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Rainfall uncertainty for extreme events in NWP downscaling model

Michaela Bray, Dawei Han, Yunqing Xuan Orcid Logo, Paul Bates, Michael Williams

Hydrological Processes, Volume: 25, Issue: 9, Pages: 1397 - 1406

Swansea University Author: Yunqing Xuan Orcid Logo

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DOI (Published version): 10.1002/hyp.7905

Abstract

Extreme rainfall events are among the very foci of the stakeholders and policy makers in flood risk management. This paper reveals the potential of using numerical weather prediction in this context. It was one of the first in this area that has systematically studied the NWP on extreme rainfall in...

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Published in: Hydrological Processes
ISSN: 0885-6087
Published: 2011
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URI: https://cronfa.swan.ac.uk/Record/cronfa10413
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first_indexed 2013-07-23T12:06:41Z
last_indexed 2018-02-09T04:39:09Z
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spelling 2016-08-17T14:14:04.7235883 v2 10413 2013-09-03 Rainfall uncertainty for extreme events in NWP downscaling model 3ece84458da360ff84fa95aa1c0c912b 0000-0003-2736-8625 Yunqing Xuan Yunqing Xuan true false 2013-09-03 CIVL Extreme rainfall events are among the very foci of the stakeholders and policy makers in flood risk management. This paper reveals the potential of using numerical weather prediction in this context. It was one of the first in this area that has systematically studied the NWP on extreme rainfall in the context of hydrological use. Journal Article Hydrological Processes 25 9 1397 1406 0885-6087 31 12 2011 2011-12-31 10.1002/hyp.7905 Extreme rainfall events are among the very foci of the stakeholders and policy makers in flood risk management. This paper reveals the potential of using numerical weather prediction in this contxt. It was one of the first in this area that has systematically studied the NWP on extreme rainfall in the context of hydrological use. This paper continues my research line on hydrometeorological modelling and QPF highlighting the impact of modelling uncertainty, which provides a very important reference to practitioners. I supervised the research with expertise in numerical weather prediction and built the initial forecast system used by the research. COLLEGE NANME Civil Engineering COLLEGE CODE CIVL Swansea University 2016-08-17T14:14:04.7235883 2013-09-03T06:39:23.0000000 College of Engineering Engineering Michaela Bray 1 Dawei Han 2 Yunqing Xuan 0000-0003-2736-8625 3 Paul Bates 4 Michael Williams 5
title Rainfall uncertainty for extreme events in NWP downscaling model
spellingShingle Rainfall uncertainty for extreme events in NWP downscaling model
Yunqing Xuan
title_short Rainfall uncertainty for extreme events in NWP downscaling model
title_full Rainfall uncertainty for extreme events in NWP downscaling model
title_fullStr Rainfall uncertainty for extreme events in NWP downscaling model
title_full_unstemmed Rainfall uncertainty for extreme events in NWP downscaling model
title_sort Rainfall uncertainty for extreme events in NWP downscaling model
author_id_str_mv 3ece84458da360ff84fa95aa1c0c912b
author_id_fullname_str_mv 3ece84458da360ff84fa95aa1c0c912b_***_Yunqing Xuan
author Yunqing Xuan
author2 Michaela Bray
Dawei Han
Yunqing Xuan
Paul Bates
Michael Williams
format Journal article
container_title Hydrological Processes
container_volume 25
container_issue 9
container_start_page 1397
publishDate 2011
institution Swansea University
issn 0885-6087
doi_str_mv 10.1002/hyp.7905
college_str College of Engineering
hierarchytype
hierarchy_top_id collegeofengineering
hierarchy_top_title College of Engineering
hierarchy_parent_id collegeofengineering
hierarchy_parent_title College of Engineering
department_str Engineering{{{_:::_}}}College of Engineering{{{_:::_}}}Engineering
document_store_str 0
active_str 0
description Extreme rainfall events are among the very foci of the stakeholders and policy makers in flood risk management. This paper reveals the potential of using numerical weather prediction in this context. It was one of the first in this area that has systematically studied the NWP on extreme rainfall in the context of hydrological use.
published_date 2011-12-31T03:19:55Z
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score 10.8781185