Growth of finite errors in ensemble prediction

We study the predictability of chaotic conservative and dissipative maps in the context of ensemble prediction. Finite-size perturbations around a reference trajectory are evolved under the full nonlinear system dynamics; this evolution is characterized by error growth factors and investigated as a...

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Main Authors: M. Harle, F. Kwasniok, U. Feudel
Format: Article
Language:English
Published: Copernicus Publications 2006-01-01
Series:Nonlinear Processes in Geophysics
Online Access:http://www.nonlin-processes-geophys.net/13/167/2006/npg-13-167-2006.pdf
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spelling doaj-1d73a0dea7e14812998a8ce4f31284c52020-11-24T22:36:07ZengCopernicus PublicationsNonlinear Processes in Geophysics1023-58091607-79462006-01-01132167176Growth of finite errors in ensemble predictionM. HarleF. KwasniokU. FeudelWe study the predictability of chaotic conservative and dissipative maps in the context of ensemble prediction. Finite-size perturbations around a reference trajectory are evolved under the full nonlinear system dynamics; this evolution is characterized by error growth factors and investigated as a function of prediction time and initial perturbation size. The distribution of perturbation growth is studied. We then focus on the worst-case predictability, i.e., the maximum error growth over all initial conditions. The estimate of the worst-case predictability obtained from the ensemble approach is compared to the estimate given by the largest singular value of the linearized system dynamics. For small prediction times, the worst-case error growth obtained from the nonlinear ensemble approach is exponential with prediction time; for large prediction times, a power-law dependence is observed the scaling exponent of which depends systematically on the initial error size. The question is addressed of how large an ensemble is necessary to reliably estimate the maximum error growth factor. A power-law dependence of the error in the estimate of the growth factor on the ensemble size is established empirically. Our results are valid for several markedly different chaotic conservative and dissipative systems, perhaps pointing to quite general features.http://www.nonlin-processes-geophys.net/13/167/2006/npg-13-167-2006.pdf
collection DOAJ
language English
format Article
sources DOAJ
author M. Harle
F. Kwasniok
U. Feudel
spellingShingle M. Harle
F. Kwasniok
U. Feudel
Growth of finite errors in ensemble prediction
Nonlinear Processes in Geophysics
author_facet M. Harle
F. Kwasniok
U. Feudel
author_sort M. Harle
title Growth of finite errors in ensemble prediction
title_short Growth of finite errors in ensemble prediction
title_full Growth of finite errors in ensemble prediction
title_fullStr Growth of finite errors in ensemble prediction
title_full_unstemmed Growth of finite errors in ensemble prediction
title_sort growth of finite errors in ensemble prediction
publisher Copernicus Publications
series Nonlinear Processes in Geophysics
issn 1023-5809
1607-7946
publishDate 2006-01-01
description We study the predictability of chaotic conservative and dissipative maps in the context of ensemble prediction. Finite-size perturbations around a reference trajectory are evolved under the full nonlinear system dynamics; this evolution is characterized by error growth factors and investigated as a function of prediction time and initial perturbation size. The distribution of perturbation growth is studied. We then focus on the worst-case predictability, i.e., the maximum error growth over all initial conditions. The estimate of the worst-case predictability obtained from the ensemble approach is compared to the estimate given by the largest singular value of the linearized system dynamics. For small prediction times, the worst-case error growth obtained from the nonlinear ensemble approach is exponential with prediction time; for large prediction times, a power-law dependence is observed the scaling exponent of which depends systematically on the initial error size. The question is addressed of how large an ensemble is necessary to reliably estimate the maximum error growth factor. A power-law dependence of the error in the estimate of the growth factor on the ensemble size is established empirically. Our results are valid for several markedly different chaotic conservative and dissipative systems, perhaps pointing to quite general features.
url http://www.nonlin-processes-geophys.net/13/167/2006/npg-13-167-2006.pdf
work_keys_str_mv AT mharle growthoffiniteerrorsinensembleprediction
AT fkwasniok growthoffiniteerrorsinensembleprediction
AT ufeudel growthoffiniteerrorsinensembleprediction
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