HR: 1330h
AN: H43A-05    [Abstracts]
TI: Simulation of Precipitation at Multiple Stations Using a Multivariate Autoregressive Model With Censored Normal Marginals
AU: * Gautam, N
EM: umgauta1@cc.umanitoba.ca
AF: University of Manitoba, Dept. of Civil Engineering, Winnipeg, MB R3T 5V6 Canada
AU: Rasmussen, P F
EM: rasmusse@cc.umanitoba.ca
AF: University of Manitoba, Dept. of Civil Engineering, Winnipeg, MB R3T 5V6 Canada
AB: Stochastic weather generators are frequently used in climate change studies to simulate input to hydrologic models. In this presentation, we focus on the particular problem of simulating daily precipitation at multiple stations in a region for which records are available. Daily precipitation is a highly intermittent process, highly variable in space, and typically has a highly skewed distribution. A stochastic precipitation model should ideally preserve the regional pattern of intermittence, the autocorrelation, the cross-correlation, and the marginal distributions of observed precipitation. For this purpose, we employed a multivariate autoregressive model. Below zero-values were considered days with no rain. To preserve the marginal distributions of observed precipitation at different stations some prior transformation of data was required. The presentation will describe the experience gained from applying the model to precipitation records in Canada. Focus will be on analytical model properties, methods of parameter estimation, and the preservation of observed statistics in the application.
DE: 1833 Hydroclimatology
DE: 1860 Runoff and streamflow
DE: 1869 Stochastic processes
SC: Hydrology [H]
MN: 2005 Joint Assembly