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

Within this study we present a robust method for generating precipitation time series for the Anas catchment in North Western India. The method employs a multivariate stochastic simulation model that is driven by a time series of objectively classified circulation patterns (CPs). In a companion stud...

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Main Authors: E. Zehe, A. K. Singh, A. Bárdossy
Format: Article
Language:English
Published: Copernicus Publications 2006-01-01
Series:Hydrology and Earth System Sciences
Online Access:http://www.hydrol-earth-syst-sci.net/10/807/2006/hess-10-807-2006.pdf
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spelling doaj-c9d0e887448a4c9b9147002b868ebda82020-11-24T23:48:30ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382006-01-01106807815Modelling of monsoon rainfall for a mesoscale catchment in North-West India II: stochastic rainfall simulationsE. ZeheA. K. SinghA. BárdossyWithin this study we present a robust method for generating precipitation time series for the Anas catchment in North Western India. The method employs a multivariate stochastic simulation model that is driven by a time series of objectively classified circulation patterns (CPs). In a companion study (Zehe et al., 2006) it was already shown that CPs classified from the 500 or 700 Hpa levels are suitable to explain space-time variability of precipitation in that area. The model is calibrated using observed rainfall time series for the period 1985–1992 for two different CP time series, one from the 500 Hpa level and the over from the 700 Hpa level, and 200 realizations of daily rainfall are simulated for the period 85–94. Simulations using the CPs from the 500 Hpa level as input yield a good match of the observed averages and standard deviations of daily rainfall. They show furthermore good performance at the monthly scale. When used with the 700 Hpa level CPs as inputs the model clearly underestimates the standard deviation and performs much worse at the monthly scale, especially in the validation period 93–94. The presented results give evidence that CPs from the 500 Hpa, level in combination with a multivariate stochastic model, make up a suitable tool for reducing the sparsity of precipitation data in developing regions with sparse hydro-meteorological data sets.http://www.hydrol-earth-syst-sci.net/10/807/2006/hess-10-807-2006.pdf
collection DOAJ
language English
format Article
sources DOAJ
author E. Zehe
A. K. Singh
A. Bárdossy
spellingShingle E. Zehe
A. K. Singh
A. Bárdossy
Modelling of monsoon rainfall for a mesoscale catchment in North-West India II: stochastic rainfall simulations
Hydrology and Earth System Sciences
author_facet E. Zehe
A. K. Singh
A. Bárdossy
author_sort E. Zehe
title Modelling of monsoon rainfall for a mesoscale catchment in North-West India II: stochastic rainfall simulations
title_short Modelling of monsoon rainfall for a mesoscale catchment in North-West India II: stochastic rainfall simulations
title_full Modelling of monsoon rainfall for a mesoscale catchment in North-West India II: stochastic rainfall simulations
title_fullStr Modelling of monsoon rainfall for a mesoscale catchment in North-West India II: stochastic rainfall simulations
title_full_unstemmed Modelling of monsoon rainfall for a mesoscale catchment in North-West India II: stochastic rainfall simulations
title_sort modelling of monsoon rainfall for a mesoscale catchment in north-west india ii: stochastic rainfall simulations
publisher Copernicus Publications
series Hydrology and Earth System Sciences
issn 1027-5606
1607-7938
publishDate 2006-01-01
description Within this study we present a robust method for generating precipitation time series for the Anas catchment in North Western India. The method employs a multivariate stochastic simulation model that is driven by a time series of objectively classified circulation patterns (CPs). In a companion study (Zehe et al., 2006) it was already shown that CPs classified from the 500 or 700 Hpa levels are suitable to explain space-time variability of precipitation in that area. The model is calibrated using observed rainfall time series for the period 1985–1992 for two different CP time series, one from the 500 Hpa level and the over from the 700 Hpa level, and 200 realizations of daily rainfall are simulated for the period 85–94. Simulations using the CPs from the 500 Hpa level as input yield a good match of the observed averages and standard deviations of daily rainfall. They show furthermore good performance at the monthly scale. When used with the 700 Hpa level CPs as inputs the model clearly underestimates the standard deviation and performs much worse at the monthly scale, especially in the validation period 93–94. The presented results give evidence that CPs from the 500 Hpa, level in combination with a multivariate stochastic model, make up a suitable tool for reducing the sparsity of precipitation data in developing regions with sparse hydro-meteorological data sets.
url http://www.hydrol-earth-syst-sci.net/10/807/2006/hess-10-807-2006.pdf
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AT abardossy modellingofmonsoonrainfallforamesoscalecatchmentinnorthwestindiaiistochasticrainfallsimulations
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