Physical disaggregation of numerical model rainfall
نویسندگان
چکیده
منابع مشابه
Generating synthetic rainfall using a disaggregation model
Synthetic rainfall data has a large number of uses. Specifically, the behaviour of a reservoir under most scenarios can be best understood when evaluated using a large number of synthetic inputs. These synthetic values are all equally probable to occur but many of them may not have appeared in the historical record. Stochastic weather generators produce these synthetic data that were statistica...
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Use of output from global Circulation Models (GCMs) by regional or small scale rainfall-runoff models necessitates the disaggregation of the hydrological information available from GCMs to smaller scales. The hydrological processes of interest commonly occur at much smaller scales than those being modelled by GCMs. The present work examines the disaggregation of areally averaged monthly rainfal...
متن کاملA stochastic spatial-temporal disaggregation model for rainfall
A stochastic model for disaggregating spatial-temporal rainfall data is presented. In the model, the starting times of rain cells occur in a Poisson process, where each cell has a random duration and a random intensity. In space, rain cells have centres that are distributed according to a two dimensional Poisson process and have radii that follow an exponential distribution. The model is fitted...
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Stochastic weather generators are useful for producing daily sequences that reproduce climatic statistics aggregated to, e.g., a monthly time scale, for use with biological simulation models. This paper describes a stochastic weather generator that disaggregates monthly rainfall by adjusting input parameters or by constraining output to match target rainfall totals, and demonstrates its use wit...
متن کاملUsing Probable Maximum Precipitation to Bound the Disaggregation of Rainfall
The Multiplicative Discrete Random Cascade (MDRC) class of model is used to temporally disaggregate rainfall volumes through multiplying the volumes by random weights, which is repeated through multiple disaggregation levels. The model development involves the identification of probability density functions from which to sample the weights. The parameters of the probability density functions ar...
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ژورنال
عنوان ژورنال: Hydrology and Earth System Sciences
سال: 2000
ISSN: 1607-7938
DOI: 10.5194/hess-4-419-2000