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The aim of this paper is to test the Multivariate Linear Parametric Modelsapplied to daily rainfall series. These simple models allow to generatesynthetic series preserving both the time correlation (autocorrelation) andthe space correlation (crosscorrelation). To have synthetic daily series, insuch a way realistic and usable, it is necessary the application of acorrective procedure, removing negative values and enforcing the no-rainprobability. The following study compares some linear models each other andpoints out the roles of autoregressive (AR) and moving average (MA)components as well as parameter orders and mixed parameters

Multivariate linear parametric models applied to daily rainfall time series