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www.adv-geosci.net/2/87/2005/
doi:10.5194/adgeo-2-87-2005
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Multivariate linear parametric models applied to daily rainfall time series
1Institute of Research for Hydrogeological Protection, CNR-IRPI, Perugia Italy
2Department of Hydraulics, Transportations and Highways, University of Rome “La Sapienza", Rome, Italy
Abstract. 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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Citation: Grimaldi, S., Serinaldi, F., and Tallerini, C.: Multivariate linear parametric models applied to daily rainfall time series, Adv. Geosci., 2, 87-92, doi:10.5194/adgeo-2-87-2005, 2005. Bibtex EndNote Reference Manager XML
