Multivariate linear parametric models applied to daily rainfall time series

Publikationstyp
Journal Article
Date Issued
2005-03-31
Sprache
English
Author(s)
Grimaldi, Salvatore  
Serinaldi, Francesco 
Tallerini, C.
TORE-URI
https://hdl.handle.net/11420/62316
Journal
Advances in geosciences  
Volume
2
Start Page
87
End Page
92
Citation
Advances in Geosciences 2: 87-92 (2005)
Publisher DOI
10.5194/adgeo-2-87-2005
Scopus ID
2-s2.0-33748084741
Publisher
European Geosciences Union
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.
DDC Class
551: Geology, Hydrology Meteorology