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| Titel |
Discriminating low frequency components from long range persistent fluctuations in daily atmospheric temperature variability |
| VerfasserIn |
M. Lanfredi, T. Simoniello, V. Cuomo, M. Macchiato |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 9, no. 14 ; Nr. 9, no. 14 (2009-07-15), S.4537-4544 |
| Datensatznummer |
250007500
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| Publikation (Nr.) |
 copernicus.org/acp-9-4537-2009.pdf |
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| Zusammenfassung |
| This study originated from recent results reported in literature, which
support the existence of long-range (power-law) persistence in atmospheric
temperature fluctuations on monthly and inter-annual scales. We investigated
the results of Detrended Fluctuation Analysis (DFA) carried out on
twenty-two historical daily time series recorded in Europe in order to
evaluate the reliability of such findings in depth. More detailed
inspections emphasized systematic deviations from power-law and high
statistical confidence for functional form misspecification. Rigorous
analyses did not support scale-free correlation as an operative concept for
Climate modelling, as instead suggested in literature. In order to
understand the physical implications of our results better, we designed a
bivariate Markov process, parameterised on the basis of the atmospheric
observational data by introducing a slow dummy variable. The time series
generated by this model, analysed both in time and frequency domains,
tallied with the real ones very well. They accounted for both the deceptive
scaling found in literature and the correlation details enhanced by our
analysis. Our results seem to evidence the presence of slow fluctuations
from another climatic sub-system such as ocean, which inflates temperature
variance up to several months. They advise more precise re-analyses of
temperature time series before suggesting dynamical paradigms useful for
Climate modelling and for the assessment of Climate Change. |
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