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| Titel |
Multivariate linear parametric models applied to daily rainfall time series |
| VerfasserIn |
S. Grimaldi, F. Serinaldi, C. Tallerini |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7340
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| Digitales Dokument |
URL |
| Erschienen |
In: 6th Plinius Conference on Mediterranean Storms (2004) ; Nr. 2 (2005-03-31), S.87-92 |
| Datensatznummer |
250000301
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| Publikation (Nr.) |
 copernicus.org/adgeo-2-87-2005.pdf |
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| Zusammenfassung |
| The aim of this paper is to test the Multivariate Linear Parametric Models
applied to daily rainfall series. These simple models allow to generate
synthetic series preserving both the time correlation (autocorrelation) and
the space correlation (crosscorrelation). To have synthetic daily series, in
such a way realistic and usable, it is necessary the application of a
corrective procedure, removing negative values and enforcing the no-rain
probability. The following study compares some linear models each other and
points out the roles of autoregressive (AR) and moving average (MA)
components as well as parameter orders and mixed parameters. |
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