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| Titel |
A reexamination of methods for evaluating the predictability of the atmosphere |
| VerfasserIn |
J. L. Anderson, V. Hubeny |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1023-5809
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics ; 4, no. 3 ; Nr. 4, no. 3, S.157-166 |
| Datensatznummer |
250001683
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| Publikation (Nr.) |
 copernicus.org/npg-4-157-1997.pdf |
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| Zusammenfassung |
Pioneering work by Lorenz (1965, 1968, 1969) developed a number of
methods for exploring the limits of predictability of the atmosphere. One method uses an
integration of a realistic numerical model as a surrogate for the atmosphere. The
evolution of small perturbations to the integration are used to estimate how quickly
errors resulting from a given observational error distribution would grow in this perfect
model context.
In reality, an additional constraint must be applied to this
predictability problem. In the real atmosphere, only states that belong to the
atmosphere's climate occur and one is only interested in how such realizable states
diverge in time. Similarly, in a perfect model study, only states on the model's attractor
occur. However, a prescribed observational error distribution may project on states that
are off the attractor, resulting in unrepresentative error growth. The 'correct' error
growth problem examines growth for the projection of the observational error distribution
onto the model's attractor.
Simple dynamical systems are used to demonstrate that this additional
constraint is vital in order to correctly assess the rate of error growth. A naive
approach in which this information about the model's 'climate' is not used can lead to
significant errors. Depending on the dynamical system, error doubling times may be either
underestimated or overestimated although the latter seems more likely for more realistic
models. While the magnitude of these errors is not large in the simple dynamical systems
examined, the impact could be much larger in more realistic forecast models. |
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