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A stochastic space-time rainfall forecasting system for real time flow forecasting I: Development of MTB conditional rainfall scenario generator

Lookup NU author(s): Justin Sheffield, Professor Enda O'Connell, Dr Andrew Metcalfe



The need for the development of a method for generating an ensemble of rainfall scenarios, which are conditioned on the observed rainfall, and its place in the HYREX programme is discussed. A review of stochastic models for rainfall, and rainfall forecasting techniques, is followed by a justification for the choice of the Modified Turning Bands (MTB) model in this context. This is a stochastic model of rainfall which is continuous over space and time, and which reproduces features of real rainfall fields at four distinct scales: raincells, cluster potential regions, rainbands and the overall outline of a storm at the synoptic scale. The model can be used to produce synthetic data sets, in the same format as data from a radar. An inversion procedure for inferring a construction of the MTB model which generates a given sequence of radar images is described. This procedure is used to generate an ensemble of future rainfall scenarios which are consistent with a currently observed storm. The combination of deterministic modelling at the large scales and stochastic modelling at smaller scales, within the MTB model, makes the system particularly suitable for short-term forecasts. As the lead time increases, so too does the variability across the set of generated scenarios.

Publication metadata

Author(s): Mellor D, Sheffield J, O'Connell PE, Metcalfe AV

Publication type: Article

Publication status: Published

Journal: Hydrology and Earth System Sciences

Year: 2000

Volume: 4

Issue: 4

Pages: 603-615

Print publication date: 01/01/2000

Date deposited: 01/01/1970

ISSN (print): 1027-5606

ISSN (electronic): 1607-7938

Publisher: Copernicus