Simulation of multisite precipitation using an extended chain-dependent process

Abstract

The chain-dependent process is a popular stochastic model for precipitation sequence data. In this paper, the effect of daily regional precipitation occurrence is incorporated into the stochastic model. This model is applied to analyze the daily precipitation at a small number of sites in the upper Waitaki catchment, New Zealand. In this case study, the probability distributions of daily precipitation occurrence and intensity, spatial dependences, and the relation between precipitation and atmospheric forcings are simulated quite well. Specifically, some behaviors which are not well modeled by existing models, such as the extremal behavior of daily precipitation intensity, the lag 1 cross correlation of daily precipitation occurrence, spatial intermittency, and spatial correlation of seasonal precipitation totals, are significantly improved. Moreover, a new and simpler approach is proposed which successfully eliminates overdispersion, i.e., underestimation of the variance of seasonal precipitation totals. Copyright 2010 by the American Geophysical Union.