A stochastic space-time rainfall forecasting system for real time flow forecasting I: Development of MTB conditional rainfall scenario generator
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 justificatio...
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doaj-991feadda5e6489692aade82fdd905782020-11-24T21:39:34ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382000-01-0144603615A stochastic space-time rainfall forecasting system for real time flow forecasting I: Development of MTB conditional rainfall scenario generatorD. MellorJ. SheffieldP. E. O'ConnellP. E. O'ConnellA. V. MetcalfeThe 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.</p> <p style='line-height: 20px;'><b>Keywords: </b>MTB model, space-time rainfall field model, rainfall radar, HYREX, real-time flow forecasting</p>http://www.hydrol-earth-syst-sci.net/4/603/2000/hess-4-603-2000.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
D. Mellor J. Sheffield P. E. O'Connell P. E. O'Connell A. V. Metcalfe |
spellingShingle |
D. Mellor J. Sheffield P. E. O'Connell P. E. O'Connell A. V. Metcalfe A stochastic space-time rainfall forecasting system for real time flow forecasting I: Development of MTB conditional rainfall scenario generator Hydrology and Earth System Sciences |
author_facet |
D. Mellor J. Sheffield P. E. O'Connell P. E. O'Connell A. V. Metcalfe |
author_sort |
D. Mellor |
title |
A stochastic space-time rainfall forecasting system for real time flow forecasting I: Development of MTB conditional rainfall scenario generator |
title_short |
A stochastic space-time rainfall forecasting system for real time flow forecasting I: Development of MTB conditional rainfall scenario generator |
title_full |
A stochastic space-time rainfall forecasting system for real time flow forecasting I: Development of MTB conditional rainfall scenario generator |
title_fullStr |
A stochastic space-time rainfall forecasting system for real time flow forecasting I: Development of MTB conditional rainfall scenario generator |
title_full_unstemmed |
A stochastic space-time rainfall forecasting system for real time flow forecasting I: Development of MTB conditional rainfall scenario generator |
title_sort |
stochastic space-time rainfall forecasting system for real time flow forecasting i: development of mtb conditional rainfall scenario generator |
publisher |
Copernicus Publications |
series |
Hydrology and Earth System Sciences |
issn |
1027-5606 1607-7938 |
publishDate |
2000-01-01 |
description |
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.</p> <p style='line-height: 20px;'><b>Keywords: </b>MTB model, space-time rainfall field model, rainfall radar, HYREX, real-time flow forecasting</p> |
url |
http://www.hydrol-earth-syst-sci.net/4/603/2000/hess-4-603-2000.pdf |
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