Broken symmetry and long-term forecasting
(2007) In Journal of Geophysical Research 112(D24).- Abstract
- [1] This paper takes a novel approach to a known basic difficulty with computer simulations of nonlinear dynamical systems relevant to climate modeling. Specifically, we show by minimal examples how small systematic modeling errors might survive averaging over an ensemble of initial conditions. The resulting predictive errors can grow slowly enough initially that they may be overlooked without contradicting known behaviors on middle scales. However, they may nonetheless be significant on long timescales, given our current knowledge. Mathematical symmetry, which has been investigated for improving accuracy in computational algorithms, turns out to provide a novel perspective to this issue.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/966277
- author
- Essex, Christopher ; Ilie, Silvana LU and Corless, Robert M.
- organization
- publishing date
- 2007
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Journal of Geophysical Research
- volume
- 112
- issue
- D24
- publisher
- Wiley-Blackwell
- external identifiers
-
- wos:000251526100001
- scopus:49249136884
- ISSN
- 2156-2202
- DOI
- 10.1029/2007JD008563
- language
- English
- LU publication?
- yes
- additional info
- The information about affiliations in this record was updated in December 2015. The record was previously connected to the following departments: Numerical Analysis (011015004)
- id
- 88199c48-7859-4e4e-8a44-7ed1c6a781a1 (old id 966277)
- alternative location
- http://www.agu.org/pubs/crossref/2007/2007JD008563.shtml
- date added to LUP
- 2016-04-01 12:08:12
- date last changed
- 2022-03-28 20:45:39
@article{88199c48-7859-4e4e-8a44-7ed1c6a781a1,
abstract = {{[1] This paper takes a novel approach to a known basic difficulty with computer simulations of nonlinear dynamical systems relevant to climate modeling. Specifically, we show by minimal examples how small systematic modeling errors might survive averaging over an ensemble of initial conditions. The resulting predictive errors can grow slowly enough initially that they may be overlooked without contradicting known behaviors on middle scales. However, they may nonetheless be significant on long timescales, given our current knowledge. Mathematical symmetry, which has been investigated for improving accuracy in computational algorithms, turns out to provide a novel perspective to this issue.}},
author = {{Essex, Christopher and Ilie, Silvana and Corless, Robert M.}},
issn = {{2156-2202}},
language = {{eng}},
number = {{D24}},
publisher = {{Wiley-Blackwell}},
series = {{Journal of Geophysical Research}},
title = {{Broken symmetry and long-term forecasting}},
url = {{http://dx.doi.org/10.1029/2007JD008563}},
doi = {{10.1029/2007JD008563}},
volume = {{112}},
year = {{2007}},
}