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Uncertainty analysis of hydrological ensemble forecasts in a distributed model utilising short-range rainfall prediction

Y Xuan, I. D Cluckie, Y Wang, Ian Cluckie, Yunqing Xuan Orcid Logo

Hydrology and Earth System Sciences, Volume: 13, Issue: 3, Pages: 293 - 303

Swansea University Authors: Ian Cluckie, Yunqing Xuan Orcid Logo

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DOI (Published version): 10.5194/hess-13-293-2009

Abstract

Advances in mesoscale numerical weather predication make it possible to provide rainfall forecasts along with many other data fields at increasingly higher spatial resolutions. It is currently possible to incorporate high-resolution NWPs directly into flood forecasting systems in order to obtain an...

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Published in: Hydrology and Earth System Sciences
ISSN: 1607-7938
Published: 2009
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URI: https://cronfa.swan.ac.uk/Record/cronfa10540
first_indexed 2013-07-23T12:03:46Z
last_indexed 2018-02-09T04:39:24Z
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spelling 2013-11-21T14:21:52.6545338 v2 10540 2012-04-06 Uncertainty analysis of hydrological ensemble forecasts in a distributed model utilising short-range rainfall prediction d801af52a3cfb625308bd4301583064e Ian Cluckie Ian Cluckie true false 3ece84458da360ff84fa95aa1c0c912b 0000-0003-2736-8625 Yunqing Xuan Yunqing Xuan true false 2012-04-06 Advances in mesoscale numerical weather predication make it possible to provide rainfall forecasts along with many other data fields at increasingly higher spatial resolutions. It is currently possible to incorporate high-resolution NWPs directly into flood forecasting systems in order to obtain an extended lead time. It is recognised, however, that direct application of rainfall outputs from the NWP model can contribute considerable uncertainty to the final river flow forecasts as the uncertainties inherent in the NWP are propagated into hydrological domains and can also be magnified by the scaling process. As the ensemble weather forecast has become operationally available, it is of particular interest to the hydrologist to investigate both the potential and implication of ensemble rainfall inputs to the hydrological modelling systems in terms of uncertainty propagation. In this paper, we employ a distributed hydrological model to analyse the performance of the ensemble flow forecasts based on the ensemble rainfall inputs from a short-range high-resolution mesoscale weather model. The results show that: (1) The hydrological model driven by QPF can produce forecasts comparable with those from a raingauge-driven one; (2) The ensemble hydrological forecast is able to disseminate abundant information with regard to the nature of the weather system and the confidence of the forecast itself; and (3) the uncertainties as well as systematic biases are sometimes significant and, as such, extra effort needs to be made to improve the quality of such a system. Copyright © 2009 HESS - Hydrology and Earth System Sciences. Journal Article Hydrology and Earth System Sciences 13 3 293 303 1607-7938 31 3 2009 2009-03-31 10.5194/hess-13-293-2009 COLLEGE NANME COLLEGE CODE Swansea University 2013-11-21T14:21:52.6545338 2012-04-06T19:39:42.7281916 Faculty of Science and Engineering School of Engineering and Applied Sciences - Uncategorised Y Xuan 1 I. D Cluckie 2 Y Wang 3 Ian Cluckie 4 Yunqing Xuan 0000-0003-2736-8625 5
title Uncertainty analysis of hydrological ensemble forecasts in a distributed model utilising short-range rainfall prediction
spellingShingle Uncertainty analysis of hydrological ensemble forecasts in a distributed model utilising short-range rainfall prediction
Ian Cluckie
Yunqing Xuan
title_short Uncertainty analysis of hydrological ensemble forecasts in a distributed model utilising short-range rainfall prediction
title_full Uncertainty analysis of hydrological ensemble forecasts in a distributed model utilising short-range rainfall prediction
title_fullStr Uncertainty analysis of hydrological ensemble forecasts in a distributed model utilising short-range rainfall prediction
title_full_unstemmed Uncertainty analysis of hydrological ensemble forecasts in a distributed model utilising short-range rainfall prediction
title_sort Uncertainty analysis of hydrological ensemble forecasts in a distributed model utilising short-range rainfall prediction
author_id_str_mv d801af52a3cfb625308bd4301583064e
3ece84458da360ff84fa95aa1c0c912b
author_id_fullname_str_mv d801af52a3cfb625308bd4301583064e_***_Ian Cluckie
3ece84458da360ff84fa95aa1c0c912b_***_Yunqing Xuan
author Ian Cluckie
Yunqing Xuan
author2 Y Xuan
I. D Cluckie
Y Wang
Ian Cluckie
Yunqing Xuan
format Journal article
container_title Hydrology and Earth System Sciences
container_volume 13
container_issue 3
container_start_page 293
publishDate 2009
institution Swansea University
issn 1607-7938
doi_str_mv 10.5194/hess-13-293-2009
college_str Faculty of Science and Engineering
hierarchytype
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
document_store_str 0
active_str 0
description Advances in mesoscale numerical weather predication make it possible to provide rainfall forecasts along with many other data fields at increasingly higher spatial resolutions. It is currently possible to incorporate high-resolution NWPs directly into flood forecasting systems in order to obtain an extended lead time. It is recognised, however, that direct application of rainfall outputs from the NWP model can contribute considerable uncertainty to the final river flow forecasts as the uncertainties inherent in the NWP are propagated into hydrological domains and can also be magnified by the scaling process. As the ensemble weather forecast has become operationally available, it is of particular interest to the hydrologist to investigate both the potential and implication of ensemble rainfall inputs to the hydrological modelling systems in terms of uncertainty propagation. In this paper, we employ a distributed hydrological model to analyse the performance of the ensemble flow forecasts based on the ensemble rainfall inputs from a short-range high-resolution mesoscale weather model. The results show that: (1) The hydrological model driven by QPF can produce forecasts comparable with those from a raingauge-driven one; (2) The ensemble hydrological forecast is able to disseminate abundant information with regard to the nature of the weather system and the confidence of the forecast itself; and (3) the uncertainties as well as systematic biases are sometimes significant and, as such, extra effort needs to be made to improve the quality of such a system. Copyright © 2009 HESS - Hydrology and Earth System Sciences.
published_date 2009-03-31T18:19:35Z
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score 11.048302

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