subject | Potential forecasting | en_GB |
dc.subject | Potential analysis | en_GB |
dc.subject | Time series analysis | en_GB |
dc.title | Forecasting the underlying potential governing the time series of a dynamical system | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2014-06-24T11:58:53Z | |
dc.identifier.issn | 0378-4371 | |
dc.description | Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved. | en_GB |
dc.identifier.journal | Physica A: Statistical Mechanics and its Applications | en_GB |