The University of Southampton
University of Southampton Institutional Repository

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

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

HYREX, MTB model, Rainfall radar, Real-time flow forecasting, Space-time rainfall model
1027-5606
603-615
Mellor, D.
473c8d31-71b8-4a7e-8202-ae33da69ca00
Sheffield, J.
dd66575b-a4dc-4190-ad95-df2d6aaaaa6b
O'Connell, P. E.
e2364595-d542-4de5-af46-866b09c16033
Metcalfe, A. V.
f3e7156d-b9a5-417d-b486-f5dfa3ee10ef
Mellor, D.
473c8d31-71b8-4a7e-8202-ae33da69ca00
Sheffield, J.
dd66575b-a4dc-4190-ad95-df2d6aaaaa6b
O'Connell, P. E.
e2364595-d542-4de5-af46-866b09c16033
Metcalfe, A. V.
f3e7156d-b9a5-417d-b486-f5dfa3ee10ef

Mellor, D., Sheffield, J., O'Connell, P. E. and Metcalfe, A. V. (2000) 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, 4 (4), 603-615. (doi:10.5194/hess-4-603-2000).

Record type: Article

Abstract

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.

This record has no associated files available for download.

More information

Published date: December 2000
Keywords: HYREX, MTB model, Rainfall radar, Real-time flow forecasting, Space-time rainfall model

Identifiers

Local EPrints ID: 480409
URI: http://eprints.soton.ac.uk/id/eprint/480409
ISSN: 1027-5606
PURE UUID: 6fbe9aa8-d4e0-4137-846d-ef11024db501
ORCID for J. Sheffield: ORCID iD orcid.org/0000-0003-2400-0630

Catalogue record

Date deposited: 01 Aug 2023 21:43
Last modified: 17 Mar 2024 03:40

Export record

Altmetrics

Contributors

Author: D. Mellor
Author: J. Sheffield ORCID iD
Author: P. E. O'Connell
Author: A. V. Metcalfe

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×