Articles | Volume 2
Adv. Geosci., 2, 87–92, 2005
https://doi.org/10.5194/adgeo-2-87-2005
Adv. Geosci., 2, 87–92, 2005
https://doi.org/10.5194/adgeo-2-87-2005

  31 Mar 2005

31 Mar 2005

Multivariate linear parametric models applied to daily rainfall time series

S. Grimaldi1, F. Serinaldi2, and C. Tallerini2 S. Grimaldi et al.
  • 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.