Modelling of monsoon rainfall for a mesoscale catchment in North-West India II: stochastic rainfall simulations

摘要

Within this study we present a robust method for generating precipitationtime series for the Anas catchment in North Western India. The method employsa multivariate stochastic simulation model that is driven by a time series ofobjectively classified circulation patterns (CPs). In a companion study (Zeheet al., 2006) it was already shown that CPs classified from the 500 or700 Hpa levels are suitable to explain space-time variability ofprecipitation in that area. The model is calibrated using observed rainfalltime series for the period 1985–1992 for two different CP time series, one fromthe 500 Hpa level and the over from the 700 Hpa level, and 200 realizationsof daily rainfall are simulated for the period 85–94. Simulations using theCPs from the 500 Hpa level as input yield a good match of the observedaverages and standard deviations of daily rainfall. They show furthermoregood performance at the monthly scale. When used with the 700 Hpa level CPsas inputs the model clearly underestimates the standard deviation andperforms much worse at the monthly scale, especially in the validation period93–94. The presented results give evidence that CPs from the 500 Hpa, levelin combination with a multivariate stochastic model, make up a suitable toolfor reducing the sparsity of precipitation data in developing regions withsparse hydro-meteorological data sets.