Journal article 943 views
Uncertainty analysis of hydrological ensemble forecasts in a distributed model utilising short-range rainfall prediction
Hydrology and Earth System Sciences, Volume: 13, Issue: 3, Pages: 293 - 303
Swansea University Authors:
Ian Cluckie, Yunqing Xuan
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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...
Published in: | Hydrology and Earth System Sciences |
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ISSN: | 1607-7938 |
Published: |
2009
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URI: | https://cronfa.swan.ac.uk/Record/cronfa10540 |
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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 FGSEN 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 Science and Engineering - Faculty COLLEGE CODE FGSEN 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 |
|
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facultyofscienceandengineering |
hierarchy_top_title |
Faculty of Science and Engineering |
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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 |
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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 |
2009-03-31T03:11:56Z |
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1763750043257405440 |
score |
11.021648 |