Böing, SJ, Birch, CE orcid.org/0000-0001-9384-2810, Rabb, BL et al. (1 more author) (2020) A percentile‐based approach to rainfall scenario construction for surface‐water flood forecasts. Meteorological Applications, 27 (6). e1963. ISSN 1350-4827
Abstract
A novel technique to produce reasonable worst‐case rainfall scenarios from ensemble forecasts is presented. This type of scenario is relevant for predicting the risk of localized, intense rainfall events with a duration between 15 min and several hours. Such rainfall events can cause surface‐water (pluvial) flooding. Producing useful forecasts of these events at lead times of more than a few hours is challenging due to the precision and accuracy in rainfall intensity, duration and location that is required. The technique described here addresses these challenges by constructing appropriate scenarios using a neighbourhood technique in combination with ensemble forecasting. It is similar to the distance‐dependent depth–duration analysis described in earlier studies, but it introduces an additional post‐processing step based on probability distribution functions of rainfall accumulation near a location of interest. This additional step makes the reasonable worst‐case scenarios less dependent on grid‐scale behaviour, and helps to generate scenarios with a consistent interpretation. The method is used to compare forecasts with a lead time of 6–36 hr to radar data for several case studies that occurred in Yorkshire. These comparisons also introduce new techniques to present maps of the reasonable worst‐case rainfall accumulation at each location.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 The Authors. Meteorological Applications published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | flood forecasting; neighbourhood processing method; rainfall prediction |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Inst for Climate & Atmos Science (ICAS) (Leeds) |
Funding Information: | Funder Grant number NERC (Natural Environment Research Council) NE/P011160/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 04 Dec 2020 12:35 |
Last Modified: | 04 Dec 2020 12:35 |
Status: | Published |
Publisher: | Wiley |
Identification Number: | 10.1002/met.1963 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:168676 |