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Coupled hydro-meteorological modelling on a HPC platform for high-resolution extreme weather impact study

Dehua Zhu, Shirley Echendu, Yunqing Xuan Orcid Logo, Michael Webster Orcid Logo, Ian Cluckie

Hydrology and Earth System Sciences, Volume: 20, Issue: 12, Pages: 4707 - 4715

Swansea University Authors: Dehua Zhu, Shirley Echendu, Yunqing Xuan Orcid Logo, Michael Webster Orcid Logo, Ian Cluckie

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DOI (Published version): 10.5194/hess-20-4707-2016

Abstract

Impact-focused studies of extreme weather require coupling of accurate simulations of weather and climate systems and impact-measuring hydrological models which themselves demand larger computer resources. In this paper, we present a preliminary analysis of a high-performance computing (HPC)-based h...

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Published in: Hydrology and Earth System Sciences
ISSN: 1607-7938 1607-7938
Published: 2016
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URI: https://cronfa.swan.ac.uk/Record/cronfa31336
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In this paper, we present a preliminary analysis of a high-performance computing (HPC)-based hydrological modelling approach, which is aimed at utilizing and maximizing HPC power resources, to support the study on extreme weather impact due to climate change. Here, four case studies are presented through implementation on the HPC Wales platform of the UK mesoscale meteorological Unified Model (UM) with high-resolution simulation suite UKV, alongside a Linux-based hydrological model, Hydrological Predictions for the Environment (HYPE). The results of this study suggest that the coupled hydro-meteorological model was still able to capture the major flood peaks, compared with the conventional gauge- or radar-driving forecast, but with the added value of much extended forecast lead time. 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spelling 2021-01-07T16:33:42.4982337 v2 31336 2016-11-29 Coupled hydro-meteorological modelling on a HPC platform for high-resolution extreme weather impact study bb0bbd48a4b8e512ef296fa8caa3155f Dehua Zhu Dehua Zhu true false 700ec6d4c902c6ec0d312e217a69a1d4 Shirley Echendu Shirley Echendu true false 3ece84458da360ff84fa95aa1c0c912b 0000-0003-2736-8625 Yunqing Xuan Yunqing Xuan true false b6a811513b34d56e66489512fc2c6c61 0000-0002-7722-821X Michael Webster Michael Webster true false d801af52a3cfb625308bd4301583064e Ian Cluckie Ian Cluckie true false 2016-11-29 FGSEN Impact-focused studies of extreme weather require coupling of accurate simulations of weather and climate systems and impact-measuring hydrological models which themselves demand larger computer resources. In this paper, we present a preliminary analysis of a high-performance computing (HPC)-based hydrological modelling approach, which is aimed at utilizing and maximizing HPC power resources, to support the study on extreme weather impact due to climate change. Here, four case studies are presented through implementation on the HPC Wales platform of the UK mesoscale meteorological Unified Model (UM) with high-resolution simulation suite UKV, alongside a Linux-based hydrological model, Hydrological Predictions for the Environment (HYPE). The results of this study suggest that the coupled hydro-meteorological model was still able to capture the major flood peaks, compared with the conventional gauge- or radar-driving forecast, but with the added value of much extended forecast lead time. The high-resolution rainfall estimation produced by the UKV performs similarly to that of radar rainfall products in the first 2–3 days of tested flood events, but the uncertainties particularly increased as the forecast horizon goes beyond 3 days. This study takes a step forward to identify how the online mode approach can be used, where both numerical weather prediction and the hydrological model are executed, either simultaneously or on the same hardware infrastructures, so that more effective interaction and communication can be achieved and maintained between the models. But the concluding comments are that running the entire system on a reasonably powerful HPC platform does not yet allow for real-time simulations, even without the most complex and demanding data simulation part. Journal Article Hydrology and Earth System Sciences 20 12 4707 4715 1607-7938 1607-7938 29 11 2016 2016-11-29 10.5194/hess-20-4707-2016 COLLEGE NANME Science and Engineering - Faculty COLLEGE CODE FGSEN Swansea University 2021-01-07T16:33:42.4982337 2016-11-29T21:45:06.6749705 Faculty of Science and Engineering School of Engineering and Applied Sciences - Uncategorised Dehua Zhu 1 Shirley Echendu 2 Yunqing Xuan 0000-0003-2736-8625 3 Michael Webster 0000-0002-7722-821X 4 Ian Cluckie 5 31336__4290__957f2326ac5a4a9b835deacf59019116.pdf zhu2016.pdf 2016-12-05T14:03:14.8600000 Output 2336789 application/pdf Version of Record true 2016-12-05T00:00:00.0000000 Distributed under the terms of a Creative Commons Attribution 4.0 (CC-BY) Licence. true eng https://creativecommons.org/licenses/by/4.0/
title Coupled hydro-meteorological modelling on a HPC platform for high-resolution extreme weather impact study
spellingShingle Coupled hydro-meteorological modelling on a HPC platform for high-resolution extreme weather impact study
Dehua Zhu
Shirley Echendu
Yunqing Xuan
Michael Webster
Ian Cluckie
title_short Coupled hydro-meteorological modelling on a HPC platform for high-resolution extreme weather impact study
title_full Coupled hydro-meteorological modelling on a HPC platform for high-resolution extreme weather impact study
title_fullStr Coupled hydro-meteorological modelling on a HPC platform for high-resolution extreme weather impact study
title_full_unstemmed Coupled hydro-meteorological modelling on a HPC platform for high-resolution extreme weather impact study
title_sort Coupled hydro-meteorological modelling on a HPC platform for high-resolution extreme weather impact study
author_id_str_mv bb0bbd48a4b8e512ef296fa8caa3155f
700ec6d4c902c6ec0d312e217a69a1d4
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author_id_fullname_str_mv bb0bbd48a4b8e512ef296fa8caa3155f_***_Dehua Zhu
700ec6d4c902c6ec0d312e217a69a1d4_***_Shirley Echendu
3ece84458da360ff84fa95aa1c0c912b_***_Yunqing Xuan
b6a811513b34d56e66489512fc2c6c61_***_Michael Webster
d801af52a3cfb625308bd4301583064e_***_Ian Cluckie
author Dehua Zhu
Shirley Echendu
Yunqing Xuan
Michael Webster
Ian Cluckie
author2 Dehua Zhu
Shirley Echendu
Yunqing Xuan
Michael Webster
Ian Cluckie
format Journal article
container_title Hydrology and Earth System Sciences
container_volume 20
container_issue 12
container_start_page 4707
publishDate 2016
institution Swansea University
issn 1607-7938
1607-7938
doi_str_mv 10.5194/hess-20-4707-2016
college_str Faculty of Science and Engineering
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hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Engineering and Applied Sciences - Uncategorised{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Uncategorised
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description Impact-focused studies of extreme weather require coupling of accurate simulations of weather and climate systems and impact-measuring hydrological models which themselves demand larger computer resources. In this paper, we present a preliminary analysis of a high-performance computing (HPC)-based hydrological modelling approach, which is aimed at utilizing and maximizing HPC power resources, to support the study on extreme weather impact due to climate change. Here, four case studies are presented through implementation on the HPC Wales platform of the UK mesoscale meteorological Unified Model (UM) with high-resolution simulation suite UKV, alongside a Linux-based hydrological model, Hydrological Predictions for the Environment (HYPE). The results of this study suggest that the coupled hydro-meteorological model was still able to capture the major flood peaks, compared with the conventional gauge- or radar-driving forecast, but with the added value of much extended forecast lead time. The high-resolution rainfall estimation produced by the UKV performs similarly to that of radar rainfall products in the first 2–3 days of tested flood events, but the uncertainties particularly increased as the forecast horizon goes beyond 3 days. This study takes a step forward to identify how the online mode approach can be used, where both numerical weather prediction and the hydrological model are executed, either simultaneously or on the same hardware infrastructures, so that more effective interaction and communication can be achieved and maintained between the models. But the concluding comments are that running the entire system on a reasonably powerful HPC platform does not yet allow for real-time simulations, even without the most complex and demanding data simulation part.
published_date 2016-11-29T03:38:17Z
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